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Ref. M . Janovjak, 15th April 2013 1
InSysteAInnovative Systemic Applications
ISPE Workshop Hamburg, 18.-19.April 2013 „Regulatorischer Druck und Kostendruck in der Pharmaindustrie: Trends zur Veränderung der Produktionsprozesse“ Trend 8: Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz: ein Weg zu besserer Kapitaleffizienz, höherer Geschwindigkeit, Kostenreduzierung und dynamischer Adaptierbarkeit.
Ref. M . Janovjak, 15th April 2013 2
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 3
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 4
InSysteAInnovative Systemic Applications
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 1. Challenge
„The complexity of Manufacturing supply chain processes
often overwhelms our ability to understand them.“
In this perspective we are challenged to evolve
an advanced approach to master it.
Ref. M . Janovjak, 15th April 2013 5
InSysteAInnovative Systemic Applications
An advanced approach is needed that enables users - to handle dynamic complexity (timely changes of e.g. product portfolio, disposition of operational processes, trade offs…) - to optimize performance (costs reduction, maximization throughput, OEE, cycle time, process capability…) - to utilize environment (small order sizes, responsiveness, resources, shift / time regime…)
“at the same time” in a “balanced” and “pro-active” way
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 1. Challenge
Ref. M . Janovjak, 15th April 2013 6
InSysteAInnovative Systemic Applications
Such advanced approach - requires a systemic approach, which concentrates on the whole reference system rather than on segments or single events. - calls for understanding the causal structures and generative mechanisms of the manufacturing supply chain which govern its system behavior. - must be based on a dynamic rather than static view (analytical and synthetic).
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 1. Challenge
Ref. M . Janovjak, 15th April 2013 7
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 8
InSysteAInnovative Systemic Applications
demand supply Manufacturing SC
process
Levers
KPI, Benefit potentials System
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 2. Systemic view
Ref. M . Janovjak, 15th April 2013 9
InSysteAInnovative Systemic Applications
demand supply Manufacturing SC
process
Levers
KPI, Benefit potentials System
Manufacturing SC
process
Manufacturing SC
process
Optimization of assets & capacity utilization; Reduce inventory levels; Reduce Cycle Time; Maximize throughput; Improve Process capability & robustness;
Process design; Policies and principles; Dynamic & linkages of processes; Product portfolio & product quality; Demand (order sizes, scheduling, …)
Process steps & structure; Equipment characterization; Process parameters; Materials; Resources; …
System elements
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 2. Systemic view
Ref. M . Janovjak, 15th April 2013 10
InSysteAInnovative Systemic Applications
Levers
KPI, Benefit potentials System
Manufacturing SC Process schematics
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 2. Systemic view
demand supply Manufacturing SC
process
Manufacturing SC
process
Process steps & structure
Equipment characterization
Process parameters
Materials Resources
Ref. M . Janovjak, 15th April 2013 11
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 12
InSysteAInnovative Systemic Applications
How to evolve Model based approach
Such Model based approach requires - dynamic and causal process understanding - consideration of data and expertise - implementation of policies and principles - application of adequate methodology
Build a model of the real system and provide simulation for determination of the best solution.
real system
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 3. Model based approach
Ref. M . Janovjak, 15th April 2013 13
InSysteAInnovative Systemic Applications
Expertise Policies Principles
real system
data, structure,
interactions
Methodology Tool
Model
Simulation results
Modelling
Optimization cycle
Implement best solution
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 3. Model based approach
Ref. M . Janovjak, 15th April 2013 14
InSysteAInnovative Systemic Applications
Model is simplified but validated representations of the real system.
Simulation explores the sensitivity of the model behaviour and based on it determines any alternatives and what-if scenarios of the answer to a reel problem.
Model consists all relevant cause-and-effect relationships of the manufacturing SC System components, incl. feedbacks
The simultaneous and complementary (multifunctional) consideration of levers and KPI’s enables to optimize the manufacturing SC Process and to determine the best performing solution.
