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Abstract
Reduced setup costs and setup times have been described as necessary and facilitating factors for the achievement of small-lot manufacturing (i.e., just-in-time (JIT), stockless production or zero inventory). One important aspect of managing setup-reduction activities is the decision of how to allocate a limited investment budget between competing setup-reduction opportunities. This decision is defined in this dissertation as the investment-allocation problem (IAP). Several practitioners recommend prioritizing investments in those setups which take the longest time to complete. There is little in the academic literature to either support or challenge this recommendation.
The purpose of this dissertation is to explore this aspect of managing setup-reduction programs and to develop simple, practical guidelines for managing setup-reduction investments. The first stage of exploration involves a field study which documents the relationship between investments and the corresponding reduction in setup. The principal product of this field study is an empirically-based model of the relationship between investment and setup cost reduction. The second stage of exploration involves extending an existing EOQ-based setup-reduction model to gather insights into the investment-allocation decision. The principle insight from this stage of research is that the optimal allocation policy is to invest in multiple products simultaneously when a sufficiently convex investment function is assumed. The implications of the empirically-based investment-cost relationship are also considered. The final stage of inquiry involves evaluating several heuristic allocation policies for their relative impact on inventory and setup costs in a capacitated, dynamic demand environment. These policies are compared to the recommendation to prioritize the highest setup times. The conclusions from this analysis show that there are conditions where the highest setup time policy is an effective method, but in general, a policy which exploits the tradeoff between setup and inventory costs produces greater inventory and setup savings.
