Stackelberg Game Based Manufacturing Service Uncertainty Scheduling Toward Intelligent Manufacturing

Lingyan Li, Sicheng Liu, Lin Zhang
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Abstract

With the coming of the third industrial revolution, multiple industries have mass manufacturing needs. In order to save production costs and maximize profit, businesses in these industries hurry to improve the level of manufacturing and carry out intelligent transformation. Thus, intelligent manufacturing has become the top priority in the modern industrial system. In addition, in the intelligent manufacturing aspect, not only cost-saving problems but also unexpected events (e.g. service broken) during the manufacturing process is a crucial challenge. Therefore, it is necessary to investigate the above problem of uncertainty scheduling mechanisms in cloud manufacturing (CMfg) as one of the important representative forms of intelligent manufacturing. This paper proposes a two-layer scheduling model based on the Stackelberg game in CMfg. In this model, a triple-layer iteration algorithm is designed to get the Nash equilibrium in the game theory. Also, to better analyze and solve the uncertainty during the manufacturing process, the main service broken cases are discussed using the real-time scheduling method, and the corresponding solutions of each case are presented. The case study verifies the efficiency and necessity of the proposed scheduling method by setting automobile manufacturing as the research case.
面向智能制造的Stackelberg博弈制造服务不确定性调度
随着第三次工业革命的到来,多个行业都有大规模制造的需求。为了节约生产成本,实现利润最大化,这些行业的企业纷纷提高制造水平,进行智能化改造。因此,智能制造已成为现代工业体系的重中之重。此外,在智能制造方面,除了成本节约问题外,制造过程中的意外事件(如服务中断)也是一个至关重要的挑战。因此,作为智能制造的重要代表形式之一,有必要对云制造中的不确定性调度机制的上述问题进行研究。本文提出了一种基于Stackelberg博弈的CMfg双层调度模型。在该模型中,设计了一种三层迭代算法来获得博弈论中的纳什均衡。为了更好地分析和解决制造过程中的不确定性,采用实时调度的方法对主要的服务中断案例进行了讨论,并给出了相应的解决方案。以汽车制造业为例,验证了所提出的调度方法的有效性和必要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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