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首页> 外文期刊>International Journal of Production Research >Assessing the performances of a novel decentralised scheduling approach in Industry 4.0 and cloud manufacturing contexts
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Assessing the performances of a novel decentralised scheduling approach in Industry 4.0 and cloud manufacturing contexts

机译：评估工业4.0和云制造背景下的新型分散调度方法的表演

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摘要

The increasing globalisation process has led to a radical change in the production concept, moving from a mass production paradigm towards one of mass customisation (MC), and focusing on value creation by pursuing customers' needs and increasing responsiveness. The rapid development of information technologies has also made it possible to create new manufacturing paradigms, such as Industry 4.0 and cloud manufacturing, in which the increased level of autonomy is one of the key concepts for tackling new market challenges. This paper proposes a decentralised scheduling approach that improves the performance of production systems while minimising the usually high work-in-progress (WIP) requirements of the classic centralised scheduling and inventory production control system. Using a semi-heterarchical Manufacturing Planning and Control (MPC) architecture and integrating the Industry 4.0 innovation in a cloud manufacturing environment, this work contributes to the design of the lower level of the MPC architecture. The resulting production controller can allocate jobs following different dispatching rules dynamically. The performances of the proposed approach were assessed for different production scenarios and control parameter settings through an exhaustive experimental campaign based on hybrid simulation tools. The results showed that the proposed low-level controller led to a productivity increase while delivering increased responsiveness.
机译：越来越多的全球化过程导致了生产概念的根本变化，从大规模生产范式转向大规模定制（MC），并通过追求客户的需求和越来越高的响应性来关注价值创造。信息技术的快速发展也使得可以创建新的制造范式，如行业4.0和云制造，其中自主程度增加是解决新市场挑战的关键概念之一。本文提出了一种分散的调度方法，可以提高生产系统的性能，同时最大限度地减少经典集中调度和库存生产控制系统的通常高工作量（WIP）要求。使用半同制造规划和控制（MPC）架构并集成了云制造环境中的行业4.0创新，这项工作有助于设计MPC架构的较低级别。由此产生的生产控制器可以动态分配不同调度规则。通过基于混合仿真工具的详尽实验活动，对不同生产方案和控制参数设置进行评估的表现。结果表明，所提出的低级控制器导致生产力增加，同时提供增加的响应性。

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