NO FULL TEXT AVAILABLE. This thesis contains 3rd party copyright material. ----- This thesis describes a new manufacturing performance evaluation and production
planning method called Fuzzy-MRP-II (F-MRP-II) model, which deals with uncertain
information in the MRP-II system and then shows the consequences of uncertain
situations to decision-makers. This model enables decision-makers to prioritize
customers' orders, evaluate the best suppliers and the most suitable production lines.
The output of this model is a production plan and strategies which result in the best
production benefits and reduce risks. This model is based on fuzzy set theory, fuzzy
evaluation method, analytical hierarchy process (AHP) method and fuzzy logic
techniques to improve the traditional MRP-II system so that it can deal with decisionmaking
on the basis of uncertain information.
This F-MRP-II model considers and covers all of the five essential manufacturing
elements: manpower, equipment, raw material, production techniques and environment.
The model is divided into three parts. These are: first, customers' uncertain ordering
behaviour including market forecasting, secondly imprecise and flexible production
processes and environments and thirdly the best selection of suppliers. The result of the
model's first step shows the best selection for each factor under different conditions and
the correct evaluations, such as the suppliers' performance evaluation and the
performance of production lines. Then based on these results and the company' s correct
production and sales' strategies, F-MRP-II helps decision-makers make correct
production plans and decisions.
The following is a brief abstract for each chapter in this thesis to provide a quick
Chapter 1 "Introduction and Background". This chapter describes traditional
MRP/MRP-II systems as applied in industries to manage the supply chain. From this
author's experiences and from discussions with colleagues, we have found that,
especially in the Fast Moving Consumer Goods (FMCGs) industry, there is much
uncertain information used in decision-making. It is well recognized within the FMCGs
industry that the problem of uncertain information is greater than in most other
industries. Unfortunately, the MRP systems cannot deal with the problems and the
decision-makers cannot see the uncertain situation clearly. This makes it difficult to
make appropriate selections of suppliers and production plans.
Chapter 2 "Purpose of study and contributions". This chapter describes the author's
motivation for the main task of the thesis as well as the contributions of the project. It
then summarizes this study's contributions to knowledge and the model's potential in
Chapter 3 "Literature Review and discussions". This chapter discusses first, the
different methods and models in the literature relating to the manufacturing production
planning area. It then discusses different decision-making methods when dealing with
uncertain and imprecise information such as the fuzzy logic method, which is widely
used in the automatic control area. This. chapter also provides an analysis of the
disadvantages of traditional MRP/MRP-II systems, and the safety stock inventory
methods for dealing with uncertain customer requirements. One method is the just-intime
method. However, it is risky when there is a high level of uncertainty or
Chapter 4 "Methodology". This chapter contains the research methodology used in this
project as a general self-lead research project. Then it describes the author's F-MRP-II
model and its application.
Chapters 5 and 6, deal with F-MRP-II modeling and the results and discussion from a
case study. Chapter 5, "Evaluation and Selection Models of Manufacturing Elements
Based on AHP Method" presents the details of the AHP modeling steps and calculation
process. Chapter 6, "Using a Fuzzy Logic Method to Simulate High Profit Production
Plan" presents the fuzzy logic modeling process. Based on a case study analyzing the
results of the model it shows how the model can benefit a company. All the data for the
case study were collected from a Global FMCGs food company. Based on a Business
Confidential Agreement, all data and information are treated in confidence. Details of
the data and calculation process are shown in Appendix 1.
Chapter 8, "Conclusions". This chapter deals with the relevance, validity and further
research and development potential derived from the methodology.
Manufacturing Resource Planning (MRP-II), Fast Moving Consumer Goods (FMCGs),
Analytical Hierarchy Process (AHP), Fuzzy logic