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IN DEGREE PROJECT MECHANICAL ENGINEERING,SECOND CYCLE, 30 CREDITS
, STOCKHOLM SWEDEN 2019
A Feasibility Study of an Automated Repair Process using Laser Metal Deposition (LMD) with a Machine Integrated Component Measuring Solution
FLORIAN SÄGER
KTH ROYAL INSTITUTE OF TECHNOLOGYSCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT
I
KTH – Royal Institute of Technology
Production Engineering and Management
A Feasibility Study of an
Automated Repair Process using Laser
Metal Deposition (LMD) with a Machine
Integrated Component Measuring Solution
Master Thesis (M.Sc.)
Florian Säger
Supervisor: Zhao Xiaoyu
Examiner: Amir Rashid
In Cooperation with
Trumpf Maskin AB, Trollhättan, Sweden
II
Statement of Originality
I hereby confirm that I have written the accompanying thesis by myself, without con-
tributions from any sources other than those cited in the text and acknowledgements.
This applies also to all graphics, drawings, tables and images included in the thesis.
Stockholm, 22. August 2018
Signature
I
Florian Säger
I
Abstract (English)
The repair of worn or damaged components is becoming more attractive to manufac-
turers, since it enables them to save resources, like raw material and energy. With
that costs can be reduced, and profit can be maximised. When enabling the re-use of
components, the lifetime of a component can be extended, which leads to improved
sustainability measures. However, repair is not applied widely, mainly because costs
of repairing are overreaching the costs of purchasing a new component.
One of the biggest expense factors of repairing a metal component is the labour-
intense part of identifying and quantifying worn or damages areas with the use of
various external measurement systems. An automated measuring process would re-
duce application cost significantly and allow the applications to less cost intense
component.
To automate the repair process, in a one-machine solution, it is prerequisite that a
measuring device is included in the machine enclosure. For that, different measuring
solutions are being assessed towards applicability on the “Trumpf TruLaser Cell
3000 Series”. A machine that uses the Laser Metal Deposition (LMD) technology to
print, respectively weld, metal on a target surface.
After a theoretical analysis of different solutions, the most sufficient solution is being
validated by applying to the machine. During the validation a surface models from a
test-component is generated. The result is used to determine the capability of detect-
ing worn areas by doing an automated target-actual comparison with a specialised
CAM program. By verifying the capability of detecting worn areas and executing a
successful repair, the fundamentals of a fully automated repair process can be proven
as possible in a one-machine solution.
Key Words:
LMD – Laser Metal Deposition, Laser Cladding, Repair of Metal Components,
Reengineering, Reverse Engineering, Detection of Worn and Damaged Areas, Laser
Scanner, Measruing of Components in Machine Enclosure, Additive Manufacturing,
Measuring
II
Florian Säger
II
Abstrakt (Svenska)
Tillverkare har börjat se stora möjligheter i att reparera slitna eller skadade kompo-
nenter som ett sätt att spara resurser, så som råmaterial och energi. Med den bespa-
ringen minskar kostnaderna och vinsten kan således maximeras. Reparation möjlig-
gör även återanvändning av komponenter, vilket förlänger komponentens livslängd
och leder till förbättrade hållbarhetsåtgärder. Dock tillämpas reparation inte i någon
stor utsträckning i nuläget, främst eftersom kostnaderna för reparation överstiger
kostnaderna för att köpa en ny komponent.
En av de största kostnaderna för att reparera en metallkomponent är att identifiera
och kvantifiera slitna eller skadade områden med hjälp av olika externa mätsystem,
som är en väldigt arbetsintensiv process. En automatiserad mätprocess skulle minska
avsökningskostnaden avsevärt och således reducera den totala kostnaden för kompo-
nenten.
För att möjliggöra en automatiserad reparationsprocess i en enda maskinlösning är
det en förutsättning att en mätanordning ingår i maskinhöljet. Därför har olika mät-
ningslösningar utvärderats med avseende på användbarhet i "TRUMPF TruLaser
Cell 3000 Series", vilket är en maskin som använder Laser Metall Deposition-teknik
(LMD-teknik) för att skriva ut och svetsa metall på en definierad yta.
En teoretisk analys av olika lösningar har utförts, där den teoretiskt mest lämpliga
lösningen validerades genom att appliceras till maskinen. Valideringen genererade en
modell av ytan av en testkomponent. Sedan utfördes en automatiserad, målrelaterad
jämförelse med ett specialiserat CAM-program baserat på modellresultatet, för att
bestämma möjligheten att upptäcka slitna områden. Genom att verifiera förmågan att
upptäcka slitna områden samt genomförandet av en lyckad reparation kan grunden
för en helt automatiserad reparationsprocess bevisas som möjlig i en enda maskin-
lösning.
Key ords:
LMD – Laser Metal Deposition, Laserbeklädnad, Reperera av metall komponenter,
Reengineering, omvänd teknik, Detektion av slitna och skadade områden, Laser
Scanner, Mätning av komponenter i maskinskåp, Mätning av komponenter i maskin-
skåp, mätning
III
Florian Säger
III
Abstrakt (Deutsch)
Das reparieren von abgenutzten oder beschädigten Komponenten wird immer attrak-
tiver für Hersteller. Es ermöglicht es Ressourcen einzusparen wie beispielsweise
Rohmaterial und Energie, was die Lebenszeit einer Komponente verlängert und da-
mit die Nachhaltigkeit verbessert.
Allerdings ist Reparieren nach wie vor nicht weit verbreitet, hauptsächlich dadurch
bedingt, dass die Reparaturkosten die Kosten für eine neue Komponente übersteigen.
Einer der größten Kostenfaktoren des reparieren einer Metallkomponente ist der Ar-
beitsintensive Teil der Identifizierung und Quantifizierung des abgenutzten oder be-
schädigten Bereichs mit verschiedensten externen Vermessung Systemen. Ein auto-
matisierter Vermessungsprozess würde die Kosten signifikant reduzieren und neue
Applikationen ermöglichen.
Das automatisieren der gesamte Prozesskette – in einer Single-Maschinenlösung –
erfordert, dass eine Messeinrichtung im Bearbeitungsraum der Maschine angebracht
wird. Dafür werden verschiedene Lösungen nach Anwendbarkeit an der Trumpf La-
ser Cell 3000 Serie hin beurteilt. Eine Maschine, welche Laser Metal Deposition
(LMD) als Technologie anwendet um Material auf Oberflächen aufzubringen.
Nach einer theoretischen Analyse verschiedener Lösungen wird die beste Lösung va
durch anbringen an die Maschine validiert. Bei der Validierung wird ein Oberflä-
chenmodel erzeugt. Das Ergebnis wird dann genutzt um die Fähigkeit zu belegen,
dass beschädigte Stellen, durch einen Soll-Ist-Vergleich in einem speziellen CAM
Programm, automatisch detektiert werden können. Basierend auf diesem Beleg und
mit dem Ergebnis eine Komponente erfolgreich reparieren zu können, gilt die These
eines automatisierten Reparaturprozesses in einer Single-Maschinenlösung als be-
weisen.
Stichwörter:
LMD – Laser Metal Deposition, Laserauftragsschweißen, Detektieren von abgenutz-
ten oder beschädigten Oberflächen, Reengineering, Reverse Engineering, Detection
of Worn and Damaged Areas, Laser Scanner, Vermessen von Komponenten im Ma-
schinenbearbeitungsraum, Additive Fertigung, Vermessen
IV
Florian Säger
IV
Acknowledgment
I would like to credit some persons in particular, who helped me to accomplish this
thesis in this way.
First of all, my supervisor at Trumpf in Sweden Hubert Wilbs, who gave me the
opportunity to execute this project at his company and supported me with all needed
resources and gave continues productive feedback when needed.
Sebastian Kaufmann, my supervisor at Trumpf in Germany who supported me
greatly with ideas and the right questions. He was also the one who made it possible
that the solution could be validate on the machine. He further gathered experts in
their filed in order to realise the test over the full process chain.
Further I would like to accredit Amir Rashid, my examiner at KTH who was inter-
ested in this project from minute one and was in contact with me during the entire
project to make the best outcome possible for this project. In the same way I would
like to mention Xiaoyu Zhao, my supervisor at KTH. She ensured at all times that I
am on the right track and I have all the information needed to make this thesis suc-
cessful.
Another thank you is dedicated to the CAM expert Christian Walter from
“Netvision
Datentechnik GmbH u. Co. KG”, who substantial contributed to the success with his
knowledge and support during the validation and the post-calculation of the generat-
ed CAM models. Without him the reverse engineering and with that, the entire vali-
dation process wouldn’t have been possible.
In addition to that I would like to mention Lars Östergren form GKN Aerospace
Sweden AB, who – as an important customer from Trump – enabled me to see how
the LMD process is applied to real cases. He further made it possible for me to attend
a CAM course.
Furthermore, I would like to mention Anna Bolay who helped me with all questions
in the company and assistant greatly to the success of this thesis and even more im-
portant made this thesis possible. She got me in contact with Mr. Wilbs after ap-
proaching her with my idea. The same help was at all times made possible by Karin
Gustafsson, she ensured that I had all the information needed form the company to
accomplish this thesis work.
A truly unique “thank you” is dedicated to my family and my girlfriend. Thank you
for the unlimited support along the entire way, I am grateful for your boundless en-
couragement.
Thank you, each and every one of you for supporting and realising this thesis project
and thus me on my way to get the title as Master of Science!
Florian Säger
V
Table of Content
I. List of Figures................................................................................................... VII
II. List of Tables ...................................................................................................... IX
List of Abbreviations ..................................................................................................... X
1 Introduction .......................................................................................................... 1
1.1 Aim of this Thesis ...................................................................................... 2
1.2 Motivation for Optimising the Measuring Process .................................... 3
1.3 Structure of the Thesis ................................................................................ 5
1.4 Research Question ...................................................................................... 6
1.5 Scope and Definition of the Thesis ............................................................ 7
1.6 Goal of the Thesis ....................................................................................... 7
1.7 The Company Trumpf ................................................................................ 7
1.7.1 The Additive Manufacturing Products from Trumpf ............................ 9
2 Theory ................................................................................................................. 11
2.1 Additive Manufacturing Processes ........................................................... 11
2.2 The Laser Metal Deposition (LMD) Process ........................................... 12
2.2.1 Main Application Fields of LMD ....................................................... 15
2.3 The Repair Process using LMD ............................................................... 16
2.3.1 The Current Process of Repairing Components using LMD .............. 17
2.3.2 The Future Process of Repairing ......................................................... 20
2.4 Sensor Systems for Surface Measurement ............................................... 22
3 Methodology to Evaluate Feasible Measuring Solutions ............................... 26
3.1 Qualitative Assessment of the Measuring Solutions ................................ 28
3.2 Quantitative Evaluating of the Measuring Solutions ............................... 29
4 Analysis of Most Suitable Measuring Solutions for the Application ............ 33
4.1 Possible Solution 1: Laser Line Sensor from Micro-Epsilon “LLT
2900-100” ................................................................................................. 33
4.2 Possible Solution 2: Laser Line Sensor from LMI Technologies
“Gocator 2440” ......................................................................................... 38
4.3 Possible Solution 3: Stereo Camera from GOM “ATOS Core 200” ....... 42
4.4 Result of Measuring Solution Analysis .................................................... 46
5 Validation of Proposed System through Experiments ................................... 48
Florian Säger
VI
5.1 Validation Setup and used Equipment ..................................................... 49
5.2 The Validation Procedure ......................................................................... 51
5.3 Validation Results .................................................................................... 53
6 Identification of Future Work Packages based on Validation ...................... 54
7 Conclusion of the Work ..................................................................................... 56
III. References ........................................................................................................... 58
IV. Appendix 1 .......................................................................................................... 60
Florian Säger
VII
I. List of Figures
Figure 1 - The current and future LMD repair process in a simplified version.
Showing the improvement aims, where blue colour represents
process steps involving mainly manual work and green colour
representing automated process steps. ......................................................... 2
Figure 2 - Overview of the thesis structure in a flow diagram.......................................... 5
Figure 3 - Trumpf Logo. Source: (Trumpf Media Server 2018)....................................... 8
Figure 4 - LMF process, where the laser currently melts a metal powder layer.
