In today's global economy the need for an efficient and optimised supply chain is increasing. Recent studies showed that supply chain management is one of the areas that have a great impact on the financial well being of an organization as well as customer satisfaction. The recognition of the importance of efficient and optimised supply chains has led to increasing investments in supply chain planning and execution systems. In order to compete in the global market place organizations want to develop systems that enable fast and effective on time delivery of products to customers. Therefore generating the necessary customer satisfaction. Today there are APS (Advanced Planning&Scheduling) systems available to help "manage" the supply chains. These tools were specifically designed to have the ability to rapidly and simultaneously plan and schedule customer demand while considering material and capacity constraints. Not only does these systems provide the ability to increase revenues, but it can also increase the customer service and cut costs by synchronized management of the complete supply chain. Although these systems help to improve the system, it is restricted to the static part and it does not incorporate the dynamic part. The result therefore is that a lot of "noise" still exists within the system once the results are achieved. This opened the way for solutions that can provide insight to the uncertainty and interdependency of processes and customer demand within the supply chain. One way of gaining insight into the system variation and interdependencies is through the use of simulation technology. This type of technology allows organizations to predict future behaviour and test future designs or do redesigns of their current supply chains. The scope of this dissertation is to develop a supply chain planning methodology, which will help to improve the understanding of the uncertainty and interdependency of processes within the supply chain. To design this methodology different steps are taken in order to introduce the final solution. Therefore, four main methods were used; literature research, market research, supply chain planning methodology development and a case study. The literature research brought to light the reasons for the inefficiencies and variations in supply chain planning and why the need for change exists. During the supply chain market research several supply chain planning and execution systems were under study. From this it was quite clear that the only way that organisations can ensure one optimal answer is when the demand is constant and there is a zero percent chance that it could change. In real world systems it is virtually impossible to accurately predict future demand 100 percent of the time, and therefore variability and randomness cannot be excluded from a supply chain solution. This paved the way for the introduction of simulation technology as a possible solution for this variability and randomness. The market research was concluded with the analyses of the current simulation solutions in the market. The next step in the design phase was the introduction of the new supply chain planning methodology. The main purpose of this new methodology is to use the power of modelling and simulation to improve the initial supply chain performance. This methodology focuses on initial supply chain design, analyses and optimisation. By introducing this methodology organisations are now able to compare current supply chains with an unlimited realm of possible future configurations .... and without disrupting the initial day-to-day operations of an actual supply chain. The methodology is also designed to help predict the supply chain performance in terms of throughput, tardiness, utilisation, profitability, and other key performance indicators ... In order to experience real-life supply chain problems a case study has been done. This case study is about the automotive industry, which will include the ordering of parts assembly of vehicles, warehousing and distribution of vehicles. Different problems and difficulties were experienced. In conclusion, this case study provided a better insight into the behaviour of a supply chain. The case study was used to evaluate the use of this new methodology and as a result certain inefficiencies were recognized. As a result of the evaluation certain improvements need to be made to the supply chain methodology in order to make it more suitable for the market. These improvements would focus on inventory planning, supply chain analysis as well as database integration. The result of the case study also showed that the supply chain planning methodology is now set to develop a supply chain solution on the lowest level. There is however a need to be able to grow this supply chain methodology from a low level to a relatively high level. These functions are among others higher-level planning modules, which focus on transportation, production, demand and distribution and performance measurements. The focus will be to introduce these functions as objects. Every object will have the ability to design a supply chain solution on a high level or low level depending on the detail and requirements. ••• I also believe that the one who adapts his policy to the times prospers, and likewise that the one whose policy clashes with the demands of the times does not. 11 Niccolo Machiavelli, 1525 / Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2006. / Industrial and Systems Engineering / unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/29999 |
| Date | 01 December 2005 |
| Creators | Von Raubenheimer, Albert Ludwich |
| Contributors | Mr P J Conradie, upetd@up.ac.za |
| Source Sets | South African National ETD Portal |
| Detected Language | English |
| Type | Dissertation |
| Rights | © 2001, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
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