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© ifm© ifm
IMPLEMENTATION OF KAIZEN ACTIVITY
THROUGH IOT TO EXPLOIT VIBRATION DATA
IN MACHINE TOOL APPLICATION
JIMTOF 2018 – ifm efector co., ltd.
ifm diagnostic gbmh 114/12/2018
© ifm© ifm
Your speaker:
Mr. Edil Alvarez
ifm diagnostic gbmh 214/12/2018
ifm diagnostic (International Project Manager Vibration Systems)
© ifm© ifm
Let us introduce the Y Path approach
5 % of the data is
processed in the controller
– in bytes per millisecond
95 % of the data should be
processed in the IT world
– in megabytes per
second
ifm diagnostic gbmh 314/12/2018
Industry 4.0 – what does that mean for ifm customers?
© ifm© ifm
Y Path: from the sensor to SAP (Database)
Y Path provides 95 % of the process data without detour via the controller.
IT and automation technology are integrated in a simple and economical
manner for the first time – from the sensor to the SAP® database.
ifm diagnostic gbmh 414/12/2018
© ifm© ifm
From sensor to SAP (Database)
For the first time, sensor data can be directly transmitted to the business
software – and this on a factory-wide or even worldwide level.
Evaluation of the obtained data in real time enables an increase in
production efficiency and energy savings in the context of Industry 4.0.
ifm diagnostic gbmh 514/12/2018
© ifm© ifm ifm diagnostic gbmh 614/12/2018
SPSPC,
Server Modbus-
TCP
Smart Observer
VSE DLL
Proprietary protocol
ifm OPC server VOS00x
(classic OPC)
VSE15x
Parameter software VES004
Office
LAN
OPC
Industry 4.0 = Online Condition Monitoring + Connectivity & Y Path
© ifm© ifm
WCM (World Class Manufacturing): Kaizen Activity 10 technical pillars and 10 management tasks to be improved
Commitment Involvement Communication Understanding Measurement Deployment
Implementation Evaluation Standardization with visibility Documentation
Sa
fety
/ H
ygie
ne
& w
ork
ing
en
viro
nm
ent
Kaizen Activity (WCM)
Custo
me
r S
erv
ice
Cost D
ep
loym
ent
Fo
cu
se
d Im
pro
ve
me
nt
Qu
alit
y C
on
tro
l
Au
ton
om
ous A
ctivity
Pro
fessio
nal M
ain
ten
an
ce
Ea
rly P
rod
uct /
Equ
ipm
ent
Ma
na
ge
ment
Pe
op
le D
eve
lop
me
nt
En
viro
nm
ent
ifm
solutions
are available
for all pillars.
Roadmap
solution
packages.
NOW
1-2 years
1.5 -2.5
years
ifm diagnostic gbmh 714/12/2018
© ifm© ifm
Key Principles of WCM
WCM comprises 10 technical and
10 managerial pillars
In every pillar 5 points can be achieved
The status is checked by audit through
WCM Experts
Status for each pillar is structured
from Step1 – Step7
Example:
Professional Maintenance
WCM Status is the result
>50 points BRONZE
>60 points SILVER
>70 points GOLD
>80 points WORLD CLASS
ifm diagnostic gbmh 814/12/2018
Commitment Involvement Communication Understanding Measurement
Deployment Implementation Evaluation Standardization with visibility
Documentation
Safe
ty /
Hyg
iene &
work
ing e
nvironm
ent
Kaizen Activity
(WCM)
Custo
mer
Serv
ice
Cost
Deplo
yment
Focused I
mpro
vem
ent
Qualit
y C
ontr
ol
Auto
nom
ous A
ctivity
Pro
fessio
nal M
ain
tenance
Early
Pro
duct
/ E
quip
ment
Managem
ent
People
Develo
pm
ent
Environm
ent
© ifm© ifm
ifm application solutions – RTM Improvement in Maintenance
ifm diagnostic gbmh 914/12/2018
Autonomous Maintenance
Professional Maintenance
RTM ifm solutionfrom
Time-Based (STEP 5 )
to
Condition-Based
Maintenance (STEP 6)
RTM
Real
Time
Maintenance
Predictive
Maintenance
Commitment Involvement Communication Understanding
Measurement Deployment Implementation Evaluation Standardization
with visibility Documentation
Sa
fety
/ H
ygie
ne
&
wo
rkin
g e
nvir
on
me
nt
World class
manufactur
ing
Custo
me
r S
erv
ice
Cost
De
plo
ym
en
t
Fo
cu
se
d Im
pro
ve
me
nt
Qu
ality
Con
tro
l
Au
ton
om
ou
s A
ctivity
Pro
fessio
na
l
Ma
inte
na
nce
Earl
y P
roduct / equip
ment
Managem
ent
Pe
op
le D
eve
lop
me
nt
En
vir
on
me
nt
© ifm© ifm ifm diagnostic gbmh 1014/12/2018
Steps of improvement