Source: (Trumpf Media Server 2018) ......................................................... 9
Figure 5 - The LMD process in action, here the nozzle can be seen during
processing metal powder onto a spinning metal disc. Source:
(Trumpf Media Server 2018) .................................................................... 10
Figure 6 – The nozzle of the LMD while the process is in work. The laser melts
the surface of the target and adds powder into the melt pool. The
process is shileded by shiled gas. Source: (Petrat, Graf, Gumenyuk,
& Rethmeier, 2016, p. 762) ....................................................................... 12
Figure 7 – A macro caption of the nozzle with active powder feed. (1) indicates
the intersection of the powder outlets and the focus of the laser
beam. This also defines the working distance to the target (D).
Source: (TRUMPF 2018c) ........................................................................ 13
Figure 8 - The LMD nozzle Trumpf uses in golden/bronze colour. The
mechanics seen above are the optics for the laser focus and process
surveience. Source: (TRUMPF 2018c) ..................................................... 14
Figure 9 - The Trumpf TruLaser Cell 3000 Series. Source: (Trumpf Media
Server 2018) .............................................................................................. 15
Figure 10 - LMD process while working, done on a shaft (used as base material)
to create a helix. Further in golden colour the nozzle can be seen.
Source: (Trumpf Media Server 2018) ....................................................... 16
Figure 11 – Taxonomy of measuring principles ordered according to their
physical technique used. Own graphic, based on (Bellocchio,
Borghese, Ferrari, & Piuri, 2013, p. 21) .................................................... 23
Figure 12 - PDCA (Plan-Do-Check-Act)-Cycle for Sensor Assessment ....................... 26
Figure 13 – A graphical representation of the methodology applied, to assess the
best measuring system. .............................................................................. 27
Figure 14 - Micro-Epsilon laser line sensor. Source: (Micro Epsilon - Datasheet
2018, p. 3) .................................................................................................. 33
Figure 15 - Radar Chart for solution 1: The result of the Micro-Epsilon laser line
sensor shown in a graphical way, for all eight rated factors. .................... 36
Figure 16 - LMI Gocator 2440 laser line sensor. Source: (LMI Gocator
Technical Specification 2018, p. 1) ........................................................... 38
Figure 17 - Radar Chart for solution 2: The result of the LMI laser line sensor
shown in a graphical way, for all eight rated factors. ................................ 40
Florian Säger
VIII
Figure 18 - GOM ATOS Core 200 sensor mounted on a tripod, with illustrated
components being measured on the left side. Source: (GOM ATOS
Core Homepage 2018) ............................................................................... 42
Figure 19 - Radar Chart for solution 3: The result of the GOM stereo camera
shown in a graphical way, for all eight rated factors. ................................ 44
Figure 20 - Overlay of all three rated solutions in one radar chart, ................................ 46
Figure 21 - The setup as used for the tests of the sensor. The sensor can be seen
attached to the machine head and connected to the computer. ................. 49
Figure 22 - Three types of the demonstration parts used for the test. All made of
sheet metal and stapled together with welding spots, used for the
validation. Left to right: 1) clear part, 2) LMD coated part
crosswise to the sheet metal layers, 3) chalk sprayed clear part ............... 50
Figure 23 - Close caption of the sensor next to the machine head, mounted with
the magnetic arm. ...................................................................................... 51
Figure 24 - The result of scan number 17, viewed in Scan Control 3D Viewer
3.1. ............................................................................................................. 52
Figure 25 - Blind spots during the measurements, as the angle towards the sensor
gets greater then 180 degrees. ................................................................... 52
Figure 26 - The scanned data imported to the ADEM CAM software (in green),
with the processed additive lines (in yellow) along the surface. ............... 53
Florian Säger
IX
II. List of Tables
Table 1 - Extract of the product portfolio of Trumpf (TRUMPF 2018d) ......................... 8
Table 2 - Detailed Process Steps of the process step as carried out at some
Trumpf customers (Source: In a less detailed version, form a
customer of Trumpf in Sweden, which wants to stay anonymous) ........... 18
Table 3 - Rating and the respective justifications for each factor, to compare
possible solutions ...................................................................................... 30
Table 4 - Rating of Solution 1: Laser Line Sensor “LLT 2900-100” from Micro-
Epsilon ....................................................................................................... 34
Table 5 - Rating of Solution 2: Laser Line Sensor "Gocator 2440" from LMI
Technologies ............................................................................................. 39
Table 6 - Rating of Solution 3: Stereo Camera "ATOS Core 200" from GOM ............. 43
Florian Säger
X
List of Abbreviations
LMD Laser Metal Deposition
LMF Laser Metal Fusion
PLC Product Life Cycle
GHG Greenhouse gases
AM Additive Manufacturing
CAD Computer-aided Design
CAM Computer-aided manufacturing
NC Numerical Code
USP Unique Selling Proposition
CMM Coordinate-Measruing Machine
RQ Research Question
SDK Software development kit
Florian Säger
1
1 Introduction
This thesis project was carried out together with Trumpf Maskin AB, who provided this pro-
ject and all related equipment. The question under research arose from customer requests as
well as by identifying market niches, who addressed this problem and the opportunity of sell-
ing such product, to Trumpf.
The project deals with the additive manufacturing (AM) process “Laser Metal Deposition”
(LMD), which can – among other application – be used to repair metal components. Worn or
damaged surface areas and missing or destroyed features can be additively re-manufactured.
This repairing option results ideally in a re-use of the component, which leads to an extension
of the Product’s Life Cycle (PLC), respectively the use-phase of it. With that also the re-
sources can be reduced, such as energy and material but also monetary assets. (Gao et al.,
2015, p. 79)
In most cases, however, the overall costs of repairing are component are higher than the costs
of a newly built part, due to the high costs of the repair process. It is a time-intense process
which requires high investments into machinery and auxiliaries, investment in knowledge-
building as well as a high demand of labour in several steps of the repairing phase (Zheng, Li,
& Chen, 2006, p. 1062). To lower the cost of applying the LMD to repair components, the
whole process chain of the repair needs to be examined to identify cost drivers and eliminate
them.
As a main driver for costs, especially in labour expensive countries in Europe, labour can be
identified among others in the forefront. That can be significantly reduced or even eliminated
by applying concepts of automation to the process. As a result, the part repair is cheaper and
can be applied profitable to other components.
It will further enable the digitalisation of the process over the full process chain, which opens
the way for Industry 4.0. By storing the measurement data, quality control can be applied
based on historical data and conclusions can be made by interpret the measurements.
As mentioned, the complete LMD repair process will be examined to identify improvement
areas in terms of lowering costs of application. However, this thesis will focus on the en-
hancement and automation of the measuring process. It evaluates the feasibility of applying
such an automated measuring process to the Trumpf TruLaser Cell 3000 Series.
This pursues the vision of an automated repair process in one single machine, where the entire
process of repair can be carried out on a component without any change of machine or loca-
tion nor knowing the area of repair. Starting from identifying the component and the worn
areas; choosing the strategy and parameters to repairing and carrying out the print on the
component in a fully automatic way.
Florian Säger
2
1.1 Aim of this Thesis
The aim of the thesis work is to find a solution which allows to measure parts in three-
dimensional space within the machine enclosure of the Trumpf TruLaser Cell 3000 Series.
Adding a partly or fully automated measuring device to the machine, the repair process using
Laser Metal Deposition (LMD) can be significantly simplified. That, in the context of the
process chain of repairing a part, will reduce the cost of application by reducing throughput
time, manual labour and investment in further measuring products.
Next to the reduced costs of application and simplification of the process, the automation en-
ables for example a one-piece flow, where each part can be unique in its’ repair requirements.
Additionally, another scan of the part in the post-process can be used to validate the repaired
area and increase the quality assurance by allowing to analyse the result.
With a fully automated repair process using LMD, Trumpf would inaugurate a unique selling
proposition (USP) to the market, since there is no similar product on the market today.
New customers can be reached which do not have other possibilities to measure a part in or-
der to define areas for repair.
Figure 1 shows the repair process in a flow diagram, where blue colour indicates steps which
mainly involve manual work and green mainly automated processes. The full process chain
and its analysis can be found in section 2.3 “The Repair Process using LMD”.
Figure 1 - The current and future LMD repair process in a simplified version. Showing the im-
provement aims, where blue colour represents process steps involving mainly manual work and
green colour representing automated process steps.
Florian Säger
3
Automation requires, to begin with a suitable measurement process which can be integrated
into the machine environment. To this direction a solution shall be researched and combined
with experimental work will contribute to ideally carrying out first trial measurements during
this thesis project.
Based on that evaluation, first achievements can be mentioned and more important: future
challenges can be identified and pointed out. This will overall clarify if such an application is
feasible to develop. Further, it identifies the amount of resources needed to develop the pro-
cess fully towards an automated solution at Trumpf.
It also demonstrates the ratio of the possibilities with the chosen measurement system or de-
vice.
Summing up, the aim of the project and thus a strategic goal of Trumpf, is to offer a “one-
machine” solution to its’ customers, with which a fully automated repair process can be car-
ried out to almost any metal component.
1.2 Motivation for Optimising the Measuring Process
It is known that the use of material and energy resources on earth needs to decrease to ensure
that the emissions of Greenhouse Gases (GHG), the main contributors to climate change, are
reduced significantly in order to cap global warming. One of many technologies in industry,
which seems to be a promising step towards decreasing these GHG, and the carbon footprint
could be Additive Manufacturing (AM). That, together with other advantages AM has over
classical machining processes, lead to an enormous trend in growth of this technology.
It is, however, controversially discussed if AM has the power to become the next industrial
revolution, since it could be a game changer for the whole industry on how to manufacture
components. Printed functional assemblies and whole products are possible to print directly
from digital data.
Some studies have already researched the potential of LMD to reduce the carbon footprint and
came up with the conclusion that the application of it to repair, can reduce the carbon foot-
print and the material used the whole PLC : Morrow, Qi, Kim, Mazumder, and Skerlos (2007,
p. 933) and Serres, Tidu, Sankare, and Hlawka (2011, p. 1123).
In addition to that, repairing of components is always a less resource intense process, since it
focuses just on damaged areas not on creating an entire new part. A greener manufacturing
environment could thus be enabled with this technology. (Liu et al., 2016, p. 1027)
Trumpf, does highly believe in the technology and AM and invests greatly into the develop-
ment. Besides other solutions offered, one application of the technology is the repairing of
metal components with Laser Metal Deposition. Where until today, the machine is mainly
used to print, the rest of the repair process chain (measuring, quality control…) is done in
other – external – machines.
As mentioned, the repair process is costly and time-intense as well as complex in terms of
expertise is required, all of which is explained in detail in section “2.3 - The Current Process
of Repairing Components using LMD By reducing the mentioned factors, and in particular
leading to decreased overall costs of the process, new customers can be acquired.
Florian Säger
4
Trumpf can create a USP to its customers by offering an automated repair process, which can
be executed on many metal parts without human interaction.
The cheaper repair could allow the application on cheaper components, where it was until
now not cost efficient to apply a repair with LMD, because a newly built part was cheaper and
less time intense to build.
These arguments, combined a process ready for Industry 4.0 where the process chain is fully
digitised, could win new customers and thus orders for Trumpf. While enabling a greener
production with reduced GHG and a lower carbon footprint each for each component repaired
and reused.
Florian Säger
5
1.3 Structure of the Thesis
Figure 2 shows the structure of the thesis in a process diagram. The main parts are namely:
introduction, theory, market survey & analysis and the validation are building the core of the
work. Followed by the result of the work where all findings will be summarised briefly and in
the next chapter discussed. In the “future work” paragraph, the results are being interpreted,
and found challenges are being pointed out. Hence, further work steps can be derived from
that, in order to perceive the magnitude of a future development project.
After introducing the project and its aim the whole process chain used to repair a component
with the LMD process is described as it is carried out from some of Trumpf customers. Based
on that, areas of improvement can be identified.
Based on these improvement areas, this thesis with its research questions can be derived. To-
gether with the scope of the thesis work is clearly defined within given boundaries.
Introduction
•Project introduction
•Goal definition
•Research Questions (RQ)
Theory
•State of the Technology
•Measureing Systems
Applied Methodo-
logy
•Sensor assessment
•Comparison
Validation •Experimental work
•Result of Validation
Future Work
Discussion
Result of Work
Figure 2 - Overview of the thesis structure in a flow diagram
Florian Säger
6
The introduction will be finished with a brief explanation of the company Trumpf and their
offered products. Followed by the theory regarding different available measuring and sensor
systems, which could be applied to the stated engineering problem in this thesis.
