Inventory Control for High Technology Capital Equipment Firms

Many firms within the high technology capital equipment sector are faced with a situation where effective inventory management is a rather complex and possibly most critical factor to their long-term profitability. Within this thesis we discuss the development of two decision support tools that address some of the unique aspects of the situation faced by Teradyne, Inc., one of the largest suppliers of semiconductor test equipment for the. We also discuss our implementation experiences and develop a framework that calls for a closer interaction with industry, which in our case has provided the motivation and laboratory for this research. In the first part we discuss our involvement with Teradyne over the course of the past four years. We highlight some of the problems faced by firms that operate in a manner and environment similar to Teradyne. We highlight two of the key problems that we chose for study and discuss their importance to Teradyne. We develop a framework that was used to develop good research problems that had an immediate practical impact. We believe that in the current era of limited public sector funding for fundamental research, our framework may provide some guidance for conducting research projects with greater real world applicability. In the second part we present a single product inventory model subject to nonstationary demand. We develop exact, as well as approximate performance measures, for this system and develop a relevant optimization problem. Many firms face environments where the underlying demand is non-stationary and there is little visibility of this non-stationary nature. In Teradyne’s case this is possibly the most critical problem. We believe that our research provides some insight into the viability of a model that we implemented at Teradyne and permits us to fine-tune the model for greater benefit. From our work we are able to assess the role of intermediate-decoupling inventories in non-stationary demand environments. We believe that our model could also serve as a decision support tool in configuring finished goods inventories as well as intermediate-decoupling inventories in practice. In the third part we present a robust, computationally efficient methodology to determine the base stocks for components in assemble-to-order environments. This is a rather generic problem faced by many firms within the high technology sector. We present a computationally efficient procedure that outperforms an equal-allocation-policy as well as other heuristic policies that are often used in practice. To this end we believe that our work has significant practical implications.