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 3. Model based approach
Ref. M . Janovjak, 15th April 2013 15
InSysteAInnovative Systemic Applications
The Model based approach is one and only way to provide solutions in pro-active way.
The capability to act pro-active opens up additional value proposition - process design - capital efficiency - implementation speed - cost avoidance - risk mitigation
On the purpose, the capability of the applied methodology and tool (SW) has to be of unique performance.
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 3. Model based approach
Ref. M . Janovjak, 15th April 2013 16
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 17
InSysteAInnovative Systemic Applications
System Dynamics is a holistic universal applicable Methodology for studying & managing complex feedback systems..
Vensim is a tool (SW) applying SD methodology which enables - to transform knowledge and data into model - to build a model of any complex system - to determine the best performing solution under consideration of the multidimensional optimization policy.
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 4. Methodology & Tool
Ref. M . Janovjak, 15th April 2013 18
InSysteAInnovative Systemic Applications
Vensim Models delivers (SOURCE: VENTANA LTD).
Intelligence amid mixed signals by combining human expertise and data to determine the true signal Focus amid distractions by using cumulative knowledge to highlight new leverage Consensus amid multiple views by integrating knowledge and reconciling differences Understanding amid complexity By tracking the interactions of causes and effects, ... Confidence amid uncertainty by showing the odds and the best ways to influence them while experience deepens
productioninventory control
production rate
inventory
production status
change over
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 3. Model based approach
Ref. M . Janovjak, 15th April 2013 19
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 20
InSysteAInnovative Systemic Applications
Depending on focus (Process, Purpose, Objectives) there is a wide spectrum of possible applications, exemplary: • Manufacturing: demand and supply, material & product flows, … demand & order tracking, WIP / Inventory, throughput, Cycle Time, yield, utilization / OEE, Resources…
• Manufacturing: processing & technology process parameter variations and associated risks, impact on product quality…
• Process development speed / time to market, cost reduction…
• Product Portfolio Life Cycle Management time to market, costs, risks, value generation…
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 21
InSysteAInnovative Systemic Applications
Manufacturing: demand and supply, material & product flows,… Solid manufacturing & packaging (coated tablets, Lean / WIP, Cycle Time, …)
Biopharmaceuticals bulk manufacturing & fill & finish (organizational design /WIP, CT, …) Liquid fill & finish (syrup, Design & investment efficiency)
Biopharmaceuticals bulk manufacturing & fill & finish (PFS, Lean / WIP, SC responsiveness, …)
Packaging & Palletizing area (demand & performance variations, Eq. design,…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 22
InSysteAInnovative Systemic Applications
Manufacturing: processing & technology Process model and risk based multivariate quantitative investigational analysis and improvement of an API process consisting multiple process steps (Dialysis, Ultra filtration , Distillation, Sterile Filtration) Process development Process development and transfer (solid, granulation) Product Portfolio Life Cycle management PPLCM Management and strategic governance (LC Phases II to launch (Pilot Study))
For more information about the 3 Ex. above, please contact InSysteA
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 23
InSysteAInnovative Systemic Applications
Manufacturing: demand and supply, material & product flows,… Solid manufacturing & packaging (coated tablets, Lean / WIP, Cycle Time, …)
Biopharmaceuticals bulk manufacturing & fill & finish (organizational design /WIP, CT, …) Liquid fill & finish (syrup, Design & investment efficiency)
Biopharmaceuticals bulk manufacturing & fill & finish (PFS, Lean / WIP, SC responsiveness, …)
Packaging & Palletizing area (demand & performance variations, Eq. design,…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 24
InSysteAInnovative Systemic Applications
Solid manufacturing & packaging
