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تعداد صفحات این فایل: ۲۵ صفحه

بخشی از مقاله انگلیسیعنوان انگلیسی:Forming effective worker teams for cellular manufacturing~~en~~

Cellular manufacturing has been extensively adopted as a measure to reduce cycle time, increase productivity, and improve product quality. The past research in cellular manufacturing has focused on the methodology for identi®cation of machine groups, part families, and determination of processing routes. The relocation of existing workers into cells and their training for a team-oriented, cellular manufacturing environment have largely been ignored. In this research, a mixed integer, goal programming model is formulated for guiding the worker assignment and training process to create worker teams with high team synergy and individual job ®tness meeting cell requirements for technical and administrative skills. The model integrates psychological, organizational, and technical factors. Several solution methods including greedy heuristic, ®ltered beam search, and simulated annealing techniques are developed and tested. It appears that heuristics such as beam search are capable of obtaining good solutions with reasonable computational eŒort.

۶- Conclusions

We formulated a detailed worker assignment and training (WAT) model for formation of worker teams in cellular manufacturing. The procedures allow an existing functional organization to be converted to cells so as nearly to maximize team synergy and the ®t between worker abilities/instincts and task requirements while minimizing training cost. The model supports the design of manufacturing cells to meet the operational requirements created by external demand, while establishing a cohesive and cooperative working environment, and individual job satisfaction. The model output locates workers into cells and details the task assignments for each worker.

Owing to the computational complexity of model WAT, solving the model opti- mally is not feasible for large problems. We developed a greedy heuristic and greedy- heuristic based ®ltered beam search algorithm. The algorithms were tested over a range of parameter combinations. Additional tests with simulated annealing were performed for certain di cult cases. The results indicate that the ®ltered beam search may be an eŒective solution approach, preferable to straightforward optimization or possibly simulated annealing when computational time and memory are limited.

This research provides a usable methodology for manufacturing managers to allocate workers and tasks into cells and for human resource managers to improve their return on training investment. Future research plans include determining additional factors beyond synergy that can reliably predict team performance and inclu- sion of these in the model.

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