Production Planning

1
Production Planning Scheduling improvement
potential assessment with a System Dynamics model
for internal supply chain
Elisa Anggraeni and Zofia Verwater-Lukszo
Faculty of Technology, Policy and
Management August, 2003
2
Structure

• Introduction (Background, Challenges, Thesis
  assignment)
• System boundary
• Description of the proposed method
• Design phase
• Implementation phase System Dynamics model
• Utilization phase
• Conclusion
• Recommendation

Introduction
3
Introduction

• The importance of Production Planning and
  Scheduling in the achievement of productivity and
  competitiveness
• The complexity of production planning and
  scheduling in batch wise processes
• The necessity of effective performance
  measurement system in the decision making

Introduction
4
Challenges

• Identification of indicators which could measure
  the performance of production planning and
  scheduling
• Assessment of these performance indicators with
  regards to potential improvement of the main
  objective of the company
• Choosing the most preferred potential improvements

Introduction
5
Thesis assignment

• The study is dealing with formulating method to
  support production planning and scheduling
  decision making by utilizing the concept of
  performance measurement system to include
  explicitly the indicators for companys
  competitiveness and productivity
• System under study is the internal supply chain
  of batch wise processes specifically food
  processing company
• Development of a simulation model - System
  Dynamic

Introduction
6
System Boundary
System boundary
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The proposed method
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Identification of relevant Performance Indicators

• Identification of Performance Indicators using
  objective tree
• Decision makers can make their interests explicit
  and obtain insight in the objective and
  sub-objective relationship
• Systematically scrutinize the objectives with
  regards to the achievement of productivity and
  competitiveness

Design Phase
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The main objective tree
Design Phase
10
Criteria Hierarchy
Design Phase
11
Criteria Hierarchy
Design Phase
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Identification of improvement options

• Identification of improvement options using
  causal diagram
• To identify the leverage point/instrument
• To identify the influence mechanism of the option
  to the performance of the system

Design Phase
13
Causal relationship basis for System Dynamic
model
14
Assessment of Evaluation Parameters System
dynamic model

• The use of System dynamic
• Understand the behavior of the system
• How is the behavior of inventory level or
  production rate over simulation time?
• Experiment with the instrument to improve
  behavior of the system
• What is going to happen when production cycle
  is reduced?

Implementation Phase
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• System Dynamic Model for internal supply
• Three sectors in the internal supply chain
• Effect of policies strategies
• Different scenarios

Customer Order
Raw Material Inventory
Production Inventory
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System Dynamic model for the internal supply
chain sum up
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Simulation model
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Simulation model

• General framework easy to adapt to a specific
  plant situation
• With a specific model possible to calculate the
  expected changes in the pre-defined performance
  indicators by implementing improvement options
• Model already applied to two industrial
  situations
• Further validation needed

19
Case study on AVEBE

• General System Dynamic model adapted to this case
  
• The internal supply chain of PN-1 line of AVEBE
• Data which is used in this case study is from 8
  weeks observation carried out by Roeterink (2002)

System boundary
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Impact Table
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Making choice

• The act of making choice which includes
• Making trade off based on priority
• Choosing the most preferred options
• The use of Scorecard Method
• Comparing alternative for each criterion by using
  visual representation
• Allow discussion among decision maker
• Trade-off is done explicitly

Utilization Phase
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Priority assignment

• Profit gt competitiveness gt productivity
• Competitiveness
• lower product price
• higher delivery reliability
• higher quality
• higher flexibility
• lower delivery lead time

Utilization Phase
23
Ranking analysis

• Based on tradeoff, the most preferred improvement
  options are
• reduce safety stock coverage by 50
• reduce safety stock coverage by 10
• lengthen the production cycle to 12 weeks
• reduce target delivery lead time to 6 days
• reduce product changeover to 17 changes

24
Ranking analysis
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Treatment of Uncertainty

• Strategy to deal with uncertainty
• Stochastic model (one stochastic variable is
  involved) with different state of nature in the
  future
• Uncertainty Identification
• External Uncertainty
• System Response Uncertainty
• Value Uncertainty
• Sensitivity analysis using scenario design

Utilization Phase
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Robust improvement option

• From sensitivity analysis with different
  scenario, the ranking of options changes. Only
  two options survive in 4 different state of
  future
• Lengthen production cycle to 12 weeks
• Increase batch size by 5

27
Finding Robust options
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Conclusions

• The application of method provide
• Valuable contribution to the knowledge-base in
  the production planning and scheduling decision
  making
• Systematic way to structure information
  supporting decision making
• Tools to increase management understanding and
  insight over the internal supply chain
• Reproducibility of the proposed method depends
  largely on the adjustment, judgment and
  compromises as determined by the decision maker

29
Recommendation

• The overall method is sensitive to the change in
  companys objective, evaluation parameters, and
  system boundary so that close cooperation with
  the modeler is needed
• It would be useful to relax some assumption by
  making elaboration / disaggregation to obtain
  more detail analysis
• Further validation of the System Dynamic model
  would be beneficial