Purpose Build a model which enables to elaborate the Lean optimized manufacturing and packaging process (one certain coated tablet product) Starting position Order based packaging installed, rhythm wheel “optimized “ push practice in bulk manufacturing (at each work center) Approach Objectives Deployment of Pull principle across entire process, optimized campaign size in dispensing & granulation, batch and customer order tracing , back log control, representation of QC & QA process, Eq. utilization Optimization Objectives CT reduction (responsiveness), Cost Reduction (WIP, Inventories, batch yield) Results Cost reduction through reduction of WIP / Inventory ca. 300 k CHF/a while maintaining same customer service KPI
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 25
InSysteAInnovative Systemic Applications
Batch tracing, QC & QA processing
Backlog control per each process step
Model Parameterization
Initialization Pre-position batches
Solid manufacturing & packaging
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Pull Order based
Customer order tracing
supply Tabletting Dispensing Granulation
Packaging
Warehouse Coating
Capacity / work center optimized rhythm wheel push practice
Scheduling
demand
Tabletting Dispensing Granulation Coating Packaging
Pull Principle across entire process
25
Total wait time - 25mg (Stacked)200
150
100
50
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing HourSimulatedPullSystem - Granulating HourSimulatedPullSystem - Tabletting HourSimulatedPullSystem - Coating Hour
Total wait time - 50mg (Stacked)400
300
200
100
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing HourSimulatedPullSystem - Granulating HourSimulatedPullSystem - Tabletting HourSimulatedPullSystem - Coating Hour
Total wait time - 100mg (Stacked)400
300
200
100
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing HourSimulatedPullSystem - Granulating HourSimulatedPullSystem - Tabletting HourSimulatedPullSystem - Coating Hour
Total wait time - 200mg (Stacked)400
300
200
100
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing HourSimulatedPullSystem - Granulating HourSimulatedPullSystem - Tabletting HourSimulatedPullSystem - Coating Hour
Mean Cycle Times (Stacked)1,000
500
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
Dispensing HourGranulating HourTabletting HourCoating Hour
Total Product at Location (Stacked)20,000
15,000
10,000
5,000
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
Day
SimulatedPullSystem - Dispensing kgSimulatedPullSystem - Granulating kgSimulatedPullSystem - Tabletting kgSimulatedPullSystem - Coating kgSimulatedPullSystem - Packing kg
25 mg Material Losses (Stacked)200
150
100
50
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing kgSimulatedPullSystem - Granulating kgSimulatedPullSystem - Tabletting kgSimulatedPullSystem - Coating kgSimulatedPullSystem - Packing kg
50 mg Material Losses (Stacked)400
300
200
100
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing kgSimulatedPullSystem - Granulating kgSimulatedPullSystem - Tabletting kgSimulatedPullSystem - Coating kgSimulatedPullSystem - Packing kg
100 mg Material Losses (Stacked)400
300
200
100
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing kgSimulatedPullSystem - Granulating kgSimulatedPullSystem - Tabletting kgSimulatedPullSystem - Coating kgSimulatedPullSystem - Packing kg
200 mg Material Losses (Stacked)400
300
200
100
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem - Dispensing kgSimulatedPullSystem - Granulating kgSimulatedPullSystem - Tabletting kgSimulatedPullSystem - Coating kgSimulatedPullSystem - Packing kg
Machine Utilisation - (running average)100
50
00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
day (Day)
SimulatedPullSystem -Granulating PercentSimulatedPullSystem -Tabletting PercentSimulatedPullSystem -Coating PercentSimulatedPullSystem -Packaging Percent
Eq. utilization Idle times WIP mfct.
Cycle Times
Yield losses
Tabletting Dispensing Granulation Coating
Packaging
Simulation 30 days; 90 orders;
Ref. M . Janovjak, 15th April 2013 26
InSysteAInnovative Systemic Applications
Manufacturing: demand and supply, material & product flows,… Solid manufacturing & packaging (coated tablets, Lean / WIP, Cycle Time, …)
Biopharmaceuticals bulk manufacturing & fill & finish (organizational design /WIP, CT, …) Liquid fill & finish (syrup, Design & investment efficiency)
Biopharmaceuticals bulk manufacturing & fill & finish (PFS, Lean / WIP, SC responsiveness, …)
Packaging & Palletizing area (demand & performance variations, Eq. design,…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 27
InSysteAInnovative Systemic Applications
Biopharmaceuticals bulk manufacturing & fill & finish Source: Lee Jones, Ventana Ltd.
