Open Access. Powered by Scholars. Published by Universities.®
Operations and Supply Chain Management Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
Articles 1 - 2 of 2
Full-Text Articles in Operations and Supply Chain Management
Flexibility: The Next Competitive Battle: The Manufacturing Futures Survey, Arnoud De Meyer, Jinichiro Nakane, Jeffrey M. Miller, Kasra Ferdows
Flexibility: The Next Competitive Battle: The Manufacturing Futures Survey, Arnoud De Meyer, Jinichiro Nakane, Jeffrey M. Miller, Kasra Ferdows
Research Collection Lee Kong Chian School Of Business
Over the past 4 years research teams from INSEAD (Fontainebleau), Boston University and Waseda University (Tokyo) have administered a yearly survey on the manufacturing strategy of the large manufacturers of the three industrialized regions of the world. In this paper the results for the 1986 survey are compared. One of the most striking results of that year’s survey is the emphasis some of the more advanced manufacturers put on their efforts to overcome the trade-off between flexibility and cost efficiency. In particular for the Japanese respondents these attempts become clear. Europeans and North Americans are not yet seizing the opportunity …
Enhancing Manufacturing Planning And Control Systems Through Artificial Intelligence Techniques, Ronald S. Dattero, John J. Kanet, Edna M. White
Enhancing Manufacturing Planning And Control Systems Through Artificial Intelligence Techniques, Ronald S. Dattero, John J. Kanet, Edna M. White
MIS/OM/DS Faculty Publications
Manufacturing planning and control systems are currently dominated by systems based upon Material Requirements Planning (MRP). MRP systems have a number of fundamental flaws. A potential alternative to MRP systems is suggested after research into the economic batch scheduling problem.
Based on the ideas of economic batch scheduling, and enhanced through artificial intelligence techniques, an alternative approach to manufacturing planning and control is developed. A framework for future research on this alternative to MRP is presented.