The following chapter “Methodology to Evaluate ” outlines the methodology which was used
to find the best suitable solution of sensor, which was then used together with the machine in
order to measure parts within the machine enclosure. Here also the evaluated
1.4 Research Question
The overall strategic goal of Trumpf is to develop a process, which decreases the labour hours
needed for process and likewise the human interaction with the process. This will result in a
more automated and thus, user-friendlier application and equally important it would also de-
crease the overall costs, as mentioned in the previous chapter.
The result: cheaper repair costs per component for the user, which will make the LMD and its
machine more appealing to customers to purchase from Trumpf, with this USP. Since,
Trumpf will be one of the first companies offering a “plug and play” (to a certain extend!)
solution, to repair metal parts using the LMD process.
However, until today it is not defined what are the specifications and needs to develop such a
solution, and accordingly, what challenges need to be faced.
Which is a reason why this thesis was set up: To research the feasibility of automating the
repair process. In this thesis in particular, focusing on the part of measuring compo-
nents within the machine enclosure.
The research question(‘s) (RQ) this thesis aims to answer are the following ones:
RQ 1: Is it feasible to integrate a sensor system into the enclosure of the Trumpf TruLaser
Cell 3000 Series machine, to measure metal parts fully automated and detect
worn/defect areas on them to use the machines’ LMD process to repair mentioned
areas?
From this, sub-questions arise:
RQ 1.1: What will be the best measuring system for this purpose?
RQ1.2: What are biggest challenges to face when developing this solution entirely?
These research question(s) will be answered during this thesis project and in the last chapter:
7 “Conclusion”.
Florian Säger
7
1.5 Scope and Definition of the Thesis
The scope of the project at Trumpf initially was to create a ready-to-use “product”, which is
capable to carry out a fully automated repair process, over the whole process chain. The rough
idea was, to attach a measuring sensor to the machine and with some changes to the machine-
and CAM software, repair components fully automated.
However, after formulating a first project draft and getting in contact with professors and ex-
perienced engineers, it became clear that the scope for this thesis has to be narrowed down
from these expectations.
Together with the KTH supervisor, Xiaoyu Zaho and in communication with the responsible
persons from Trumpf, it was agreed to focus on finding a sensor system which then sets
grounds for a complete process automation in a future development project.
Upon that, it was also agreed that a validation of the researched system will be carried out on
a Trumpf TruLaser Cell 3000, in order to prove that correct measurements can be derived
from the chosen system.
Based on both, the research for the best suitable sensor type and system and the executed val-
idation with the chosen system, recommendation for sensory type or system can be given and
future work packages can be suggested.
1.6 Goal of the Thesis
By lowering and reducing:
1) the overall costs of the process
replace (usually used) external measuring devices
2) the complexity of the process
abrogate the change of machines
adopt automatically to different components
simplify process (for end-user) to abrogate special knowledge
compare scan and original file automatically to identify worn areas
3) the time consumption of repairing overall
a) reduce of the throughput time
4) the manual work during the repair process
b) automate the process to best extend
The goal is to provide a sensor recommendation for Trumpf, which enables to measure parts
of different sizes in the machine area of the Trumpf TruLaser Cell 3000. Further, the “one
solution” shall be chosen and be validated towards the ability to create a point cloud of a
component. The point cloud shall have a resolution, high enough, to ensure that worn areas on
the component can be identified in a sufficient quality. This will be validated with tests and
the CAM software of Net-Vision called ADEM, where path generation for repair needs to be
successfully done.
1.7 The Company Trumpf
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Trumpf is a family-owned-and-operated company with the headquarters in Ditzingen near
Stuttgart in Germany. Besides the subsidiary Trumpf Maskin AB in Sweden, where this thesis
was carried out, it has more than 70 further subsidiaries in the whole world, to provide all
products, solution and services in close proximity to all their customers over the world. In
addition, Trumpf is one of the world’s biggest providers of machines tools, with production
facilities in Germany, China, France, Japan, Mexico, Switzerland and USA. (TRUMPF
2018b)
Trumpf is a high-tech company offering manufacturing solutions in seven different fields.
Below, these mentioned fields and their core products are listed. However, this is just an ex-
tract of the portfolio of Trumpf in total more variants of products and specialised solutions
are offered to customers all over the world. (TRUMPF 2018d):
Table 1 - Extract of the product portfolio of Trumpf (TRUMPF 2018d)
- Machines & Systems
- Laser cutting machines
- 3D laser cutting
- Laser welding machines
- Marking systems
- 3D printing systems
- Punching machines
- Bending machines
- Automation
- Lasers
- Disk laser
- Diode laser
- Fiber laser
- CO2 laser
- Scientific laser
- Power Electronics
- Power Tools
- Shear cutter
- Seem locker
- Drill driver
- Smart Factory
- Machine connections
- Optimization
- Software
- Specialised CAM software
- Monitoring applications
- Services
- Financial service
- Technical service
- Individual solution planning
- Energy Storage Systems
Figure 3 - Trumpf Logo. Source: (Trumpf Media Server 2018)
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- Induction Generators
Trumpf was founded in 1923, when Christian Trumpf together with two other persons ac-
quired a company called “Julius Geiger GmbH”, which was located in Stuttgart, Germany.
From that point onwards, the company evolved statically and has today as a yearly revenue of
3,11 billion € (2016/17) and 11.883 employees world-wide. (TRUMPF 2017) 1
Preliminary figures from a press release of 19.07.2018 even show an increase in sales to
3,6 billion € (2017/18), which is an increase by 15 % (TRUMPF 2018a).
Trumpf Maskin AB in Alingsås, Sweden is a subsidiary of Trumpf GmbH + Co. KG with its
headquarters in Ditzingen, Germany.
The main function of the subsidiary in Sweden is to offer products and solutions from the
Trumpf portfolio to customers in all the Nordic countries. Thus, Trumpf in Alingsås is re-
sponsible for the markets in Sweden, Denmark (here only for lasers products), Iceland and
Norway and Finland. Further the service business is offered to all its customers to ensure the
highest availability of all machines and the best maintenance possible.
1.7.1 The Additive Manufacturing Products from Trumpf
Besides the mentioned products (see section 1.7) that Trumpf offers, the portfolio includes
also products belonging to the category of additive manufacturing (AM)
Trumpf has – until today – two different machine types for AM in the portfolio:
1. Laser Metal Fusion (LMF)
This process uses a laser as energy source to melt metal powder in a bed, on desired
points. Layer by layer metal powder is added and melted to form the part according to
the CAD model.
The process belongs to the group of Powder Bed Fusion processes and is also referred
to as: Selective Laser Melting, Selective Laser Sintering, Direct Metal Laser Sintering.
The following picture illustrates the process.
1 Data form company report, as referenced, 16/17 with reporting date from 30. June 2017.
Figure 4 - LMF process, where the laser currently melts a metal powder layer. Source:
(Trumpf Media Server 2018)
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2. Laser Metal Deposition (LMD)
This process is among other applications, used to repair metal parts. It is further the
process which is used in this thesis project and will thus be explained in detail in the
following sub-section.
The process is also referred to as: Direct Laser Deposition, Direct Energy Deposition,
Laser Cladding
Figure 5 - The LMD process in action, here the nozzle can be seen during processing metal
powder onto a spinning metal disc. Source: (Trumpf Media Server 2018)
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2 Theory
In this chapter the fundamental principles for this thesis work are mentioned and explained.
The chapter is divided into four sections. The first part mentioned, and brief explained the
different additive manufacturing (AM) methods. In the second section, the theory for the La-
ser Metal Deposition (LMD) process itself is explained. The third section of this chapter ex-
plains the repair process of metal parts, using the LMD process as it is applied by Trumpf
customers. The last section focuses on measurement systems, here the applicable measuring
techniques for measuring components in the machine enclosure are enumerated and elaborat-
ed with their work principles.
2.1 Additive Manufacturing Processes
Additive Manufacturing Processes are being developed rapidly and thus new branding names
are developed in the same pace, to differentiate the own product from the competitors. Never-
theless, according to ASTM F2792 standard, all the AM processes unrelated to their marked
and branded name can be distinguished between seven categories or families. The American
Society for Testing and Materials (ASTM) shows so, in their standard “ASTM F2792. The
seven families and the short description to each, according to ASTMInternational (2015;
Standard Terminology for Additive Manufacturing Technologies) are listed below.
1) VAT Photopolymerization
A vat of liquid photopolymer resin is cured through selective exposure to light (via a
laser or projector) which then initiates polymerization and coverts to exposed areas to
a solid part.
2) Powder Bed Fusion (PBF)
Powdered materials are selectively consolidated by melting it together using a heat
source such as a laser or elector beam. The powder surrounding the consolidated part
acts as support material for overhanging features.
3) Binder Jetting
Liquid bonding agents are selectively applied onto thin layers of powdered material to
build up layer by layer. The binders include organic and inorganic materials. Metal or
ceramic powdered parts are typically fired in a furnace after they are printed.
4) Material Jetting
Droplets of material are deposited layer by layer to make parts. Common varieties in-
clude jetting a photocurable resin and curing it with UV light, as well as jetting ther-
mally molten materials that then solidify in ambient temperatures.
5) Sheet Lamination
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Sheets of material are stacked and laminated together to form an object. The lamina-
tion method can be adhesives chemical or similar. Unneeded regions are cut out layer
by layer and removed after the object is built.
6) Material Extrusion
Material is extruded trough a nozzle in tracks or beads, which are often combined into
multi-level layer models. Common varieties include heated thermoplastic extrusion,
similar to a hot glue gun.
7) Directed Energy Deposition (DED)
Powder or wire is fed into a melt pool which has been generated on the surface of the
part where it adheres to the underlying part of the layers by using an energy source
such as a laser or elector beam.
8) Hybrid Processes
For example, laser metal deposition is combined with CNC machining, which allows
additive manufacturing and subtractive machining to be performed in a single ma-
chine, so that parts can utilize the strength of both processes.
2.2 The Laser Metal Deposition (LMD) Process
Laser Metal Deposition (LMD) is an Additive Manufacturing (AM) technology, however just
one of many.
It belongs to the class of direct energy deposition AM technologies (Mahamood, 2018, p. 4).
As the name indicated the process uses laser as the energy source to melt the raw material,
which either is fed as powder (as used by Trumpf) or as a wire.
On the target the laser fuses the surface of the component and at the same time shots metal
powder into this melt pool. The powder particles are being melted as well as they reach the
melt pool. When the powder impinges onto the melt pool, the two materials (ground material
and powder) are permanently bonded together in a metallurgical way. As the laser passes, the
area solidifies again, since heat was just applied in a focused zone on the surface. The follow-
ing graph illustrates this in a schematic way. (Mahamood, 2018)
Figure 6 – The nozzle of the LMD while the process is in work. The laser melts the surface of
the target and adds powder into the melt pool. The process is shileded by shiled gas. Source:
(Petrat, Graf, Gumenyuk, & Rethmeier, 2016, p. 762)
Feed
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The illustration further indicates how the two process gases are used with LMD.
The shield or nozzle gas indicated in the picture in light blue is commonly argon. Its main
purpose is to shield the target, in particular the molten pool to prevent the area from oxidation.
The other, referred to as carrier gas (usually helium), is used to transport the powder from the
powder container to the nozzle and the target area. With a change of the flow rate [l/m] the
amount of powder transported from the container to the target can be adjusted. (TRUMPF
2018c, pp. 2-2)
The nozzle has a specific focus point, indicated by the (1) in Figure 7. Here, the powder from
the different outlets meets and intersects with the laser focus. It defines also the working dis-
tance to the target, so-called (D).
Technical specifications of the process, according to: (TRUMPF 2018c)
Nozzles available:
o Three-beam nozzle (usually: 3D processing) used for coating with different
specifications available:
Powder focus diameter 2,5 – 4,0 mm
Target distance approx.: 12 – 16 mm
o Coaxial nozzle (usually: 2D processing) with specification ranges:
Powder focus diameter: 1 mm
Target distance approx.: 7 mm
Feed
The feed can basically be freely chosen and defines the thickness of the process. Less
feed will add more material to a certain point and thus result in a thinner layer of ma-
terial added and vis versa. It is however limited to the physical boundaries, where the
powder will leave the focus due to the indolence of the metal powder.