Purpose Assess impact of change from functional to process-oriented organization given; • Random demand stream for multiple products • Shared production lines • Alternate physical locations of packaging
Approach Study current system and build ‘as is’ SC model; validate Identify performance and structural changes when moving from functional to process-oriented organization (‘to be’) Modify model/parameter values to represent multiple ‘to be’ options Evaluate impact on KPI such as delivery performance, stock holding and cycle times, and determine possible benefit potentials Results Reduction in cycle time of (~25% ) and stocks (~33%) while maintaining same customer service KPI
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 28
InSysteAInnovative Systemic Applications
filling transport bulk storage
finished goods
transport packaging transport delivery
forecast
production campaign
packaging schedule
FTE OEE
Materials
Production campaign drives by forecast
Orders drives packaging schedule
Order data informs forecasting
Orders
Pull bulk for packaging
Pull API through production
Product pushed through filling process
Availabilility of FTE and Materials, packaging line capability influence packaging performance
Product pushed though packaging to finished goods and delivery
Primary contained product
thawing compounding
Biopharmaceuticals bulk manufacturing & fill & finish Source: Lee Jones, Ventana Ltd.
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
WIP
WIP WIP
WIP
Production campaign drives by pulled scheduling
Order data and WIP Informs scheduling
Orders and order tracing drives order data
Order tracing
Product pulled through filling process
Ref. M . Janovjak, 15th April 2013 29
InSysteAInnovative Systemic Applications
Manufacturing: demand and supply, material & product flows,… Solid manufacturing & packaging (coated tablets, Lean / WIP, Cycle Time, …)
Biopharmaceuticals bulk manufacturing & fill & finish (organizational design /WIP, CT, …) Liquid fill & finish (syrup, Design & investment efficiency)
Biopharmaceuticals bulk manufacturing & fill & finish (PFS, Lean / WIP, SC responsiveness, …)
Packaging & Palletizing area (demand & performance variations, Eq. design,…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 30
InSysteAInnovative Systemic Applications
Liquid fill & finish
Purpose Assess the costs reduction potential of currently coupled line and determine the possible benefits in the case of decoupling of the line. Starting position Order based SC installed, optimized rhythm wheel controlled manufacturing (“push”); planned project for line decoupling; Approach Objectives Determination of the solution with biggest cost reduction potential, incl. decision support for project realization. Lean optimization, batch and customer order tracing, representation of QC & QA process, Eq. utilization; Optimization Objectives Cost Reduction (WIP / Inventories, change over costs) Results Cost reduction Lean optimized current coupled line: 25 % Cost reduction Lean optimized decoupled line (planned project): < 30 % Planned project cancelled due to insufficient rentability (cost avoidance 250 kCHF)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 31
InSysteAInnovative Systemic Applications
Fill + Pack
Fill Pack
(Simulation period = 500 days)
Inventory
Change over
Filling Packaging Costs (%)
0
20
40
60
80
100
Coupled line - Coupled line - Decoupled Decoupled
0
5
10
15
20
25
30
Coupled line - Pull (lean Decoupled line - 0
5
10
15
20
25
30
Coupled line - Rhythm wheel Push Coupled line - Pull (lean optimized current) Decoupled Push on Fill / Pull on Pack Decoupled line - Pull on Fill&Pack
0
20
40
60
80
100
Coupled line - Rhythm wheel P Coupled line - Pull (lean Decoupled line - Push
Total Costs
50%
60%
70%
80%
90%
100%
110%
Coupled line - Rhythm wheel Push Coupled line - Pull (lean optimized current) Decoupled line - Push on Fill / Pull on Pack Decoupled line - Pull on Fill&Pack Decoupled line - Pull on Fill&Pack (QC parallel)
Coupled line - Rhythm wheel Push (current)
Coupled line - Pull (lean optimized )
Decoupled line - Push on Fill ; Pull on Pack Decoupled line - Pull on Fill & Pack Decoupled line - Pull on Fill & Pack and QC parallel
Decoupled line (planned project)
