Name
Abstract | ||
|---|---|---|
A worker's energy level, mood, skill level can affect her/his working performance. These factors can be regarded as the “state” of the worker and they affect the production. Also, these factors are affected by the management. In this way, the management affects the production. One important task of managing a factory is keeping the production in a high level and in a safe condition via improving the management. However, in the literature usually this is done in an exogenous way, that is, a survey is given and based on the survey result the management is improved. This paper provides a first step for “optimizing” the management in an endogenous and analytical way. We propose a framework based on which we can analyze how the management affects the state of the worker and then affects the production. The basic idea is that we regard the management as a control policy to control the state of a worker to make the worker-position fitness as good as possible. We admit that it is difficult to evaluate how the management affects the worker's state as this problem is closely related to the uncertainty rooted in the human-being. To attack this difficulty, we introduce the fuzzy method to model how the management affects a worker's state. By the method in this paper, reasonable results can be obtained, based on which the management can be improved. In the future, it may be possible to collect real data to improve the method in this paper. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/SOLI.2010.5551615 | Service Operations and Logistics and Informatics |
Keywords | DocType | Volume |
fuzzy set theory,production management,worker skill level,industrial psychology,employee welfare,worker state,worker mood level,worker-position fitness,worker energy level,fuzzy model,energy levels | Conference | null |
Issue | ISSN | ISBN |
null | null | 978-1-4244-7118-8 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhen Shen | 1 | 6 | 5.53 |
| Fei-Yue Wang | 2 | 5273 | 480.21 |
| Changjian Cheng | 3 | 42 | 7.01 |
| Wei N. Zhong | 4 | 0 | 0.34 |