Agricultural Safety and Health Training for Public Health Graduate Students

  • McKnight, Robert (PI)

Grants and Contracts Details


problem in many sectors of industry. Scheduling strategies for various shop configurations and performance criteria have been widely researched in academia. However, many companies- mostly small and medium-sized ones, estimated to be around 330,000 in the U.S. (NAP, 1999)- continue to experience difficulty in effectively scheduling jobs, for two reasons: having to face new and more challenging manufacturing environments to which existing scheduling strategies are not readily applicable and being unable to transfer academic findings into practical applications. Mass customization, which requires efficient production of iMividually customized products (or services), is an emerging strategy that can be a source of competitive advantage for many companies. However the economic benefits of the strategy are out of reach unless companies can manufacture and sell products at competitive prices with short lead times-which in turn requires effective production scheduling. Kuhlman Electric, a company engaged in the mass customization of transformers, is experiencing difficulty with effective production scheduling due to both the obstacles mentioned above: lack of research-based strategies to handle new complex manufacturing environments such as mass customization and lack of effective transfer of such academic findings (once developed) into solutions usable by industry. The overall objective of this research is to address both obstacles above through a university-industry collaborative project. We define the scheduling problem at Kuhlman Electric's plant in Versailles, KY as an associative parallel machine scheduling (APMS) problem. The APMS problem is more complex than parallel machine scheduling (PMS), which in itself has been shown to be NP-hard, research on such problems is not known. APMS problems can arise in situations when there is a high variability in products and when there are multiple machines available of the same type but with slightly different capabilities. Given the increasing demand for customized products, such APMS situations are likely to arise more frequently in industry. Researchers from the University of Kentucky and engineers from Kuhiman Electric working will work in partnership to develop methods to solve the APMS problem. We will (I) formulate the APMS situation as a mathematical programming problem and determine solution methods and (2) study the challenges to effective transferability of academic research and propose strategies to increase knowledge transfer to industry. Broader Imnacts: The findings of this project, in addition to helping Kuhlman Electric, will be of benefit to many other companies engaged in similar operations. Understanding challenges to knowledge transferability has benefits in a much broader context and puts the researchers in an even better position to assist companies that lack the resources available to their larger counterparts who are able to research, develop and implement their own scheduling methods. Mass customization, which is becoming increasingly popular and if successfully implemented can become a tactical and strategic advantage for U.S. companies over foreign manufacturers, is among the P1's major research interests. The collaboration with Kuhlman Electric will establish an excellent partnership to continue research in the area. The collaboration will also provide opportunities for hands-on manufacturing experience for students and enable them to better understand the real-life scheduling problems and how to incorporate relevant issues in developing solutions. Intellectual Merit: This work will contribute to developing new methods to solve APMS problems that arise in complex manufacturing environments such as in make-to-order! mass customization. The novel aspect of this university-industry syiiergistic project is the focus on learning and then mastering the challenges to transferability of knowledge to industry which is as important as the scheduling methods developed. We also believe the research has the
Effective start/end date7/1/066/30/10


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