Policy optimized
Coupled line
Cost reduction 25 %
Cost reduction potential < 30 %
Liquid fill & finish
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 32
InSysteAInnovative Systemic Applications
Manufacturing: demand and supply, material & product flows,… Solid manufacturing & packaging (coated tablets, Lean / WIP, Cycle Time, …)
Biopharmaceuticals bulk manufacturing & fill & finish (organizational design /WIP, CT, …) Liquid fill & finish (syrup, Design & investment efficiency)
Biopharmaceuticals bulk manufacturing & fill & finish (PFS, Lean / WIP, SC responsiveness, …)
Packaging & Palletizing area (demand & performance variations, Eq. design,…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 33
InSysteAInnovative Systemic Applications
Biopharmaceuticals bulk manufacturing & fill & finish
Purpose Build a model which enables to elaborate the Lean optimized manufacturing SC process Starting position Order based SC installed, BB Cycle Time focused project implemented Approach Objectives Deployment of Pull principle, optimized batch and customer order tracing , back log control, representation of QC & QA process, Eq. utilization Optimization Objectives CT reduction (responsiveness), Cost Reduction (WIP, Inventories) Results Cost reduction through reduction of 4 batches of 24 in WIP Inventory cost reduction ca. 2’000 k CHF/a
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 34
InSysteAInnovative Systemic Applications
Pull principle
Raw materials
Primary Packaging
filters
Compounding and Filling line preparation
Preparation and assembling
Needle Shields
Stoppers
PFS barrel
“Additives II”
“Additives I”
Frozen API
first In line
compounding filling optical inspection packaging
Biopharmaceuticals bulk manufacturing & fill & finish
Model Parameterization
Initialization Pre-position batches
Scheduling Planned
batch orders
customer order tracing batch tracing
Subscripts
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Calculations results : Calculations results : Results : - Cycle times at each process steps
- customer order backlogs (duration, # of orders, at delivery) - stock levels WIP at product and at process step (Lt., # of syringes)
- Equipment utilization (OEE)
- mean Cycle times stacked - Total product demand & available supply (released filled product prior sec. packaging)
- Yield / CONC Simulation period 60 days; 469 orders
Ref. M . Janovjak, 15th April 2013 35
InSysteAInnovative Systemic Applications
Manufacturing: demand and supply, material & product flows,… Solid manufacturing & packaging (coated tablets, Lean / WIP, Cycle Time, …)
Biopharmaceuticals bulk manufacturing & fill & finish (organizational design /WIP, CT, …) Liquid fill & finish (syrup, Design & investment efficiency)
Biopharmaceuticals fill & finish (PFS, Lean / WIP, SC responsiveness, …)
Packaging & Palletizing area (demand & performance variations, Eq. design,…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 36
InSysteAInnovative Systemic Applications
Packaging & Palletizing area
Purpose Determine performance of packaging area and needed size of conveyor system and palletizer and provide sensitivity analysis of impact of variation of order sizes and lines performance on results. Starting position Upgrade of existing production. Approach Objectives Deployment of random functions to simulate variations of - order sizes - lines performance - change over and line clearance
Optimization Objectives & Results - Determination of impact of the shift to smaller orders sizes on performance and throughput - Determination of material flow (cases) and palettizer utilization (mean, St. Dev.) - Model design adaptable to extended scope (scheduling, order control, WIP…)
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 37
InSysteAInnovative Systemic Applications
Randomized duration change order and share fraction based decision of change order activity
Batch control cycle with determination of cumulative # of batches and change order execution data
Randomized order size and line performance and determination of batch duration and processing time
Packaging line outflow accumulated in cases, conveyor system & transport to Palletizer
Palletizer performance & utilization
Palletizing process as flow rate into buffer in front of Palletizer and warehouse