Step 1 Step 2 Step 3
Once the problem has emerged,
corrective measures are adoptedReactive
Step 4 Step 5
According to experience acquired,
appropriate corrective actions are
adopted to avoid repetition of an
already known problem
Preventive
Step 6
Improvement with
RTM ifm solution
from Time based (STEP 5 )
to Predictive
Maintenance
Proactive
enables for
Step 6
>> Preparation for
connection to SAP
© ifm© ifm ifm diagnostic gbmh 1114/12/2018
Predictive Maintenance
© ifm© ifm ifm diagnostic gbmh 1214/12/2018
Wear / Consumption WEAR INDICATORS INFLUENCE QUANTITIES
Rolling element bearing
1 - 4 months prior to failure:
Bearing frequencies,
vibrations, temperature and
abrasion
Before first measurable wear
indicator occurs (bearing noise):
Operating hours
Vibration- and impact-related
loads (dose)
Temperature load,
Bearing position (dose)
Play Unbalance, shaft vibrations Speed, operating hours, load
Milling toolAcceleration measurement
a_peak (cutting forces)
Processing time (use of the tool)
Tank content Filling level Consumption/km + history
Gearbox oilClouding, conductance, ph-
value
Temperature distribution during
operation
(Lithium-ion) battery Voltage drop Operating time, temperature
Tool clamp (HSC spindle)play; only towards end of
lifetime
Number of replacement cycles
Electronics Check sums, error logs Writing cycles (flash memories)
Ball screw drivepreload, overrolling noise
(vibrations)
12
Predictive MaintenanceDistinction of wear indicators and influence quantities
© ifm© ifm ifm diagnostic gbmh 1314/12/2018
Information
Machine running / not running Operating hours
Machine running with different loads/
operating points => load collective of the
operating hours
Operating mode; if possible, conclusions as to
further areas, e.g. performance factor
Number of impacts above limit value =>
degree of impact load
Operating mode, impacts during start-up
Bearing temperature > permissible value Viscosity of lubrication
Temperature classes of gearbox oils
Alarms / unit of time Micro-interruptions
Distance covered in linear guidance systemsOperating time
Acceleration of robots Material strain
Predictive MaintenanceA closer look at the influence quantities
© ifm© ifm
Influence
quantity ->
Wear
indicator
< MTBF > MTBF
HIGH
“vibration”
LOW
“vibration”
ifm diagnostic gbmh 1414/12/2018
Residual life: 1,200
operating hours
Influence Quantities
Runtime-counter
MTBF
Weak point
Corrective action
Longer service life
Money saved!
Preparation of
maintenance
measure
Planning and
implementing
maintenance
measures
Normal operation
No preventive
action necessary!
• No inspection
• No diagnosis
Predictive Maintenance
© ifm© ifm
Predictive Maintenance – a living system!
ifm diagnostic gbmh 1514/12/2018
© ifm© ifm
ifm diagnostic gbmh14/12/2018
OEE =
Availabilty Productivity Quality
X X
OEE (Overall Equipment Effectiveness)
The formula: OEE = A x P x Q
© ifm© ifm ifm diagnostic gbmh 1714/12/2018
Sources: IFW Hannover, WZL Aachen,
KIT Karlsruhe, VERSTAND research
project, Germany
OEE availability losses
Unplanned downtime classified by technical causes
Availabilty
© ifm© ifm
Wear 6 %
Lubrication 5 %
Leakage 4 %
Others 10 %
Crash, overload, wear, 75 %
1 2 3 4 5
Vibration monitoring can …
Make spindle load
transparent
Protect against overload
Avoid unplanned downtime
Reduce consequential
damage
ifm diagnostic gbmh 1814/12/2018
Source: KIT / IWB / ifm, 2018
OEE availability losses
Unplanned downtime classified by technical causes
Availabilty
© ifm© ifm
Motor spindle monitoring: typical error messages
Error messages Activities, alarm schedule
Vibration value too highCounters document the load collective; depending on the time spent in a
high vibration range, a reaction is also possible, if appropriate
Impact value too highDocument the incident, intervene in the process, if appropriate. Control
bearing condition (e.g. stone has hit the windscreen).
