讲座人介绍:
Professor in the Department of Operations, University of Groningen. Editor of European Journal of Operational Research.
讲座内容:
Abstract: Problem Definition: Many production systems deteriorate over time as a result of load and stress caused by production. The deterioration rate of these systems typically depends on the production rate, implying that the equipment’s deterioration rate can be controlled by adjusting the production rate. We introduce the use of condition monitoring to dynamically adjust the production rate to minimize maintenance costs and maximize production revenues. We study a single-unit system for which the next maintenance action is scheduled upfront. Academic/Practical Relevance: Condition-based maintenance decisions are frequently seen in the literature. However, in many real-life systems, maintenance planning has limited flexibility and cannot be done last minute. As an alternative, we are the first to propose using condition information to optimize the production rate, which is a more flexible short-term decision. Methodology: We derive structural optimality results from the analysis of deterministic deterioration processes. A Markov decision process formulation of the problem is used to obtain numerical results for stochastic deterioration processes. Results:The structure of the optimal policy strongly depends on the (convex or concave) relation between the production rate and the corresponding deterioration rate. Condition-based production rate decisions result in significant cost savings (by up to 50%), achieved by better balancing the failure risk and production output. For several systems a win-win scenario is observed, with both reduced failure risk and increased expected total production. Furthermore, condition-based production rates increase robustness and lead to more stable profits and production output. Managerial Implications: Using condition information to dynamically adjust production rates provides opportunities to improve the operational performance of systems with production-dependent deterioration.
注意:
1.网上预约所要求填写的学号与姓名均为必填项,且须与本人一卡通完全一致,否则会导致最终预约不成功。
2.讲座开始前工作人员收一卡通记次数,讲座结束后归还。预约而未听讲座、讲座迟到早退者均倒扣一次,未预约而去听讲座不计次数。
3.学院学生均使用学校mis账号及密码进行登录报名,校内学生使用校外注册账号进行报名,将视为校友或者其他校外人员,并不予进行统计前沿讲座次数。
2019/10/10
09:33
2019/10/10
09:02
2019/10/10
09:02
2019/10/10
08:57
2019/10/06
14:59
2019/10/06
14:28
2019/10/06
13:18
2019/10/06
08:55
2019/10/06
08:55
2019/10/06
08:54
2019/10/06
08:51
2019/10/06
08:47
2019/10/06
08:47
2019/10/06
08:44
2019/10/06
08:41
2019/10/06
08:34
2019/10/06
08:34
2019/10/06
08:34
2019/10/06
08:31
2019/10/06
08:30
2019/10/06
08:30
2019/10/06
08:27
2019/10/06
08:27
2019/10/06
08:21
2019/10/06
08:19
2019/10/06
08:19
2019/10/06
08:15
2019/10/06
08:13
2019/10/06
08:13
2019/10/06
08:12
2019/10/06
08:12
2019/10/06
08:11
2019/10/06
08:10
2019/10/06
08:10
2019/10/06
08:10