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A Case Study Initiating Discrete Event Simulation as a Tool for Decision Making in I4.0 Manufacturing

机译:案例研究启动离散事件模拟作为I4.0制造中决策的工具

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Smart manufacturing needs to handle increased uncertainty by becoming more responsive and more flexible to reconfigure. Advances in technology within industry 4.0 can provide acquisition of large amounts of data, to support decision making in manufacturing. Those possibilities have brought anew attention to the applicability of discrete event simulation for production flow modelling when moving towards design of logistics systems 4.0. This paper reports a study investigating challenges and opportunities for initiation of discrete event simulation, as a tool for decision making in the era of industry 4.0 manufacturing. The research has been approached through action research in combination with a real case study at a manufacturing company in the energy sector. The Covid-19 pandemic fated that adjusted and new ways of communication, collaboration, and data collection, in relation to the methods, had to be explored and tried. Throughout the study, production data, such as processing times, have been collected and analyzed for discrete event simulation modelling. The complexity of introducing discrete event simulation as a new tool for decision making is highlighted, where we emphasize the human knowledge and involvement yet necessary to understand and to draw conclusions from the data. The results also demonstrate that the data analysis has given valuable insights into production characteristics, that need addressing. Thus, revealing opportunities for how the initiative of introducing discrete event simulation as an anew tool in the wake of industry 4.0, can act as a catalyst for improved decision making in future manufacturing.
机译:智能制造需要通过变得更响应和更灵活地进行更高的不确定性来处理增加的不确定性。行业内的技术进步4.0可以提供较大量数据的收购,以支持制造业的决策。这些可能性提请重新注意在朝着物流系统设计的设计时对生产流动建模的离散事件模拟的适用性。本文报告了研究调查挑战和离散事件仿真的机会,作为行业时代的决策工具4.0制造业的制作。该研究已经通过行动研究与能源部门制造公司的实际研究相结合。 Covid-19大流行涉及调整和新的通信方式,协作和数据收集,必须探索和尝试。在整个研究中,已经收集和分析了用于离散事件仿真建模的生产数据,例如加工时间。将离散事件仿真引入的复杂性作为决策制定的新工具,在那里我们强调人类的知识和参与但是必须了解和从数据中得出结论。结果还表明,数据分析对生产特征提供了有价值的见解,需要解决。因此,揭示了如何在工业4.0之后将离散事件模拟引入作为一种重组工具的主动的机会,可以作为改善未来制造业的改进决策的催化剂。

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