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Exploring the benefits of scheduling with advanced and real-time information integration in Industry 4.0: A computational study
Journal of Industrial Information Integration ( IF 15.7 ) Pub Date : 2021-09-01 , DOI: 10.1016/j.jii.2021.100281
Victor Fernandez-Viagas 1 , Jose M. Framinan 1, 2
Affiliation  

The technological advances recently brought to the manufacturing arena (collectively known as Industry 4.0) offer huge possibilities to improve decision-making processes in the shop floor by enabling the integration of information in real-time. Among these processes, scheduling is often cited as one of the main beneficiaries, given its data-intensive and dynamic nature. However, in view of the extremely high implementation costs of Industry 4.0, these potential benefits should be properly assessed, also taking into account that there are different approaches and solution procedures that can be employed in the scheduling decision-making process, as well as several information sources (i.e. not only shop floor status data, but also data from upstream/downstream processes).

In this paper, we model various decision-making scenarios in a shop floor with different degrees of uncertainty and diverse efficiency measures, and carry out a computational experience to assess how real-time and advance information can be advantageously integrated in the Industry 4.0 context. The extensive computational experiments (equivalent to 6.3 years of CPU time) show that the benefits of using real-time, integrated shop floor data and advance information heavily depend on the proper choice of both the scheduling approach and the solution procedures, and that there are scenarios where this usage is even counterproductive. The results of the paper provide some starting points for future research regarding the design of approaches and solution procedures that allow fully exploiting the technological advances of Industry 4.0 for decision-making in scheduling.



中文翻译:

探索工业 4.0 中高级实时信息集成的调度优势:一项计算研究

最近为制造领域带来的技术进步(统称为工业 4.0)通过实时集成信息为改进车间决策流程提供了巨大的可能性。在这些过程中,调度通常被认为是主要的受益者之一,因为它是数据密集型和动态的。然而,鉴于工业 4.0 的实施成本极高,应适当评估这些潜在的好处,同时考虑到在调度决策过程中可以采用不同的方法和解决程序,以及几个信息源(即不仅是车间状态数据,还有来自上游/下游过程的数据)。

在本文中,我们对具有不同程度不确定性和不同效率措施的车间中的各种决策场景进行建模,并进行计算经验以评估如何在工业 4.0 环境中有利地集成实时和提前信息。大量的计算实验(相当于 6.3 年的 CPU 时间)表明,使用实时、集成的车间数据和提前信息的好处在很大程度上取决于对调度方法和求解程序的正确选择,并且有这种用法甚至适得其反的场景。该论文的结果为未来有关方法和解决方案设计的研究提供了一些起点,以充分利用工业 4 的技术进步。

更新日期:2021-09-01
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