Packaging line outflow in cases
Packaging & Palletizing area
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Ref. M . Janovjak, 15th April 2013 38
InSysteAInnovative Systemic Applications
P40P50P45
max palletising @ 4000060
50
40
30
20max palletising
Palletizer Buffer
6,000
4,500
3,000
1,500
00 10000 20000 30000 40000
Time (Minute)
VVP
Palletizer Buffer : P40Palletizer Buffer : P50Palletizer Buffer : P45
Palletizer outflow per hour
60
45
30
15
00 10000 20000 30000 40000
Time (Minute)
Palle
t/H
our
Palletizer outflow per hour : P40Palletizer outflow per hour : P50Palletizer outflow per hour : P45
Packaging & Palletizing area
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Applications (Examples)
Simulation period 30 days; 1’574 orders
Ref. M . Janovjak, 15th April 2013 39
InSysteAInnovative Systemic Applications
Content 1. Challenge
2. Systemic view
3. Model based approach
4. Methodology & Tool 4. Applications (Examples)
5. Conclusions
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Conclusions
Ref. M . Janovjak, 15th April 2013 40
InSysteAInnovative Systemic Applications
Benefit of deployment of model based approach with System Dynamics Vensim - enables to master complex manufacturing SC processes and to harvest even “very high hanging fruits” not achievable with other approaches. - leverages user to be in position to elaborate and select optimized solution and making sustainable decisions with minimized risk and maximized benefit. -. results in paradigm shift to facilitate pro – active management of complex manufacturing SC processes. Over all, the universal applicability of the applied methodology & tool opens up to build a platform for a flexible and effective governance to master future challenges.
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 5. Conclusions
Ref. M . Janovjak, 15th April 2013 41
InSysteAInnovative Systemic Applications
Thank You !
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Matej Janovjak, M.Sc. S.F.I.T. (Dipl.Ing.ETH) InSysteA GmbH, Innovative Systemic Applications, CEO University of applied Science, Basel, Lecturer for System Dynamics Tel. Mobile +41-79-536 61 56 Tel/Fax +41-52-659 47 22 Address Dorfstr. 56, 8212 Nohl, Switzerland Email [email protected] Web www.insystea.ch
Ref. M . Janovjak, 15th April 2013 42
InSysteAInnovative Systemic Applications
Backup slides
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz
Ref. M . Janovjak, 15th April 2013 43
InSysteAInnovative Systemic Applications
Correctness and validity of the model
- Structural fit (structure of the causal relations between variables and sub-processes)
- Behavior correctness (the behavior of the real system is appropriately reproduced by the model, i.e. dynamic and logical behave, equation & operating point)
- Plausibility and consistency of results (qualitative and quantitative, extreme conditions)
- Validity for application (it the model is appropriate for the domain in which it is to be used and conforms with purpose, i.e. based on comparison of the experimental values and simulation results, the model enables required changes and must provide requested answers, i.e. problem solving results )
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 3. Model based approach
Ref. M . Janovjak, 15th April 2013 44
InSysteAInnovative Systemic Applications
Optimieren der Manufacturing Supply Chain Prozesse durch einen modellbasierenden Ansatz, 4. Methodology & Tool
The methodological capability and the tool characteristics determine the power of the context of the modelling & simulation
• The methodological capability
- modelling of the dynamic processes - modelling of the complex feedback systems - application field universality - suitable for study and practical management - practical to knowledge mgmt.
• The tool characteristics
- wide range of mathematic functions - easy to model and validate - high calculating capacity - high capability to provide multivariate analysis and simulation - easy customisable front-end cockpit - powerful and easy customisable graphical presentation - integrated data management (data collection, bi-directional IM/IT integration, …)
Methodology capabilities and tool characteristics (in extracts)