Figure 7 – A macro caption of the nozzle with active powder feed. (1) indicates the intersec-
tion of the powder outlets and the focus of the laser beam. This also defines the working dis-
tance to the target (D). Source: (TRUMPF 2018c)
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Materials
Almost any metal, in form of powder can be processed. Alloys and a mix of different
metal powders in the head are possible as well.
Gas used in the process
Carrier gas is commonly helium
Nozzle gas (also known as shield gas), commonly argon
The nozzle that Trumpf uses can be seen in Figure 8. It is indicated in golden/bronze colour,
the mechanics above are the laser optics.
The basic principle of the process is thus very similar – and also related – to the welding pro-
cess. Which is also why this technology can be called "Laser Cladding". Other names are:
"Direct Energy Deposition". (ASTM International (Standard F2792-12a) 2015)
Depending on the application purpose and the material which will be manufactured, Trumpf
offers a variety of laser sources (disk laser, CO2 laser, fiber laser,…) to its customers, special-
ly customized to the specific requests.
The machine tool used for this thesis project is the Trumpf TruLaser Cell 3000. It is a univer-
sal 3D multi-machine tool from Trumpf with which laser cutting and welding can be per-
formed as well as the mentioned Laser Metal Deposition process can be executed. The ma-
chine can be seen in Figure 9. To do so, some peripheries needs to be added to the machine
environment, such as the metal powder feeder (also called powder conveyor) and the process
nozzle for the LMD, available in a coaxial or three-beam variant. The details of the LMD pro-
cess however will be explained in sub-section 2.3 “The Repair Process using LMD”.
Figure 8 - The LMD nozzle Trumpf uses in golden/bronze colour. The mechanics seen above
are the optics for the laser focus and process surveience. Source: (TRUMPF 2018c)
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The LMD process can be ordered from Trumpf with the "TruLaser Cell 3000" and "TruLaser
Cell 7000" and also with the robot-based "TruLaser Weld" system. Further, a so-called OEM
package can be ordered from Trumpf, which makes it possible to add the LMD externalities
to other laser-based machines, to perform LMD. The package includes the powder feeder unit
and the nozzle head.
2.2.1 Main Application Fields of LMD
The LMD technology has several application fields, from which four main categories can be
identified:
1. Repairing
Mainly expensive parts where wear, changes or defects occur. Further many custom-
ers use the TruLaser Cell 3000 and 7000 to coat surfaces. The repair function of the
LMD is used for expensive part for the bare fact that the process itself is costly due to
two factors.
First, the machine is a high-end precision machine due to precise measuring internals
Further, the process for repair involves a lot of pre- and post-processing for compo-
nents. Here comes the critical part in: This involves a lot of manual work which makes
the process expensive for users. Especially in high-salary countries like Sweden.
The entire process of repairing is shown and explained in sub-section 2.3.1.
Figure 9 - The Trumpf TruLaser Cell 3000 Series. Source: (Trumpf Media Server 2018)
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2. Coating
The coating of surfaces or parts of a component is another common application. Espe-
cially when special requirements are needed, such as hardness, heat resistance or pure
aesthetic needs this can be a good solution.
3. Joining and local material adding
Where complex and thin parts with gaps need to be welded together this process can
be applied. With its precision and the readability, the process can in combination with
an automated feeding also be added into a serial production
4. Part generation
It can also be used for part generation in general, where the whole component is creat-
ed. Here the commonly referred layer manufacturing applies, where the part is created
by 2D layer "printing" and the third dimension is added by moving stepwise in Z-
direction upwards.
2.3 The Repair Process using LMD
The repair process, using the LMD, can be described in the same way the LMD is used for
creating parts. The difference is the specific purpose of its use and the area where material is
added, which is limited to worn or destroyed areas of a component. Correspondingly, this
means that the printing is executed on the component itself and not a usually used base plate.
The process during execution is illustrated in Figure 10.
Figure 10 - LMD process while working, done on a shaft (used as base material) to create a
helix. Further in golden colour the nozzle can be seen. Source: (Trumpf Media Server 2018)
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In the following two sub-sections the repair process is explained in more in detail. First the
process is explained as it is applied at Trumpf customers today. The second sub-section, start-
ing on page 20, is dedicated to the future repair process. Here the future process is explained
as it shall be developed. It includes the preferences of customers and the expertise of several
Trumpf engineers.
2.3.1 The Current Process of Repairing Components using LMD
In this sub-section the repair process is explained, as customers of Trumpf are using them
today to repair parts. This is also how Trumpf executes the process according to internal doc-
uments.
Since this thesis requires a holistic view on the process to ensure an integrated solution devel-
opment, detailed data related to process parameters or setup parameters are not mentioned.
Initiating the LMD process, a quick overview
Three important LMD process parameters, which vary according to used materials and appli-
cation use, are:
1. feed (machine head) [Millimetres/Minute],
2. laser energy [Watts] and
3. feed rate (powder supply)
Depending on the feeder: [% of max. amplitude] or [revolutions/minute].
Until today, there is no table of parameters available were process parameters can be looked
up according to used material, feed etc. Consequently, most of the machining parameters de-
pend on the experience of the user and are researched together with the customer for each
application. Trumpf and its sub-suppliers are currently working on creating such a process
parameter table, to overcome this boundary for the customers and users.
When the mentioned process parameters and all other necessary parameters are set, the nozzle
is placed near the ventilation flue, behind the working area, on the bottom of the machine, so
that the powder flow can be filtered after exiting the nozzle.
The pre-flow of metal powder is done to ensure a continues and stable supply of powder. Due
to a very varying powder supply at the first few seconds, due to powder still in the pipes when
the carrier gas was shut off after the last use. The run-up for this takes about 10-30 seconds.
The nozzle is then (powder supply still active) moved to the target area on the components
surface. Then the desired program can be stared, which will start the shielding gas supply and
the laser as well as the motion controller, each as programmed. During the process the nozzle
is placed and moved approx. 7-25 mm above the target surface, which will provide a good
powder focus intersection with the focus of the laser.
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The process steps of repairing with LMD
In the following table the LMD repair process is shown in a stepwise order. It represents the
process as it was expressed to the writer from Trumpf. The users of the process are several
customers using the LMD to repair parts, which want to stay anonymous.
In the left column of Table 2, the steps can be seen as they are carried out in a sequence. In
some cases, different attempts are possible, which then is shown in the right column in the
alternative steps, with the respective alternative process step number.
The working steps which involve manual work or partly manual work, are marked in blue
colour in the table 2.
Table 2 - Detailed Process Steps of the process step as carried out at some Trumpf customers
(Source: In a less detailed version, form a customer of Trumpf in Sweden, which wants to
stay anonymous)
Process Steps Alternative Process Step
1. Place component onto measuring ta-
ble
a. Secure component
2. Execute measuring
a. Find measuring program
b. Execute measuring program
automatic or manual
3. Create 3D-point cloud
a. Stitching of a 3D point cloud
out of several scans
b. Feasible export format needs
to be found
4. Generate surface model
a. Generate a meshed surface
model
5. Import files
a. Find original CAD file from
component
b. Load both: scanned model
and original CAD model
6. Extract delta
a. Locate worn areas/missing
features
7. Set printing strategy
a. Slice delta areas for print
b. Find print method (circle,
zigzag,...)
2. Execute measuring
a. Create measuring program
b. Validate measuring program
c. Execute measuring program
automatic or manual
3. Create 3D point cloud
a. Point need to be exported in-
to CAD/CAM
b. Point cloud need to be
stitched together from several
measuring turns to a con-
sistent 3D cloud manually
4. Generate surface model
a. Generate re-engineered sur-
face model
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c. Set parameters for print
8. Prepare part on LMD machine
a. Move part to LMD machine
b. Secure part on part-holder
c. Find reference point to print
defined areas
9. Prepare print
a. Load print
b. Check program on dry run
manually to avoid e.g. colli-
sions
10. Execute print
a. Print missing features
11. Post print
a. Check success of print
b. Move part to post machining
12. Post machining
a. Part needs to be checked for
machining needs
b. Machining needs to be pro-
grammed/adopted
c. Manual measuring to locate
machining necessary items
d. Execute post-machining
As one can observe, it can be read in the table and it was also briefly mentioned in the intro-
duction part, a lot of manual work is involved in the repair process today.
Given these points, this resolves in a high amount of labour hours and accordingly in a high
amount of costs. This increases extra, when special knowledge is necessary like it is when a
special trained person is needed for measuring of parts or carrying out a manual programming
of the process. Additionally, if the process is carried out in high-labour cost countries in Eu-
rope the costs increase further as well.
The fact that the process demands time and labour is broadly known and researchers, like
Wimpenny (2012, p. 821) , Candel, Amigó, Ramos, and Busquets (2013, p. 10) or Boehm
(2016, p. 45). Nevertheless, it needs to be analysed with regards to specific needs when ap-
plied to the Trumpf TruLaser Cell 3000 Series.
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2.3.2 The Future Process of Repairing
In contradiction to the previous sub-section, the focus in this part is to describe the ideal fu-
ture process from today’s view on the application.
The general aim – as described in section 1.1 – is, to reduce:
1) the overall costs,
2) the throughput time of the repair,
3) the human labour needed for executing the process and
4) the complexity of applying the process
on worn or damaged components, for the end-user.
As it was demonstrated in the previous sub-section 2.3.1, the current repair process is notably
labour intense. This is mainly because, several machines are needed to repair a component.
The components need to be moved thru the different machines during the process. Namely a
CMM can be mentioned here, where the part is moved for measuring and quality control.
As a result, that makes the process– above all – cost intense and economically applicable just
for expensive components. Especially in labour intense countries like Sweden and Germany
the costs are a big aspect to consider when the process is labour intense.
Thus, as a first step and as one solution, to reduce the mentioned factors the measurement
process can be optimised labour hours and at the same time reduce investment costs, the
measurement process shall be optimized.
As one possible solution the measurement system shall be integrated into the machine envi-
ronment, to enable a measuring of a worn component without moving the component. Further
by replacing e.g. a CMM machine with alternative measurement system, the measuring pro-
cess can be made significantly faster, cheaper and can be automated.
Henceforth, the first step is to find soultions to meet these demands of an integrated
measuring system. A suitable solution, shall be researched, analysed and if possible suggested
for application in this thesis. This will open new possibilities of the process towards Industry
4.0 and digitalisation of the full processes chain.
Possible future aims to be realised
In future the machine shall also be include into the Industry 4.0 environments and use these
standards. Hence an automatic recognition of the insert component could be developed. This
could enable repairing, without any interaction. The machine could access a database of the
companies’ CAD files, where a match can be performed measurement. It will to perform a
target/actual comparison and thus define worn areas fully automatically.
Additionally, less part handling between different machines shall reduce the overall needed
interaction with human which results in reduced overall costs. Consequently, loading and un-
loading could be done with a robot.
Similar future development matters are being discussed in chapter 6 “Identification of Future
Work Packages based on ”
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Similar implemented ideas available in industry:
During the research phase of this thesis, to shape the state-of-the-technology part, three simi-
lar solutions or attempts to solve a very similar problem were found.
1. A solution from Zhang, Li, Cui, and Liou (2018), where a structure light scanner was
used to measure turbine blades in order to detect worn areas on the blade. However,
the focus here is on the measuring itself and on how to improve the measured data.
2. A solution from Wimpenny (2012) where the general process was analysed, and the
same conclusions were pointed out as in this paper. Measurement was however still
carried out in a CMM externally to the print process
3. A solution from Zheng et al. (2006) where the measurement process also was pointed
out as a labour intense process. Alternative methods were presented and elaborated of
their applicability. The paper done in 2006 however indicated that the solutions avail-
able back then were not able to offer the same possibilities in terms of accuracy etc.
4. Last mentioned solution is from the company (Lunovu 2018)
which presents a very similar approach to the one Trumpf will de-
velop, however no detailed specification could be accessed or pub-
lications were found. A YouTube link was found after deeper re-
search which shows the setup and execution of the process:
https://www.youtube.com/watch?v=1u_oDjcrlXA&vl=en
QR-code– Link to the
YouTube Video
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2.4 Sensor Systems for Surface Measurement
In this chapter the different possible sensors and sensor systems, which can be applied to
measure components in the machine working area, are introduced and their working principle
is described briefly.
The process of measuring a component and feedback that data into a computer usable format,
is referred to as reverse engineer.