Imbalance too high – during
operationCheck the tool; verify process parameters, if necessary
Imbalance too high during
reference runWear of bearing
Poor bearing condition (BPFs) Prepare replacement of bearing
Temperature too high Check for electrical faults, inspect ventilation and cooling system
Maximum operating hours
reached
If lead times are long, prepare replacement of bearing, but wait for
deterioration of bearing condition. If operation exceeds expected service
life, ROI calculation provides reliable profitability forecasts.
Load classes green/yellow/red to be considered when evaluating the
operating hours.
ifm diagnostic gbmh 1914/12/2018
© ifm© ifm
Vibration severity (= effective vibration velocity or v_eff)
includes the sum of all amplitudes from 10 to 5,000 Hz (unit: mm/s).
The indicator v_eff is correlated with material fatigue.
Counters indicate the time spent working under a certain load.
Unbalance Cutting frequencies
Measurement of overall vibration (object v_eff)
ifm diagnostic gbmh 2014/12/2018
© ifm© ifm
Monitoring of motor spindle fatigue
ifm diagnostic gbmh 2114/12/2018
7000
5187
1154
659
0
1000
2000
3000
4000
5000
6000
7000
8000
Operating time o.k. yellow red
Ho
urs
Operating time
o.k.
yellow
red
During
process,
standard-type
spindle, 600
to 28,000 rpmin mm/s _rms
10-5000Hz
During
process,
HSC spindle,
28k to 40k
rpm
in mm/s _rms
10-5000Hz
A0 - 7 0 - 5
B
C 7 - 17 5 - 8
D 17- 23 8 - 12
E > 23 > 12
100 % lifetime when:
yellow < 10%
red < 1%
of total runtime
© ifm© ifm
Monitoring of shocks to the motor spindle
ifm diagnostic gbmh 2214/12/2018
Example of integrated data logger (VSE100):
Differing proportions of unbalance- and process-related vibrations
included in the overall vibration of a milling machine during various
processing steps
=> Optimisation potential
Unbalance
v_eff
© ifm© ifm ifm diagnostic gbmh 23
Crash monitoring: g-monitor (a_peak)
Crash measurement via acceleration impacts
(a_peak).
Correlation of acceleration with effective force:
(F = m*a).
Force impacts propagate in the material along 3
space axes.
Measurement time: 1 ms; alarms issued directly
to the NC unit via fast outputs.
Each impact above the crash limit is counted.
A single impact can destroy a hybrid bearing!
Analogy: stone hitting a glass window.
Check bearing after crash!
© ifm© ifm
During
process,
standard-
type spindle,
600 to
28,000 rpm
in g _pk
10-1000 Hz
During
process,
HSC spindle,
28 k to 40 k
rpm
in g_pk
10-1000Hz
Spindle
without
turning
15 6 4
25 13 10
G-monitor (a_peak)
ifm diagnostic gbmh 2414/12/2018
Impact beyond RED threshold:
potential destruction of bearings
To provide safety: subsequent bearing
check by reference run
Immediate reaction protects machine from
consequential damage
© ifm© ifm
Machine protection – why each millisecond saves money
ifm diagnostic gbmh 2514/12/2018
1: Rapid movement without disruption
2: Process-relevant shutdown threshold
(depends on material, tool and cutting parameters)
3: Spindle-relevant shutdown threshold
(protection of bearings and tool)
4: Destruction of the tool and/or workpiece;
bearings likely to be damaged
5: Overloading of feed drive and shutdown
of motor currentt / ms
Picture:
wikimedia.org
© ifm© ifm
QualityProcess quality
ifm diagnostic gbmh 2614/12/2018
Process-related limit values (g-monitor)
Tool-related limit values (g-monitor)
© ifm© ifm
Tool quality
ifm diagnostic gbmh 2714/12/2018
Milling cutter with 5 cutting edges
Tool okay
Milling cutter with 5 cutting edges
One edge worn
The next cutting edge must double its performance
=> Increase of g–level by 37 %
Quality
© ifm© ifm
Tool quality
ifm diagnostic gbmh 2814/12/2018
Raw acceleration signal
over one cycle
Edge #5 not cutting
broken
© ifm© ifm
Surface quality – chatter vibrations
