Engineering Production Control Strategies A Guide to Tailor Strategies that Unit

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Management for Professionals
2012
Engineering Production Control StrategiesA Guide to Tailor Strategies that Unite the Merits of Push and PullAuthors:

• Christoph Karrer
• …show all 1hide
  

ISBN: 978-3-642-24141-3 (Print) 978-3-642-24142-0  (Online)



A Guide to Tailor Strategies that Unite the Merits of Push and Pull

Series: Management for Professionals

Karrer, Christoph

2012, X, 176 p. 74 illus.

ISBN 978-3-642-24142-0

  Immediately available per PDF-download (no DRM, watermarked)

About this book

• Combines Lean manufacturing and algorithmic detailed planning and scheduling
•                                         With a real-life case study
•                                         A look behind the scenes and into the physics of production control
  

Identifying and customizing suitable control strategies is a challenging task, especially when production systems have to cope with variable demands, forecast error, and unstable processes. The focus of this book lies on helping companies with complex and discrete production systems to tailor a production control strategy to their needs. Thereby, the mutual merits of “push” and “pull” systems are taken into account, leading to hybrid strategies. Consequently, the book addresses practitioners who are interested in looking behind the scenes and into the physics of production control. A real-life case study demonstrates the practical applicability of the presented framework.

Contents
1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Need for a PCS Engineering Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Suitable Industrial Context for Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3 Structure of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Production Control Strategies (PCS) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1 Fundamental Concepts and Coherences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.1 PCS in the Broader Context of Production Planning
and Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
2.1.2 The Push/Pull Enigma and Their Basic Implementations . . . . . . . 8
2.1.3 The Order Penetration Point . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.4 The Influence of the PCS on Operational Performance . . . . . . . . 12
2.2 Review of Current Research on PCS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.1 Segmentation of Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.2.2 PCS Method Development . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.2.3 PCS Selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.2.4 PCS Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2.2.5 Related Design Questions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3 Synthesis and Positioning of the Following Work . . . . . . . . . . . . . . . . . . . . 35
3 A Queuing Network Based Framework for PCS Engineering . . . . . . . . 37
3.1 Design Drivers and Initial Complexity Reduction . . . . . . . . . . . . . . . . . . . . 37
3.1.1 Structuring Design Drivers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37
3.1.2 Complexity Reduction by Defining Planning Segments . . . . . . . 38
3.2 Generic Model Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.2.1 Notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41
3.2.2 Queuing Network Representation of Planning Segments . . . . . . 41
3.2.3 Basic Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.2.4 Analysis of the Resulting Solution Space . . . . . . . . . . . . . . . . . . . . . . 46
vii
3.3 Mapping Production System Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.3.1 An Integrated Approach to Stochastic Modeling
of Production System Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48
3.3.2 Definition of a Measure for Production System Variability . . . 51
3.4 Mapping of Demand Variability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3.4.1 Stochastic Modeling of Demand Variability . . . . . . . . . . . . . . . . . . . 53
3.4.2 Excursion: Possible Involvement of Customers . . . . . . . . . . . . . . . . 57
4 Numerical Optimization of Control Parameters Along
a PCS Engineering Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.1 Objective Function Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.1.1 Selection of Valuation Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.1.2 Value Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.2 Implementation of a Supporting Simulation Framework . . . . . . . . . . . . . 65
4.2.1 Introduction to Discrete-Event Simulation and the
Platform ‘AnyLogic’ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
4.2.2 Implementation of Planning Segments . . . . . . . . . . . . . . . . . . . . . . . . . 67
4.2.3 Implementation of the Demand Model . . . . . . . . . . . . . . . . . . . . . . . . . 69
4.2.4 Implementation of the Production System Model . . . . . . . . . . . . . 70
4.3 A PCS Engineering Process to Optimize Production
Control Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3.1 Approach and Process Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
4.3.2 Step 1 – Ki Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
4.3.3 Step 2 – OPPj Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
4.3.4 Step 3 – FCTj and Sij Determination . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
5 Investigation of the Push/Pull Integration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.1 Influencing Factors and Rules for the Decision among
Push and Pull . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.1.1 Hypothesis and Experiment Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
5.1.2 Determination of Relevant Factors and Derivation
of Decision Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
5.2 Closed-Form Determination of the Push/Pull Integration
Parameters FCT* and S%* . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
5.2.1 Hypothesis and Experiment Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . 90
5.2.2 Derivation of a Closed-Form Parameterization
for Hybrid Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5.2.3 Extension to the Multi-Product Case . . . . . . . . . . . . . . . . . . . . . . . . . . . 95
5.3 Analysis of the Performance Increase Achievable
with the Hybrid Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.3.1 Drivers for the Relevance of the Decision among
Hybrid and Pure Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.3.2 Derivation of a Demand Variability Measure to Characterize
Environments That Favor Hybrid Strategies . . . . . . . . . . . . . . . . . . . 99
5.4 Summary of Insights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
viii Contents
6 Case Study from the Electronics Manufacturing Industry . . . . . . . . . . . 103
6.1 Case Introduction and Specific Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . 103
6.1.1 Introduction to the Business and Manufacturing Process . . . . . 103
6.1.2 Identification of the Improvement Need
and Specific Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.2 Model Development and Parameterization . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
6.2.1 Production System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
6.2.2 Parameterization of Planning Segments . . . . . . . . . . . . . . . . . . . . . . . 107
6.2.3 Parameterization of the Demand Model . . . . . . . . . . . . . . . . . . . . . . . 108
6.3 PCS Design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
6.3.1 Strategy Derivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
6.3.2 Impact Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
6.4 Implications and Implementation Hints . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
7 Conclusion and Further Research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
7.1 Research Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
7.2 Limitations and Further Research Directions . . . . . . . . . . . . . . . . . . . . . . . . 119
8 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
8.1 List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
8.2 List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
8.3 List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
8.4 List of Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
8.5 Complex Production Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
8.6 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 128
8.7 Delimitation against Other Generic PCS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
8.8 Evolution of the Maximum Size Reduction of the Solution
Space . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 134
8.9 Simulation Model Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135
8.9.1 Planning Segment Graphical Representation . . . . . . . . . . . . . . . . . . 135
8.9.2 Demand Model: Graphical Representation . . . . . . . . . . . . . . . . . . . . 135
8.9.3 Java Code Executed at Forecast Arrival
(Event ‘FCarrival’) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
8.10 PCS Engineering Process: Numerical Optimization
of Model Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138
8.10.1 Setups for Experiments and Illustrations . . . . . . . . . . . . . . . . . . . . 138
8.10.2 Influence of Over-Capacity on the MTF Versus
MTS Decision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
8.10.3 Converting Utility Improvements into WIP Reductions . . . . 141
8.11 Investigation of the Push/Pull Integration . . . . . . . . . . . . . . . . . . . . . . . . . . 142
8.11.1 Graphical Representation of Experimental Setup
in Anylogic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
Contents ix
8.11.2 Experiments and Results to Determine Influencing
Factors for Upstream Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
8.11.3 Experiments and Results to Determine Closed-Form
Solutions for FCT* and S%* . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148
8.11.4 Extension to Arbitrary Forecast Error Distributions . . . . . . . . 157
8.11.5 Experimental Setup for the Extension to the
Multi-Product Case . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
8.11.6 Analysis of Drivers for the Impact Magnitude . . . . . . . . . . . . . 161
8.12 Anylogic Model of Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165
8.13 Used Software Products . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 169
8.14 About the Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170




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