Reverse engineering usually follows the steps of gathering data, filtering data, computing a
near-shape model and combining with further input like colour appearance or texture of the
surface.
The data collection of a surface shape and dimension can be done by the use of several differ-
ent techniques, a taxonomy can be seen in Figure 11. After filtering the data, the near-shape
model is usually computed as a triangulated or meshed model out of a point-cloud. (Bagci,
2009, p. 408)
The process of collects and produces data from the real object is commonly referred to as
scanning Depending on the used system this can be done automatically or semi-automatic. In
some cases, the component has to be moved or manipulated in a dedicated direction, in others
the scanning system itself has to be moved. (Bellocchio et al., 2013, p. 6)
If neither can be done, e.g. to scan objects bigger then the “view” of the system, in most cases
several scans have to be carried out. These scans then can be added in one combined scan in a
dedicated software in the post-process or sometimes even done by the sensor post-processing
itself.
In chapter 4 will then be analysed which of the sensor might be the best solution for the pur-
pose.
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The process of digitalising a real-world component can be done in several ways, they can be
categorised for example in the way, Bellocchio et al. (2013, p. 21) suggested in his taxonomy:
For the purpose of this project, not all in Figure 11 mentioned measuring principles are appli-
cable. For a 3D surface scan in particular, even less are applicable. In the following part, fea-
sible solutions are mentioned, and their working principle is briefly explained:
Contact
Destructive Slicing
Non-destructive
CMM
Non-contatct
Tras-missive
Computer Tomography
Reflective
Optical
Sonar
Mircowave Radar
Optical
Passive
Shape from Silhouettes
Shape from Defocus
Active
Time of Flight
Active Triangulation
Photometric Stereo
Inter-ferometry
Figure 11 – Taxonomy of measuring principles ordered according to their physical technique
used. Own graphic, based on (Bellocchio, Borghese, Ferrari, & Piuri, 2013, p. 21)
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The following list is acquired with information from Corner, D' Apuzzo, Li, and Tocheri
(2006), Chen, Brown, and Song (1999) and Zhang et al. (2018)
1. Coordinate-Measuring Machine CMM
a. Touch Trigger Probe
A probe is attached to a NC-driven machine head and with moved towards the
part, as soon as the probe gets in contact with the surface it triggers the meas-
urement and writes the current position into the measuring log.
b. Scanning Probe
A probe, usually spherical is continuously moved along the surface and in set
time spans writes the current position in a log.
2. Time of Flight
a. Laser Point
The laser point sensor creates a laser light, which is sent out of the sensors in
pulses. When getting in contact with reflective material it will reflect towards
the sensor and the time between sending the laser pulse and receiving it back
allows to recalculate the distance from the sensor to the reflected material.
3. Active Triangulation
a. Laser Line
The laser line sensor sends laser light in a line towards the pointed surface,
when reaching a reflective object, the light is reflected back to the sensor. In a
defined distance from the laser source a diode detects the reflected light and
with the principle of triangulation the distance from the reflected surface to the
sensor is acquired.
b. Coded Light Projection
This technology works with light or code patterns which are projected on the
surface, usually in several different patterns in sequences. The pattern is cap-
tured by one or more cameras and with triangulation, as explained before,
measured. With this system bigger areas with several million points can be
measured in several seconds.
Other solutions like radar sensors or inductive sensors where not considered in this thesis,
since the application would be too difficult due to boundaries of these technologies and fur-
ther due to restrictions the machine environment gives to the application of such sensors.
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Reverse Engineering
Reverse engineering is the process, where a real-world object, or in this case a metal compo-
nent, is copied into a digital world, for example into a Computer-aided design (CAD) soft-
ware. There it can be used for further processing or in turn to shape a real-world object again,
with machining for example. (Romero-Carrillo, Lopez-Alba, Dorado, & Diaz-Garrido, 2012,
p. 91)
Since all real objects are measured in three dimensions (3D), this has to be done in reverse
engineering for most of the applications as well.
Thus, 3D Scanning is the process of capturing a real-world object and by generalising, acquire
its shape into a digital model, which shall represent the real object. The device or system used
to do so is called a 3D scanner. (Bellocchio et al., 2013, p. 8)
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3 Methodology to Evaluate Feasible Measuring Solutions
The scientific methodology used to assess all sensors or sensor systems in this thesis is de-
scribed briefly below.
The assessing is necessary, since from a system perspective, different kinds of techniques can
be applied to measure a surface of a component. However, due to restrictions (e.g. the overall
allowed size of the measuring system), the “best solution” has to be researched which then
can be tested and if necessary, changed. The following graph shows the PDCA-cycle for that
continues improvement process, to ensure the right sensor used within the system.
The methodology is split into two parts:
1) Qualitative rating of measuring technologies, to measure and reverse engineer a sur-
face
2) Quantitative rating of sensors, which are applicable for the specific needs of the ap-
plication and to the boundaries given by the machine
To ensure finding the best solution, first all different technologies to measure a surface are
presented in section 2.4, followed by a quick assessment of which technologies seem feasible
to apply to the needs of this project. Additionally, the left-over sensors are being evaluated
more in detail with a rating scheme. Likewise, this ensures a transparent and traceable evalua-
tion of solutions.
It also guarantees, that changes in the application or in the specification sheet for the sensor
can be implemented in the presented evaluation table in chapter Fel! Hittar inte referens-
Plan: Implementing the
right sensor, which fulfills all specifications!
Do: Researching on
solutions possible. Assess
solutions towards "best fit".
Check: Are all
specifications fullfiled? Will
sensor also fit all other (forseeable)
purposes?
Act: Implement
changes to new specifications.
Change specifiactions if attributes failed.
Figure 12 - PDCA (Plan-Do-Check-Act)-Cycle for Sensor Assessment
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källa. on page Fel! Bokmärket är inte definierat., to find the best solution fitting to the new
needs.
The following graph illustrates the methodology, how the best of solutions of measuring sys-
tem is determined.
This methodology applied, ensures that the chosen solution is not just valid from a monetary
viewpoint, it is valid from a variety of perspectives, which will empower a broader view on
each reviewed solution. Additional to that, it enables an integral developed solution.
1 -
2 -
3 -
All available
solutions
Filter out solutions which
do not fit to the need
(Qualitative research)
Determine best
solution, thru as-
sessing. (Quantita-
tive research)
Figure 13 – A graphical representation of the methodology applied, to assess the best measur-
ing system.
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3.1 Qualitative Assessment of the Measuring Solutions
In this section reason will be given why some measuring solutions might be better and others
are less appropriate to be applied to the machine, to form a suitable solution.
1. Coordinate-Measruing Machine (CMM)
a. Touch Trigger Probe
Can easily fit into the machine environment, also the Trumpf TruLaser Cell 3000
would be applicable for this solution. A back draw is, that the accuracy is quite limited
to the probe head size.
b. Scanning Probe
The acquired data is very precise, however – as mentioned previously – limited in ac-
curacy. It can easily be integrated into a machine like the TruLaser Cell 3000, where it
can use the internal NC-drive systems to read its current position.
2. Time of Flight
a. Laser Point
This method is very accurate and simple to apply to the machine environment. Here
also the NC-drive of the machine would be used to log the current position of the la-
ser point and with adding the distance measured by the sensor, the position of the
surface in relation to the machine origin can be calculated.
However, the measuring in a sufficient resolution over the whole surface of a part
will be time consuming, since point by point a measurement has to be made. Further
shiny surfaces can lead to measuring errors, due to deflection of the light.
3. Active Triangulation
a. Laser Line
An accurate solution, which could be attached to the machine without much effort.
The principle of how this sensor measures 3D, is similar to the mentioned laser
point sensor. The internal NC-controller would be used to calculate the surface po-
sition in relation to the machine origin. A back draw could be given when surfaces
are very shiny and deflect the light in to many directions, which resolves in meas-
uring errors.
b. Coded Light Projection
The coded light sensors have a really big advantage against the other techniques:
They cover a large 2D area at once and thus get results in few seconds for big
parts. On the other hand, the systems are usually rather big and sensitive to their
environment in terms of heat, splashes and dust. Which makes them usually hard
to integrate into the process flow of machining methods.
In conclusion thus, the techniques of laser line and coded light are considered more feasible
for the project’s purpose. In the following chapter it will be continued to research with this
measuring technologies.
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3.2 Quantitative Evaluating of the Measuring Solutions
For the assessment, a process needs to be introduced which allows to quantify each solution
on a given ordinal scale. Only then a comparison based on differences will be allowed.
Sensors were researched and then assessed with the following 8 features:
1. Size (Volume)
2. Cost
3. Accuracy
4. Repeatability
5. Scan speed
6. Rigidity of the system
7. Possibility for similar application use
8. Integration feasibility
The following table shows all factors which are being used to evaluate the best solution to be
applied to the Trumpf TruLaser Cell 3000 Series in order to measure parts in its enclosure.
The rating scale is from “0” = unknown specification (which will not be shown in the table)
till “10” = excellent fulfilment of the specifications.
After the table each factor is explained in detail and reasons for the range are presented.
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Table 3 - Rating and the respective justifications for each factor, to compare possible solu-
tions
Factor Rating Justification
1) Size (Volume) 1 > 720
(ex.: 12,0 * 12,0 * 5,0 cm)
in cm3 2 - 5 720 – 591
6 - 9 590 – 128
10
< 128
(ex.: 8,0 * 8,0 * 2,0 cm)
2) Cost 1 > 250.000
in SEK 2 - 5 250.000 – 150.001
6 - 9 150.000 – 50.000
Sensor only 10 < 50.000
3) Accuracy 1 > 20
in M 2 - 5 20 – 13
6 - 9 12 – 6
Max. possible of system 10 < 6
4) Repeatability 1 > 1,6
in M 2 - 5 1,6 – 1,1
6 - 9 1,0 – 0,5
10 < 0,5
5) Scan speed 1 - 3 > 60
in sec. 4 - 6 60 – 20
Time to measure a are of
100cm2 (10 * 10 cm)
7 - 9 < 20
6) Rigidity of the system 1 - 3 Very delicate system whose environ-
ment must be controlled
IP X Classifications2 4 - 6
IP X classification, however, to some
extend careful handling necessary
7 - 9
IP X classifications and shock ap-
proved as well as housing available
7) Possibility for similar ap-
plication use 1 - 3 Not feasible at all – maybe possible
4 – 6 Possible with some extend
7 - 9 Possible – Some Exceptions
8) Integration feasibility 1 - 3 The implementation into the current
repair process seems complex
4 - 6
The integration is possible with some
changes to the process
2 IP X codes derive from the standardisation publication of the European CEN: EN 60529. Which rates and clas-
sifies an electrical enclosure to the degree of protection against intrusion of particles from the environment.
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7 - 9 Integration is fairly simple
The factors in detail used in the rating
In the following the all factors from
After the table each factor is explained in detail and reasons for the range are presented.
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Table 3 are presented and a reasoning is given for each:
1) Size (Volume)
The size of the measuring system, in particular the sensor is a crucial part since it will
limit the working space of the machine and could lead to restrictions of the freedom of
movement of the machine. Consequently, the sensor itself, has to be as small as possi-
ble. The whole system, if outside of the machine can however be bigger and is not
considered in the rating.
2) Cost
The costs always need to be considered in business decisions, which is why it needs to
be included as a factor. However, costs should be looked at in a relation to the related
output.
3) Accuracy
Accuracy plays a crucial role for the application of the sensor, since it is the technical
specification which gives an answer to the detail which worn areas on the surface can
be detected.
Further, if the rule of thumb for the accuracy is applied, backwards, the nozzles’ min-
imal processing size gives explanation to the necessary figures.
The nozzle of the LMD process, as explained in chapter 2.2, has a maximal accuracy
of less than 1 mm in diameter.
4) Repeatability
This is in particular important for the quality of a series of measurements, the higher
the rating, the closer the results are to each other. Which would resolve in a steady and
stable process is given.
5) Scan speed
Gives answer on how fast a whole component can be scanned. This factor will have
direct influence on the throughput time, the faster the part can be scanned, the less
downtime has the additive machining.
6) Rigidity of the system
Gives explanation on how sensitive the system is to external factors like dust, splashes
and heat. The system can have IPX standards applied which gives detailed information
about the resistance against such factors.