ifm diagnostic gbmh 2914/12/2018
Stable process
Instable processChatter marks
© ifm© ifm
Process quality – summary
Tool quality
Tool balancing
Avoiding tool damage
Chatter detection (quality)
ifm diagnostic gbmh 3014/12/2018
OEE =
Availabilty Productivity Quality
X X
© ifm© ifm ifm diagnostic gbmh 3114/12/2018
Sources: IFW Hannover, WZL Aachen,
KIT Karlsruhe, VERSTAND research
project, Germany
OEE availability losses
Unplanned downtime classified by technical causes
Availabilty
© ifm© ifm
References & Case Studies
ZF, Germany – gearbox manufacturer
ZF Friedrichshafen global locations marked blue
Cost saving calculations for machine tool applications
In production
In maintenance
ifm diagnostic gbmh 3214/12/2018
Source of images: https://commons.wikimedia.org/wiki/Category:ZF_Friedrichshafen?uselang=de
© ifm© ifm
Cost savings in production – example 1
ifm diagnostic gbmh 3314/12/2018
Potential Cost Saving due to Simplified Machine Diagnosis
Simplified Fault Detection 77,220.00 ¥*
Without CM there can be no machine diagnosis upon receipt of an alarm message,
unless production is stopped.
Messages / year 1,50
Diagnosis without CM 3,00 h
Online diagnosis with CM (without shut-down of machine) 0,00 h
Machine-hour rate 17,160.00 ¥
Prevention of wrong decisions 278,784.00 ¥
Incorrect diagnosis results in an increase of machine downtime.
Wrong decisions / year 0,25
Unscheduled maintenance 65,00 h
Machine-hour rate 17,160.00 ¥
*Original calculation in EUR (€); basis of conversion: 1 Euro = 132 Yen
© ifm© ifm
Cost savings in production – example 2
ifm diagnostic gbmh 3414/12/2018
Potential Cost Saving due to Scheduled Maintenance Activity
Forseeable Exchange 350,064.00 ¥*
Whereas unscheduled maintenance consists of response time, time for procurement
of replacement parts and time for repair, scheduled maintenance is limited to
the time needed for repair.
Unscheduled maintenance 65,00 h
Scheduled maintenance 14,00 h
Failures / year 0,40
Machine-hour rate 17,160.00 ¥
*Original calculation in EUR (€); basis of
conversion: 1 Euro = 132 Yen
© ifm© ifm
Cost savings in production – example 3
ifm diagnostic gbmh 3514/12/2018
Potential Cost Saving due to Preventive Maintenance Activity(Quality issues)
Prevention of reject production 704,880.00 ¥*
Without CM, disturbance in a spindle is only noticed upon deterioration of the quality of
the parts produced. CM, however, provides for replacement of the spindle without
producing rejects.
Failures + messages / year (for quality reasons) 2,67
Quality inspection, every X pieces 50,00
Piece costs per blank 5,280.00 ¥
*Original calculation in EUR (€); basis
of conversion: 1 Euro = 132 Yen
© ifm© ifm
Cost savings in maintenance – example 1
ifm diagnostic gbmh 3614/12/2018
Potential Cost Saving due to Simplified Machine Diagnostics
Simplified Fault Detection 51,728.00 ¥*
Fault messages concerning spindles that are received via CMMS have to be verified on site
if there is no CM. CM provides for much faster and better diagnostics.
Messages / year 1,50
Diagnostics without CM 3,00 h
Diagnostics with CM 0,25 h
Master engineer's hourly wage rate 12,540.00 ¥
Prevention of Wrong Decisions 165,000.00 ¥
In case of a wrong decision regarding the spindle condition, the spindle is dismantled
and sent in for maintenance. With CM, no incorrect diagnosis can occur.
Wrong decisions / year 0,25
Maintenance of spindle (without damage) 660,000.00 ¥
*Original calculation in EUR (€); basis of conversion: 1 Euro = 132 Yen
© ifm© ifm
Cost savings in maintenance – example 2
ifm diagnostic gbmh 3714/12/2018
Potential Cost Saving due to Scheduled Maintenance Activity
Forseeable Exchange 76,745.00 ¥*
If maintenance is unscheduled, maintenance staff will be tied up with
repair of the damage.
