published_or_final_version / abstract / toc / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

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Production control and capacity configuration policies are critical to a manufacturing firm for effective inventory control. In the first part of this dissertation, a Dynamic Programming model and a solution algorithm are developed to obtain an optimal (near-optimal) production control policy. The solution algorithm is able to produce an extremely good policy under mild conditions, but is applicable only to problems with a limited number of products. For problems involving a large number of products, a heuristic algorithm based on a decomposition/aggregation scheme is then proposed. This algorithm overcomes the computational difficulty typically associated with Dynamic Programming problems with a large number of state dimensions. Computational test results are reported to show the performance of the policy generated by the heuristic algorithm. In the second part of the dissertation, the production lead time and operational cost performance of two capacity configurations are analyzed. Models are developed for each configuration to determine the amount of capacity which minimizes the total capacity acquisition and operational costs, including the inventory cost. Computational test results are presented to study the impact of problem characteristics on the superiority of each configuration.

The increased globalisation of the automotive industry of South Africa has brought with it both opportunities and threats for the various players. Companies taking advantage of the government's Motor Industry Development Plan have quickly learned that exporting both components and vehicles is the most suitable way forward. Toyota SA, in its new role as a global player has strategized that sourcing parts from local suppliers will give it the competitive advantage to then compete internationally. The company has planned to increase its local content targets from 40% to around 70% in the next few years. The question that rises to the fore is "are the local suppliers able to cope in meeting this challenge?" This study explores the various issues faced by Toyota SA as well as its local suppliers in attempting to achieve these targets. While Toyota SA has to deliver the expectations of developed countries, it is faced by a local supplier base that for many reasons, lags behind the rest of the world. The study adopts classical techniques for analysis as well as recent techniques in evaluating the suitability of the increased localisation strategy. Finally, based on the impact of the various forces, recommendations are made as to the strong and weak points of the strategy. Poor product development capabilities and technical/operational improvement requirements at suppliers, the lack of internal resources at Toyota SA and finally the weak second and lower tier supplier levels all emerge as issues to be addressed. These issues cannot be ignored for the implementation of the increased localisation strategy to be successful. / Thesis (MBA)-University of Natal, Durban, 2003.

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Firms in several discrete parts manufacturing industries, e.g., electronics equipment, computers, telecommunications equipment etc. operate in a multi-plant environment where products are processed successively at several plants. Prior studies have ignored the interaction between different plants in a multi-plant scenario. The objective of this dissertation is to study the impact of coordination on the cost performance of a two-plant firm. / We propose a model that jointly determines production and inventory decisions so that the total cost of holding inventory and overtime, at the two plants is minimized. Our model captures the interaction between the two plants and is preferable to the uncoordinated or the sequential approach which ignores this interaction. We consider the case with limited capacity and explicitly model setup times. Strategies based on Lagrangian relaxation and Lagrangian decomposition methodologies are proposed to solve the model. / Two main findings emerge from this research. First, our results indicate that coordination could lead to improved cost performance and enhanced profits for firms. Two parameters, the setup time to processing time ratio and the capacity utilization at the two plants played a significant role in determining the cost improvements. Managerial implications relating to implementation of the coordinated model are discussed. The second important finding of this research is that Lagrangian decomposition consistently outperforms Lagrangian relaxation in terms of achieving better deviation from the optimal solution, for this problem. A Linear Programming based technique for further enhancing the convergence between the upper and lower bounds is presented. / In the quest for improved performance, multi-plant coordination represents an important strategy for firms. The contribution of the current research is in modelling some of the salient issues of this problem and exploring promising methodological directions.