7) Possibility for similar application use
Represents an indication on how open the system is towards other application. Is the
system dedicated for one use only, it will be hard to come up with new ideas on how
to further develop the application. This does not mean use in another context, but re-
fers to use in the same context with other focus.
8) Integration feasibility
Facilitates the need of integrating the process directly into the work flow without inter-
rupting it, for example: to initiate the system, load data or similar. The easier the sen-
sor can be used without pre-work and with software etc. provided, the better for the
project.
The rating procedure
Each of the eight mentioned factor is rated for each presented solution, according to their
technical specifications. The rating scale is from:
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“0” = unknown specification, over
“1” = insufficient, till
“10” = excellent
and is justified with a minimum specification a solution has to have, to get rated accordingly.
If the specification is in-between two numbers, due to the specifications in-between two rat-
ings, the nearest difference will decide on the rating.
If, however, no difference can be defined due to e.g. a nominal scale to choose from, a clarifi-
cation for the decision will be stated with the rating, below the rating table.
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4 Analysis of Most Suitable Measuring Solutions for the
Application
To find a sensor system which fulfils all demands described in “1.6 Goal of the ” a rating-
scale was introduced. This generates a decision-making process, traceable for the reader. Fur-
ther it opens the possibility to study and research further possible solutions and compare them
in a quantified way, which – again – makes it a traceable and thus transparent process for the
reader.
All three, in the following presented solutions were reviewed for their’ technical specification
from their’ data specification sheet, which can be found in the appendix, as mentioned to each
solution.
4.1 Possible Solution 1: Laser Line Sensor from Micro-Epsilon “LLT
2900-100”
The Sensor from Micro-Epsilon “LLT 2900-100” is rated according to the previous men-
tioned factors.
The rating itself and the elaboration for it, is commented in the following table. If further
elaborated is necessary for a factor, it is stated in the row and further described below the ta-
ble.
The data specification sheet of the sensor which was used to fill the rating, can be found in the
appendix at the end of the document: Appendix I and Appendix II.
The following table shows the rating of the sensor with the factors, mentioned in the previous
section of this chapter.
Figure 14 - Micro-Epsilon laser line sensor. Source: (Micro Epsilon - Datasheet 2018, p. 3)
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Table 4 - Rating of Solution 1: Laser Line Sensor “LLT 2900-100” from Micro-Epsilon
Reason for the rating of 4)
No data is given for that factor, however with some testing this could be defined for the sen-
sor system.
Reason for the rating of 5):
The sensor covers at the standard measuring distance of 240 mm (z-axis/distance) a range/line
of 100 mm (x-axis). Consequently, the point distance in x-direction is:
1
1280 𝑃𝑡𝑠.100 𝑚𝑚⁄
= 0,078 𝑚𝑚 = 78 m (1)
With the maximal profile frequency of 300 Hz. and in order to get the same point distance in
y-direction, the feed can be as high as:
0,078 𝑚𝑚 ∗ 300 1
𝑠𝑒𝑐.= 23,4 𝑚𝑚/𝑠𝑒𝑐.
(2)
3 The price according to the trial quotation, which was offered later during the project.
FACTOR RATING REASON / SPECIFICATION
1) SIZE 8 9,6 * 8,5 * 3,3 cm = 269,28 cm3
2) COST 9 Approx. 60.000 SEK3
3) ACCURACY 6 12 m
4) REPEAD-
ABIITY 0 Unknown
5) SCAN SPEED 10 Scan finished after approx. 4,3 sec.
6) RIGIDITY OF
THE SYSTEM 9
Sensor is IP65 certified. Further a durable metal housing
with active cooling is available for the sensor.
7) OPEN FOR
SIMILAR AP-
PLICATION
7 (Further elaboration below)
8) FEASABIL
PROCESS IN-
TEGRATION
7 (Further elaboration below)
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36
To cover the whole component, the sensor needs to be moved 100 mm, in y-direction, along
the part, which result the scan is executed in 4,3 sec.
Reason for the rating of 6):
The sensor has a high IPX classification and on top can be ordered in a safety housing with
active cooling and changeable sensor glass protectors, which added to extra good rating.
Reason for the rating of 7):
The sensor has always to be moved along the surface of the object which is measured. Which
makes the measurement easy if it is a rather simple part with a shape rather being flat. The
same method can be executed as well, if the part has no more than 100 mm of delta between
highest and lowest point to be measured in z-axis. As a result of the standard measuring range
of the sensor starting at 190 mm till 290 mm, each measured from the exit of the laser head.
If, however, these measures are exceeded, or the part has undercuts, hidden from the top view,
the sensor needs to be moved in another axis as well.
This makes the measuring process then far more complicated, since either: The measuring
needs either to be split in several parts and then in a post-process stitched together.
Or: the measuring can be done with a simultaneous axis movement. That means a recalcula-
tion of the sensor movement (in real time) and the distance measuring of the sensor is needed,
to enable an in-line 3D measurement.
Reason for the rating of 8):
The general measuring principle (how this sensor can be used to measure components, can be
seen in the section 5.2 in detail) can be applied fairly simple with the given software, however
a process integration can be done as well. The manufacture of the sensor provides software
development kits (SDK) to integrate the sensor directly in its own software, e.g. the used
CAM software of Trumpf.
Despite the mentioned measuring of simple components in 7) the measuring process gets way
more difficult when the sensor is not just moved along one axis with constant distance to the
object. Here some own development is needed in order to enable more difficult components
to be measured.
As one of the export formats *.stl-file is available, which makes a integration into the CAM
software ADEM easy.
The rating is graphically presented in Figure 15, which allows for an easier comparison of the
different solutions, when all solutions are overlaid in one chart at the end of this chapter.
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Figure 15 - Radar Chart for solution 1: The result of the Micro-Epsilon laser line sensor
shown in a graphical way, for all eight rated factors.
8
9
6
0
10
9
7
7
0
1
2
3
4
5
6
7
8
9
10
1)
2)
3)
4)
5)
6)
7)
8)
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4.2 Possible Solution 2: Laser Line Sensor from LMI Technologies
“Gocator 2440”
The Sensor from LMI Technologies called “Gocator 2440” is rated in this section, according
to the previous mentioned factors as well.
The rating itself and the elaboration for it, is commented in the following table. If elaborated
is necessary for a factor, it is stated in the row and further described below the table.
The data specification sheet, which was used to rate the sensor, can be found in the appendix
sections of this thesis: Appendix III.
Figure 16 - LMI Gocator 2440 laser line sensor. Source: (LMI Gocator Technical
Specification 2018, p. 1)
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Table 5 - Rating of Solution 2: Laser Line Sensor "Gocator 2440" from LMI Technologies
Reason for the rating of 2)
Unfortunately, there was no quote sent during the thesis time from LMI Technologies. Thus,
no costs can be stated from a reliable source.
Reason for the rating of 5)
See 4.1, where a sample calculation was carried out and applied the same way. Data used for
calculation: 1500 Pts./Profile; 100 mm (x-axis coverage); 5000 Hz. Profile-frequency;
100 mm travel in y-direction. Which results in theoretical time for measuring of 0,3 sec.
This result of however seems to be not achievable, since with a feed that high, chatter would
be created during the movement which could lead to false measurement result. However, it
speaks for the sensor’s capabilities.
Reason for the rating of 7)
The LMI laser line sensor works with the same measuring principle as the Micro-Epsilon sen-
sor. This will lead to the same conclusion and thus rating as the Micro-Epsilon sensor.
FACTOR RATING REASON / SPECIFICATION
1) SIZE 1 19,0 * 9,0 * 4,4 cm = 752,4 cm3
2) COST 0 unknown
3) ACCURACY 5 13 m
4) REPEAD-
ABIITY 4 1,2 m
5) SCAN SPEED 10 Scan finished after approx. 0,3 sec.
6) RIGIDITY OF
THE SYSTEM 8
The sensor has IP67 certification and is gasketed in an
aluminium enclosure.
7) OPEN FOR
SIMILAR AP-
PLICATION
7 (Further elaboration below)
8) FEASABIL
PROCESS IN-
TEGRATION
7 (Further elaboration below)
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Reason for the rating of 8)
Similar reasoning as with solution 4.1. Since both solutions are laser line triangulation solu-
tions. Moreover the, LMI sensor has also an SDK available which allows the integration of
the sensor within the Trumpf machine environment, thus also the same rating as the previous
sensor in this factor.
Further the files can also be exported in *.stl-format, which makes a integration into the CAM
software ADEM easy.
The rating of this solution is graphically presented in a radar chart below, which allows for an
easier comparison of the different solutions.
1
05
4
10
8
7
7
0
1
2
3
4
5
6
7
8
9
10
1)
2)
3)
4)
5)
6)
7)
8)
Figure 17 - Radar Chart for solution 2: The result of the LMI laser line sensor shown in a
graphical way, for all eight rated factors.
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4.3 Possible Solution 3: Stereo Camera from GOM “ATOS Core 200”
The GOM system, GOM ATOS Core 200, works with the same principle but different tech-
nique, compared to the previous rated solutions. It used light patterns, projected to the surface
and two cameras (a so-called stereo camera setup) to calculate up to 12 million points within
1-2 seconds using the triangulation principle. With that larger surfaces can be digitalised with-
in seconds and with the included software automated comparison to the original file can be
executed.
In the following picture, the measurement solution can be seen.
In the table below, the system is rated as seen in the previous sub-sections. The data used, can
again be seen in the appendix section: Appendix IV.
Figure 18 - GOM ATOS Core 200 sensor mounted on a tripod, with illustrated components
being measured on the left side. Source: (GOM ATOS Core Homepage 2018)
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Table 6 - Rating of Solution 3: Stereo Camera "ATOS Core 200" from GOM
Reason for the rating of 2)
The costs are related to the same system purchased by another department at KTH, as the
specification sheet indicates. Regardless, it has to be noted that this price is a special price for
universities.
Reason for the rating of 5)
No specific specification is given in the data sheet; thus, an estimation was used for this factor
rating. The measuring area is 200 mm * 100 mm in size, which means the scan of the theoret-
ical probe can be done without moving the system. Additionally, from videos of the system it
can be seen that several patterns are projected on the surface to measure. That takes approx.
1,5 second.
Reason for the rating of 7)
Together with the sensor, the system comes with a software package which allows offline
analysis of scanned data as well as comparison to original files (e.g. CAD files). Further a
software development-kit (SDK) is shipped together with the sensor, which will allow to im-
plement the scan data directly into the companies own software environment, which is a high-
ly beneficial point for this application.
FACTOR RATING REASON / SPECIFICATION
1) SIZE 1 20,6 * 20,5 * 6,4 cm = 2702,72 cm3
2) COST 1 Approx. 300.000 SEK
3) ACCURACY 1 27 m (length measurement)
4) REPEAD-
ABILTY 0 (unknown)
5) SCAN SPEED 10 Approx. 1,5 sec.
6) RIGIDITY OF
THE SYSTEM 2
No IPX standard, delicate optics, according to webpage
“dust- and splash water proof”
7) OPEN FOR
SIMILAR AP-
PLICATION
8 (Further elaboration below)
8) FEASABIL
PROCESS IN-
TEGRATION
4 (Further elaboration below)
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Reason for the rating of 8)
The ATOS Core System can theoretically be integrated into the machines environment, re-
garding the size of the sensor. With bigger parts and especially parts with freeform surfaces as
turbine blades, the sensor has to capture the part from different angles, which in the narrow
machining area can become difficult with the size of the sensor.
The rating for the GOM ATOS Core 200 is graphically presented in the radar chart below,
Figure 19. The graphical representation will allow for easier comparison between different
solutions in the next end of this chapter.
1
1
1
0
10
28
4
0
1
2
3
4
5
6
7
8
9
10
1)
2)
3)
4)
5)
6)
7)
8)
Figure 19 - Radar Chart for solution 3: The result of the GOM stereo camera shown in a
graphical way, for all eight rated factors.
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4.4 Result of Measuring Solution Analysis
In this chapter a conclusion will be drawn to the researched and rated sensors, based on which
a recommendation can be given on which sensor to proceed with. Followed by the validation
in the next chapter that will provide a feasible sensor for the automation of the measuring pro-
cess.
In this thesis was initially shown, that three techniques of measuring can be applied: CMM,
Triangulation and Time of Flight (See 2.4 - Sensor Systems for Surface Measurement). Due
to time restrictions the solution using CMM was not considered. When continuing with this
project, further effort should be put into researching all possibilities to ensure the best suitable
solution is used.
