An Adaptive Scheduling Method Based on Cloud Technology: A Structural Steelwork Industry Case Study (original) (raw)
2020
Decision making at the shop floor level has become more complex than ever before due to the massive growth in available data. The increasing market demands, concerning product quality and delivery times, make critical judgement and decision-making crucial requirements of the modern manufacturing problems. Human decision making has become insufficient and struggles to achieve manufacturing goals. Cutting edge technologies like the Internet of Things (IoT) and Cyber Physical Systems (CPS), that are the cornerstones of the Industry 4.0 smart factories, can contribute to efficient decision making. Therefore, more accurate and improved critical decisions can be achieved for the current as well as for the future status of a manufacturing system. Furthermore, production scheduling is one of the main issues that engineers have to address. The decision support tools of the Industry 4.0 era contribute to effective production scheduling, while considering a larger amount of data and constraints than ever before. This research work proposes a production scheduling method, that uses past and near real-time data to check resource and task status, providing insight to production engineers and enabling enhanced decision making. The results are validated in a structural steelwork industry shop case study.
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