当前位置: X-MOL 学术Comput. Oper. Res. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Real-time production scheduling in the Industry-4.0 context: Addressing uncertainties in job arrivals and machines breakdowns
Computers & Operations Research ( IF 4.1 ) Pub Date : 2020-11-01 , DOI: 10.1016/j.cor.2020.105031
Mageed Ghaleb , Hossein Zolfagharinia , Sharareh Taghipour

Abstract The utilization of real-time information in production scheduling decisions becomes possible with the help of new developments in Information Technology and Industrial Informatics, such as Industry 4.0. Regardless of the beliefs that the availability of such information will enhance scheduling decisions, several questions and concerns have been reported. One such question is to what extent can the availability of real-time information enhance scheduling decisions? Another concern is how can such information be utilized to advance scheduling decisions and when should it be used? Moreover, there is a general assumption that continuous rescheduling using real-time system updates is beneficial to some extent. However, this general assumption has not been extensively investigated in complex manufacturing systems, such as flexible job shops. Therefore, in this paper, our objective is to study the above-mentioned research questions by developing real-time scheduling (RTS) models for the flexible job-shop scheduling problem (FJSP) with unexpected new job arrivals and machine random breakdowns. We investigate how real-time updates on unexpected arrivals, the availability of machines (downtimes and recovery times), and the completion times of operations can be utilized to generate new schedules (i.e., rescheduling). The performance of the developed RTS models is also investigated under different settings for shop-floor events, different rescheduling strategies, rescheduling policies, and scheduling methods. Lastly, results, conclusions, and several promising research avenues are provided.

中文翻译:

工业 4.0 背景下的实时生产调度:解决工作到达和机器故障的不确定性

摘要 借助信息技术和工业信息学的新发展,例如工业 4.0,在生产调度决策中利用实时信息成为可能。尽管相信此类信息的可用性将增强调度决策,但已经报告了一些问题和担忧。一个这样的问题是实时信息的可用性可以在多大程度上增强调度决策?另一个问题是如何利用这些信息来推进调度决策以及何时使用?此外,有一个普遍假设,即使用实时系统更新进行连续重新调度在某种程度上是有益的。然而,这种一般假设尚未在复杂的制造系统中得到广泛研究,例如灵活的加工车间。因此,在本文中,我们的目标是通过为具有意外新作业到达和机器随机故障的灵活作业车间调度问题 (FJSP) 开发实时调度 (RTS) 模型来研究上述研究问题。我们研究了如何利用意外到达的实时更新、机器的可用性(停机时间和恢复时间)以及操作的完成时间来生成新的调度(即重新调度)。在不同的车间事件设置、不同的重新调度策略、重新调度策略和调度方法下,还研究了开发的 RTS 模型的性能。最后,提供了结果、结论和几个有希望的研究途径。我们的目标是通过为具有意外新作业到达和机器随机故障的灵活作业车间调度问题 (FJSP) 开发实时调度 (RTS) 模型来研究上述研究问题。我们研究了如何利用意外到达的实时更新、机器的可用性(停机时间和恢复时间)以及操作的完成时间来生成新的调度(即重新调度)。在不同的车间事件设置、不同的重新调度策略、重新调度策略和调度方法下,还研究了开发的 RTS 模型的性能。最后,提供了结果、结论和几个有希望的研究途径。我们的目标是通过为具有意外新作业到达和机器随机故障的灵活作业车间调度问题 (FJSP) 开发实时调度 (RTS) 模型来研究上述研究问题。我们研究了如何利用意外到达的实时更新、机器的可用性(停机时间和恢复时间)以及操作的完成时间来生成新的调度(即重新调度)。在不同的车间事件设置、不同的重新调度策略、重新调度策略和调度方法下,还研究了开发的 RTS 模型的性能。最后,提供了结果、结论和几个有希望的研究途径。
更新日期:2020-11-01
down
wechat
bug