In the following graph, the results of the three rated solutions are overlaid to allow direct
comparison as well as to define the best solution.
0
1
2
3
4
5
6
7
8
9
10
1
2
3
4
5
6
7
8
Solution 1 - Micro-Epsilon "LLT 2900-100" Solution 2 - LMI "Gocator 2440" Solution 3 - GOM "ATOS Core 200"
Figure 20 - Overlay of all three rated solutions in one radar chart,
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The sensor research showed that the different technologies have their own advantages, which
can be seen in Figure 20 above. However, the best overall solution in the research solutions is
solution 1: Micro-Epsilon LLT2900-100 laser line sensor. In the next chapter the validation
for this solution will be discusses and executed.
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5 Validation of Proposed System through Experiments
To validate the researched measuring system, the sensor was lent from the supplier to carry
out test trials and validate the effectiveness of the solution.
As pointed out in the result section of chapter 4 “Analysis of Most Suitable Measuring Solu-
tions for the Application” the best sensor for the stated needs is the laser line sensor from
“Micro-Epsilon Messtechnik GmbH & Co. KG” from Ortenburg in Germany. The model
“LLT 2900-100” was provided by the company two weeks, free of charge to carry out tests.
The test procedure – in short – was, that the sensor was moved along the sample surface. The
data of the scan was imported into the specialised CAM software, where print paths were cre-
ated on the scanned surface.
For this, the CAM expert Christian Walter from “Netvision Datentechnik GmbH u. Co. KG”
from Ulm in Germany was present during the tests. The company provides the CAM software
to Trumpf and other customers. Further the supervisor of the thesis, Sebastian Kaufmann
from Trumpf was present during the tests as well.
The experimental work was carried out at the research facilities of Trumpf in Ditzingen,
Germany for Trumpf Maskin AB. The machine used, was a Trumpf TruLaser Cell 3000, were
the sensor was applied to the machining head and measurements were carried out on sample
parts, all of which is described in detail in section Fel! Hittar inte referenskälla..
After that the testing procedures is explained and the different parameters for machine and for
the sensor are stated.
The results of the tests together with the specification, lead to a conclusion which are stated
and discussed in the following chapter 7.
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5.1 Validation Setup and used Equipment
In this section the setup for the validation and tests is mentioned and explained.
In the following Figure 21, the whole setup can be seen as used.
The following equipment was used:
Machine: Trumpf TruLaser Cell 3000
Computer: Sony Vaio Laptop FN, with Windows 8.1
Sensor: Micro-Epsilon scanCONTROL LLT2911-1004 – Version: 45-14
Scan Software: Scan Control Configuration Tool 5.2
View Software: Scan Control 3D View 3.1
Others: LAN cable 7m, Power cable 2m, Magnetic device holder
For the test special demonstration parts from Trumpf were used, which are used for different
demonstration purpose in the company. They have different angles on the surface crosswise
and along the surface, which will show the possibilities of the sensor. The part was used in
three different versions during the test, all of which can be seen in Figure 22.
4 The sensor used for the validation was a different one than the one being research for the thesis and used for the
comparison in chapter 4. Sensor compared: LLT2900-100; Sensor validated: LLT2911-100. The two models
differ in their ability. Second mentioned one can execute comparisons in the sensor head – offline – without a
external computer. They are, however, technically the same sensors as it was explained by Micro-Epsilon!
Figure 21 - The setup as used for the tests of the sensor. The sensor can be seen attached to
the machine head and connected to the computer.
Computer running the
measurement program
Sensor with magnetic
arm
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When referred to a part number, the above-mentioned numbers for the parts will be used re-
spectively. Figure 22.
The sensor itself was attached to the machine head with a magnetic holder, which is feasible
to hold the sensor proper enough in position for test purposes of this thesis. As a next step, a
ridged plate for attaching the sensor needs to be engineered to make the measurements more
stable. Further, the sensor was connected with the LAN cable to the computer running the
Configuration Tool software from Micro-Epsilon and to the plug with the included power
cable. A close caption of the sensor next to the machine head can be seen in Figure 23.
Figure 22 - Three types of the demonstration parts used for the test. All made of sheet metal
and stapled together with welding spots, used for the validation. Left to right: 1) clear part, 2)
LMD coated part crosswise to the sheet metal layers, 3) chalk sprayed clear part
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5.2 The Validation Procedure
The test was carried out with the “best practice” method, where with different parameters for
the measurement the best possible outcome was achieved.
Each part was placed under the laser onto the table and measured, after each round one of the
parameters in the Configuration Tool Software was changed:
exposure of reflection detector
feed of the machine / scan speed in X direction.
number of profiles saved
part arrangement
part angle to sensor
The full list of the applied measurements parameters and the series of measurements done,
can be seen in
The best measurement results where respective numbers: 13, 17 and 28. The parameters of the
measurements can be seen in Appendix V.
The result as it is shown in Scan Control 3D view, looks as it can be seen in. In Figure 24 the
result of measurement number 17 (See: Appendix V - Parameters list used for measurements
carried out with the LLT 2900-100) can be seen as an example.
The result shows the 1280 points distributed over the surface of the part, the colour indicated
the distance from the sensor to the target in colour grades.
Figure 23 - Close caption of the sensor next to the machine head, mounted with the magnetic
arm.
Magnetic holder with
adjustable arm
Laser line Sensor from
Micro-Epsilon “LLT
2900-100”
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The so-called blind spots can be seen at the three areas of the measurement. The left, which is
the beginning of the measurement, where the part has a surface in an angle of 180 ° to the
sensor, which makes it impossible to reflect the laser from there.
More deflection can be seen downwards in peaks at the beginning of the measurement, these
are the holes on the base plate, as seen in Figure 22.
Figure 25 shows the blind spots including some reflections from the quite rough surface at
this area, where single points reflect towards the sensor.
Figure 24 - The result of scan number 17, viewed in Scan Control 3D Viewer 3.1.
Figure 25 - Blind spots during the measurements, as the angle towards the sensor gets greater
then 180 degrees.
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5.3 Validation Results
The validation shows, that the chooses solution of the Micro-Epsilon “LTT 2900-100” has the
ability to meet the demands and the specification needs of Trumpf to realise the initially pre-
sented idea.
With that the Micro-Epsilon LLT2900-100 laser line sensor is concluded to be one possible
and valid solution to be used for further development of an integrated measurement solution
in the Trumpf TruLaser Cell 3000 Series.
The measured data could be successfully imported to the ADEM CAM software and printing
paths could be set on the scanned surface, as the following Figure 26 shows, made in previ-
ously mentioned software from Net-Vision, the supplier of special CAM software for Trumpf.
Further several improvement areas could be identified during the test, in order to realize a
integrates measuring solution. All of which will be mentioned in the next chapter and which
built the foundation for the future work section.
Figure 26 - The scanned data imported to the ADEM CAM software (in green), with the pro-
cessed additive lines (in yellow) along the surface.
Florian Säger
55
6 Identification of Future Work Packages based on Validation
In this chapter future work packages are mention, which will need attention in order to fulfil
the goal and develop an automatic measuring solution. All the work packages are based on the
problems that occurred during validation of the sensor. If identified during the validation, the
problem sources are stated as well. From all occurred problems, future work requirements can
be derived, which serve the need to develop the machine integrated measuring solution for the
repair process with LMD.
The proposed sensor in section 5.3, is one of many possibilities to solve the stated engineering
problem. However, as a conclusion it can be said that it is a valid solution to be used. Further
development of the project within Trumpf will show if all needs can be fulfilled with it.
The biggest problems faced during validation are the followings:
1) Blind areas when angles bigger then approx. 180 degrees to the sensor
Starting at approximately 60 degrees more Measruing errors occur
2) 3D measuring of more complex parts not realisable with one axis movement
3) Chatter of the sensor during measurement
4) Measurement errors with shiny surfaces
5) Scan is to uneven; post processing needs to be improved to reduce errors in surface
All of which need to be solved to make the measuring process possible with the suggested
sensor.
The possible causes of for the previous stated problems are explained in the following. Addi-
tionally, a possible solution, the author recommends, is stated as to each point.
1) The blind spots are caused by the measurements’ principle of the sensor. The triangu-
lation principle is not able to see reflections with the angle pointing to far away to the
detector.
A possible solution: More axis needs to be moved and in real-time used to re-
calculate the measurement of the sensor together with the internal machine head posi-
tion, in order to retrieve the part measurements in relation to the machine origin. (See
next step for more detail in a similar problem.
2) As stated before, with a one or two axis movement complex parts can hardly be meas-
ured, which will make it necessary to move more axis simultaneously.
A possible solution: Instead of one axis moving along the part, the surface could be
scanned with a 5-axis movement or even 6-axis (including the turn and twist table). To
write a test program the ADEM CAM software could be used and implement the sen-
sor as a “new tool”. Which makes it possible to automatically generate the NC-code
Florian Säger
56
for measuring the part in defined distance, within seconds.
As a post-process the scanned data from the sensor needs to be re-calculated in real
time with the internal machine positioning data. The part is then defined in relation to
the machine origin.
3) The sensor was first of all attached with an arm, which was mounted to the machine
head just with magnetic force. This allows vibrations and thus movement.
A possible solution: A first solution has to be designated mounting for the sensor to
avoid long levers and thus vibration of the sensor system.
Another colleague of Trumpf, Mr. Christoph Scharfenberg, stated another issue. The
sensor adds more weight to the machine head, which is damped electronically with
waves to its exact kinematic properties. Thus, the sensor has to be added into the ma-
chines internal tool list, with the exact properties as well, so that the dumping does not
allow the sensor to vibrate in eigenfrequency.
4) Shiny surfaces as part 1 is showed wrong measurement points occurring.
A possible solution: The surface can be coated with chalk spray, which makes it matt
and thus reduces the errors. That could be shown in the results as well.
However, it would add additionally work and time to the process, thus experts for la-
ser measurement should be asked if changes to the parameters of the sensor can help
to reduce such errors as well.
5) The scan shows sometimes too accurate measures, which then appear as a rough sur-
face when zoomed in to the measuring result. This leads to an increased computing of
the tool path, since mathematically the toolpath is longer and makes the process un-
necessary unsteady.
A possible solution: The scan can be post-processed with some basic algorithms (av-
erage, arithmetic mean,…) to flatten it. A study should be researched or executed on
the back draws of different algorithms, since they always will resolve in reduced detail
of the surface data.
With that the problems which occurred where stated and possible reasons for the problem
occurring where stated. Further the problem solving, and thus future work concepts were stat-
ed as well.
Florian Säger
57
7 Conclusion of the Work
In this work the research question was stated in the beginning, which derived from customer
needs. After the problematic was explained the necessary theory for this topic was introduced.
Based on that different measuring techniques where qualitative assessed to narrow down pos-
sible solutions. In further course the market was then scanned for purchasable systems, and
available products where assessed quantitative against each other by the use of a catalogue of
rating factors. The best product was then purchased and attached to the mentioned machine,
with that a validation could be carried out to prove that the product is applicable for the re-
searched purpose.
Answering the Research Questions
The research question (See chapter Research Question, page 6), and all further sub questions
are stated again below and answered respectively. Summing up, the feasibility study answered
RQ 1: “Is it feasible to integrate a sensor system into the enclosure of the Trumpf Tru-
Laser Cell 3000 Series machine, to measure metal parts fully automated and detect
worn/defect areas on them to use the machines’ LMD process to repair mentioned are-
as?”
Yes, it is possible to do that. For example, the laser line sensor from Micro-Epsilon (LLT
2900-100) is a feasible solution for that. The validation of this particular sensor has shown,
that measuring results are sufficient and the integration of the sensor to the machine would be
possible from a hardware and a software perspective. However, future validation and verifica-
tion needs to be carried out to address stated problems from chapter 6.
Further the sub-questions were answered in this thesis work as well:
RQ 1.1: “What will be the best measuring system for this purpose?”
As shown in the report, the best suitable solution, which is proposed to use and further devel-
op, is it the Micro-Epsilon LLT 2900-100 laser line sensor.
RQ1.2: “What are biggest challenges to face when developing this solution entirely?
The challenges which have to be faced and solved in order to engineer stated system, are stat-
ed in section 6, where their causes are listed, and possible solutions are given as well. It is
further suggested to develop a solid business case.