Unscheduled maintenance without CM 65,00 h
Scheduled maintenance with CM 14,00 h
Failures / year 0,40
Master engineer's hourly wage rate (30%) 3,762.00 ¥
*Original calculation in EUR (€); basis of conversion: 1 Euro = 132 Yen
© ifm© ifm
Cost savings in maintenance – example 3
ifm diagnostic gbmh 3814/12/2018
Potential Cost Saving due to Preventive Maintenance Activity
Prevention of Consecutive Faults, Wear, Handling Errors 84,480.00 ¥*
Leaving faults undetected will provoke consequential
damage.
Consequential damage 10,00 %
Maintenance costs 2,112,000.00 ¥
Failures / year 0.40
Longer Lifetime of Components 132,000.00 ¥
With every case of prevented damage, the component lifecycle is extended.
Extension of lifecycle in per cent 5.00 %
Price of new spindle (motor spindle) 2,640,000.00 ¥
*Original calculation in EUR (€); basis of conversion: 1 Euro = 132 Yen
© ifm© ifm ifm diagnostic gbmh 3914/12/2018
Cost saving Calculation per Spindle (24-7 operation) / year*
Potential cost saving in production / year 1,411,014.00 ¥
Potential cost saving in maintenance / year 425,436.00 ¥
Total cost saving potential / year 1,836,487.00 ¥
*Original calculation in EUR (€); basis of conversion: 1 Euro = 132 Yen
Summary: cost savings per machine (= 1 motor spindle per year !!)
© ifm© ifm
Carlo Di Nicola on FCA / CNH projects
Carlo Di Nicola (ifm System Sales Engineer from Italy) is the
global coordinator for RTM systems of the FCA Group regarding
the implementation of WCM strategy (Kaizen activity).
His experience:
With our system we are currently present in more than 30 FCA
and CNH plants worldwide.
This means we are successfully monitoring over 50 machine
tools online!
ifm diagnostic gbmh 4014/12/2018
© ifm© ifm
References
Realised installations at Fiat Chrysler Automobiles:
FCA, Italy
CNH, Italy
FCA USA
CNH USA
FCA Brazil
CNH Brazil
FCA Serbia
CNH France
ifm diagnostic gbmh 4114/12/2018
© ifm© ifm
FLASH ALERT at Renault plant informing about anomalies at a
machining centre due to excessive vibration during machining
20-09-2018
Error: V_RMS 10 – 5000hz in mm/s -> wear condition of spindle
1) Vibration level with Smartobserver
2) Details with Diziview
3) Link to Smartobserver
4) Information
Purposes of the alert:
• Increase life of spindle
• Check physical load
• Determine cause of vibration
• Reduce vibration
• Measure the result
ifm diagnostic gbmh 4214/12/2018
Information + Action + Verification of results:
1) Identification of tool concerned -> P0114 machining of drill hole -> 25-09-2018
2) Anticipated action -> stiffen the mandrel of tool P0114 -> SM39 to 40
3) Anticipated action -> modify the milling cycle as in 4154?
© ifm© ifm
Renault: measurement of vibration level with SMARTOBSERVER
ifm diagnostic gbmh 4314/12/2018
• Supervision by ifm
SMARTOBSERVER
shows: RMS values
are too high.
• A warning is issued:
electrospindle is
subjected to too
much stress.
• Machining
conditions are not
good!
© ifm© ifm
Renault: 2.2 details with Diziview
ifm diagnostic gbmh 4414/12/2018
• Detailed analysis
shows that the
relevant vibrations
occur once per
cycle.
• Among all the
tools used, it is
always the same
tools that
generate these
vibrations.
© ifm© ifm
Renault: 4.1 – information relating to the tool
ifm diagnostic gbmh 4514/12/2018
• This is the tool causing the fault.
• Intended tool lifespan: 32,000 pieces.
• Tool has been destroyed 4 times
since beginning of the month.
• Following this analysis, Renault will
proceed to take corrective action.
© ifm© ifm
VSE1xx in electrical cabinet of machine tools
ifm diagnostic gbmh 4614/12/2018
ifm’s diagnostic
electronics
VSE1xx in the
electrical cabinet
of machine tools,
connected to the
Ethernet network.
Accelerometer is
mounted on the
spindle.
© ifm© ifm
JIMTOF 2018
Thank you very much for your attention!
ifm diagnostic gbmh 4714/12/2018