The value-chain encompasses the entire value creation process, which transforms material and information into product that satisfies customers' needs. Value-chains across all industries are currently being revised and re-engineered. This grant provides funding to take a closer look at the types of changes occurring in the value-chain, to analyze their relative importance, and to suggest successful methods for managing these changes. In particular, it provides funding for three specific aspects of the value-chain: vendor-managed and vendor-owned inventory systems; coordination in batch processing environments; and rationing in the value-chain. This grant also provides funding for: (1) course and curriculum development to bring manufacturing issues into the classroom; (2) increasing active learning in the classroom; (3) case study development; (4) programs to promote student mentoring; and (5) programs to promote student involvement in research. Key to this research is interaction with real companies. Working closely with industry will help to yield results that are practical and implementable. Vendor-managed and vendor-owned inventory contracts are becoming increasingly common in industry; effective modeling will help them to be used efficiently and appropriately. A comprehensive theory for coordinating batch production systems could save money both in production dollars spent and through improved supplier performance. An assessment of the impact of rationing policies on the customer base has direct implications to the viability of retailers in the US. If successful, the results of this research will have significant academic contributions in the areas of queueing theory and stochastic scheduling. The curriculum content and case studies mentioned above for courses on manufacturing systems and stochastic processes will be based on the research areas funded by this grant. This will foster a synergy between the historically disparate educational and research components of academia. Furthermore, courses on manufacturing systems and stochastic processes promote student interest in manufacturing and give students the analytic tools required to analyze such systems; hence, these courses strengthen the pool of talent devoted to improving this country is manufacturing base.