Further Conclusions
To ensure the future success of the LMD process, it was shown as crucial that the process
need further automation. In particular during validation it showed that both, the machine and
the CAM program need too much input from a user to work fully automated. Further experi-
ence will remain a crucial part of the process chain if no standardisation is developed.
To finalise this project, it needs to be highlighted that some topics need more attention to en-
sure a successful development. Some focus should be directed towards other solutions, since
Florian Säger
58
not all to the market available solutions could be researched to the full extend in this project
due to time limitation.
In addition to that a business case should be created which shall include a market research to
estimate the market size and with that determine the economic success of the product.
Overall, the thesis was successful. A solution was researched and both qualitative and quanti-
tative methods were selected. In the last step the proposed solution could be validated. In ad-
dition to that, all future work packages were pointed out. By solving them, an automated re-
pair process using the Trumpf TruLaser Cell 3000 Series and the LMD process is possible.
Florian Säger
59
III. References
Bagci, E. (2009). Reverse engineering applications for recovery of broken or worn
parts and re-manufacturing: Three case studies. Advances in Engineering
Software, 40(6), 407-418. doi:10.1016/j.advengsoft.2008.07.003
Bellocchio, F., Borghese, N. A., Ferrari, S., & Piuri, V. (2013). 3D Surface
Reconstruction: Multi-Scale Hierarchical Approaches: Springer New York.
Boehm, V. (2016). Hybrid Manufacturing of Turbine Components - Laser metal
deposition (LMD) and adaptive repair for higher precision and shorter
production time. Laser Technik Journal.
Candel, J. J., Amigó, V., Ramos, J. A., & Busquets, D. (2013). Problems in laser
repair cladding a surface AISI D2 heat-treated tool steel. Welding
International, 27(1), 10-17. doi:10.1080/09507116.2011.592707
Chen, F., Brown, G. M., & Song, M. (1999). Overview of three-dimensional shape
measurement using optical methods. Optical Engineering, Vol. 39, No. 1,
January 2000, No. 39, 22.
Corner, B. D., D' Apuzzo, N., Li, P., & Tocheri, M. (2006). Overview of 3D surface
digitization technologies in Europe. Paper presented at the Three-
Dimensional Image Capture and Applications VII.
Gao, W., Zhang, Y., Ramanujan, D., Ramani, K., Chen, Y., Williams, C. B., . . .
Zavattieri, P. D. (2015). The status, challenges, and future of additive
manufacturing in engineering. Computer-Aided Design, 69, 65-89.
doi:10.1016/j.cad.2015.04.001
GmbH, G. (2018). Webpage GOM GmbH - ATOS Core. Retrieved from
https://www.gom.com/metrology-systems/atos/atos-core.html
Inc., L. T. (2018). Gocator 2400 Product Series - Technical Specifications. In.
International, A. (2015). ASTM F2792-12a. In Standard Terminology for Additive
Manufacturing Technologies (pp. 3).
KG, M.-E. M. G. C. (2018). Laser Profile Scanner - Technical Data Sheet. In.
KG, T. G. C. (2018a). Press release: TRUMPF increases sales to 3.6 billion euros
[Press release]. Retrieved from
https://www.trumpf.com/en_SE/company/press/global-press-releases/press-
release-detail-page/release/trumpf-steigert-umsatz-auf-36-milliarden-euro/
KG, T. G. C. (2018b). TRUMPF Gruppe - Unternehmensprofil. Retrieved from
https://www.trumpf.com/de_INT/unternehmen/trumpf-gruppe/
KG, T. G. C. (2018c). TRUMPF internal document (not public) / TruLaser Cell
3000 Technology package Deposition Line (LMD) / Internal document:
M299. In: TRUMPF.
KG, T. G. C. (2018d). TRUMPF Products. Retrieved from
https://www.trumpf.com/en_INT/products/?LS=1
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KG, T. G. C.-. (2017). Trumpf Geschäftsbereicht 16/17. Retrieved from
KG, T. G. C.-. (2018). Trumpf Media Server (Image Database for Employees). In.
Liu, Z., Jiang, Q., Li, T., Dong, S., Yan, S., Zhang, H., & Xu, B. (2016).
Environmental benefits of remanufacturing: A case study of cylinder heads
remanufactured through laser cladding. Journal of Cleaner Production, 133,
1027-1033. doi:10.1016/j.jclepro.2016.06.049
Mahamood, R. M. (2018). Laser Metal Deposition Process of Metals, Alloys, and
Composite Materials.
Morrow, W. R., Qi, H., Kim, I., Mazumder, J., & Skerlos, S. J. (2007).
Environmental aspects of laser-based and conventional tool and die
manufacturing. Journal of Cleaner Production, 15(10), 932-943.
doi:10.1016/j.jclepro.2005.11.030
Petrat, T., Graf, B., Gumenyuk, A., & Rethmeier, M. (2016). Laser Metal Deposition
as Repair Technology for a Gas Turbine Burner Made of Inconel 718. Laser
Assisted Net Shape Engineering 9 International Conference on Photonic
Technologies Proceedings of the Lane 2016, 83, 761-768.
doi:10.1016/j.phpro.2016.08.078
Romero-Carrillo, P., Lopez-Alba, E., Dorado, R., & Diaz-Garrido, F. (2012).
Machining a Free-Surface via Reverse Engineering. Key Engineering
Materials, 502, 91-96. doi:10.4028/www.scientific.net/KEM.502.91
Serres, N., Tidu, D., Sankare, S., & Hlawka, F. (2011). Environmental comparison of
MESO-CLAD® process and conventional machining implementing life cycle
assessment. Journal of Cleaner Production, 19(9-10), 1117-1124.
doi:10.1016/j.jclepro.2010.12.010
Solutions, L.-I. L. (2018). Lunovu LMD - scanning and NC generation and
execution. Retrieved from http://www.lunovu.com/1/
Wimpenny, J. J. P. M. R. T. C. P. D. (2012). Remanufacture of turbine blades by
laser cladding, machining and in-process scanning in a single machine. 7.
Zhang, X., Li, W., Cui, W., & Liou, F. (2018). Modeling of worn surface geometry
for engine blade repair using Laser-aided Direct Metal Deposition process.
Manufacturing Letters, 15, 1-4. doi:10.1016/j.mfglet.2017.11.001
Zheng, J., Li, Z., & Chen, X. (2006). Worn area modeling for automating the repair
of turbine blades. The International Journal of Advanced Manufacturing
Technology, 29(9-10), 1062-1067. doi:10.1007/s00170-003-1990-6
Florian Säger
61
IV. Appendix 1
Appendix I – Data specification sheet page 13 of the Micro-Epsilon LLT 2900-100
laser line sensor. Source: (Micro Epsilon Messtechnik GmbH 2018, p. 13)
Florian Säger
62
Appendix II - Data specification sheet page 13 of the Micro-Epsilon LLT 2900-100
laser line sensor. Source: (Micro Epsilon Messtechnik GmbH 2018, p. 17)
Florian Säger
63
Appendix III – Data specification sheet of the laser line sensor from LMI Technolo-
gies Gocator 2440. Source: (LMI Technologies Inc. 2018, p. 2)
Florian Säger
64
Fro
m:
Bö
rje L
ars
so
nbo
rje
.lars
so
n@
ca
sca
de
.se
Su
bje
ct:
SV
: F
orm
Su
bm
issio
n -
Ko
nta
ktf
orm
ulä
r -
Se
arc
hin
g f
or
a m
easu
ring
syste
m f
or
reve
rse
eng
ine
erin
g
Da
te:
27
. Ju
ly 2
01
8 a
t 1
0:0
3
To
:F
lori
an
Sä
ge
rfs
ag
er@
kth
.se
Från
:Sk
icka
t:Ti
ll:Ä
mn
e:
Hej
ag
ain
Bö
rje,
Th
ank
yo
u f
or
yo
ur
fast
rep
ly.
I w
ant
to m
enti
on
th
e G
OM
AT
OS
Co
re p
rod
uct
as o
ne
of
the
solu
tio
n i
n m
y t
hes
is.
Th
us
I n
eed
to
giv
e so
me
det
ails
to
it
for
the
use
in
clu
din
g a
so
urc
e. In
part
icu
lar
I w
ant
to s
tate
th
ese
dat
a:-
size
of
the
dev
ice
Bö
rje:
AT
OS
Co
re
20
0 –
Se
ns
or
·
M
easuring a
rea:
200 m
m x
150 m
m
·
W
ork
ing d
ista
nce:
250 m
m
·
P
oin
t spacin
g:
0.0
8 m
m
·
S
ensor
dim
ensio
ns:
appro
x.
206 m
m x
205 m
m x
64 m
m
·
W
eig
ht:
appro
x.
2.1
kg
- o
utp
ut
dat
a fo
rmat
- in
terg
ener
atio
n i
n e
xte
rnal
so
ftw
are
po
ssib
le (
So
ftw
are D
ev.K
it a
vai
lab
le?)
- th
e p
urc
has
ing
co
st
- ac
cura
cy
- re
pea
tab
ilit
y
- sc
an s
pee
d (
surf
ace
rev
erse
en
gin
eeri
ng
, p
art
10
0 *
10
0 m
m)
Appendix IV - Data specification via email from Börje Larson, who sent this data upon re-
quest for a specification sheet. He is responsible from the company Cascde, the retailer for
GOM products in the Nordic countries.
Florian Säger
65
Fe
edFe
edPr
ofi
le F
requ
enz
Exp
osur
e
[mm
/se
k]
[mm
/min
][1
/s]
[m
s]
TE
ST_1
53
0030
550
5
“_2
""
""
"in
terp
ol i
nva
lid
po
ints
act
iva
ted
no
w a
t th
e e
dge
s a
lot
of
fail
ure
s o
ccu
red
“_3
""
""
"in
terp
ol d
eact
ivat
ed;
inte
nsit
y ch
ang
ed
to 1
00
“_4
16
0"
237
51
“_5
2,5
150
"95
00
,5C
han
ge
d t
o S
ampl
e 2
“_6
4,5
270
"50
00
,75
Me
asr
um
ing
are
a= "
big
" (+
/-40
mm
)
“_7
""
""
"S
am
ple
til
ted
in
an a
ngle
to
the
fro
n, t
o s
ee h
ow
refl
ecti
on c
ha
nges
; M
easr
umin
g ar
ea
= "
very
big
"
Big
dea
d a
rea
s ar
e
sho
win
g
“_8
""
"48
0"
Sa
mp
le t
ilte
d t
o t
he
side
; Me
asu
rin
g ra
nge
= "
big"
“_9
""
""
"M
ea
sru
ing
filt
er
dea
civa
ted
, th
us
po
st p
roce
ss f
ilte
rin
g
can
be
appl
ied
; Ma
x Z
va
lue
30
4m
m
“_10
74
2025
320
0,7
5M
ea
suri
ng
are
a =
stan
dard
“_11
14
840
"18
0"
“_12
""
""
2
“_
131
710
2050
230
"g
ood
me
asur
me
nt
“_14
""
"30
0"
“_15
""
2515
0"
“_16
14
840
""
0,1
“_17
""
""
0,2
go
od m
eas
urm
ent
“_18
""
"17
00
,35
“_19
""
""
0,7
5
“_20
""
""
1,5
“_21
""
""
2
“_22
""
""
5
“_23
""
""
10
“_24
""
""
20
“_25
""
""
40
“_26
""
""
40
Ch
ang
e t
o S
amp
le N
o. 3
“_27
""
""
5
“_28
""
""
"C
han
ge
d a
ngle
of
sen
sor
tow
ard
s a
pp
rox.
10
deg
ree
s
tow
ard
s th
e s
can
dir
ect
ion
go
od m
eas
urm
ent
“_29
""
""
"C
han
ge
d a
ngle
of
sen
sor
tow
ard
s a
pp
rox.
20
deg
ree
s
tow
ard
s th
e s
can
dir
ect
ion
“_30
""
"C
han
ge
d a
ngle
of
sen
sor
tow
ard
s a
pp
rox.
30
deg
ree
s
tow
ard
s th
e s
can
dir
ect
ion
File
nam
e#
of
pro
file
sO
ther
ch
ange
s R
emar
ks
Appendix V - Parameters list used for measurements carried out with the LLT 2900-100.
Own Excel Table for measurements parameters, bases on trial and error method.
TRITA ITM-EX 2019:123
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