|Industrial and Systems Engineering
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Manufacturing complex products in order to survive the competition in the automotive electronics industry requires high volume manufacturing combined with high levels of quality and automation at a very low cost. All of the above require carefully engineered logistics, effective material handling, material identification and tracking at individual component levels, irreversible equipment and tooling investment, and dedicated floor space. Since electronics manufacturing facilities also require specific facility systems, floor space becomes an extremely valuable asset. Effective utilization of this valuable asset results in competitive advantages where the embedded flexibility to manage the capacity to generate more revenue or more cost savings significantly contributes to the profitability of enterprises. Considering the business volume generated by the automotive industry, the primary goal of this research is to formally investigate the contribution of effective floor space valuation to strategic decision making in automotive electronics manufacturing industry. Thus it is intended to describe a conceptual framework by developing a method to evaluate the value of the additional floor space generated by manufacturing logistics investments. The scope of this research is limited to plant level capital investment decisions of a global publicly held high-volume high-mix automotive electronics manufacturer, where the facility in question is located in the United States of America. The specific focus of this research is the valuation of the additional floor space generated by automated capital equipment replacement for the logistics department of Continental Automotive Systems, Inc. Huntsville facility. The aforementioned equipment is fully depreciated, outdated, and causing extreme downtime, thus interrupting the manufacturing operations. Several decision alternatives are analyzed and a floor space valuation method utilizing traditional discounted cash flow techniques, decision tree analysis, and real options analysis is developed. The results of the conceptual framework are discussed in order to provide better understanding for the implications of the model, and an outline for future research opportunities is discussed.