Journal of Manufacturing Systems · 2019 · 157 citations · 50 references
EngineeringIndustrial EngineeringManufacturing EngineeringAutomationManufacturing ProcessesManufacturing SystemsEnergy SimulationEnergy-efficient ManufacturingManufacturing AutomationManufacturing SimulationProcess EngineeringProcess SimulationEnergy AnalysisEnergy ConsumptionManufacturingManufacturing Process SimulationManufacturing System ModelsManufacturing System SimulationProcess Energy ConsumptionProcess Energy Modeling
Manufacturing firms face pressure to cut energy use while sustaining profits, and computational modelling offers a decision‑making tool to optimize throughput, plan operations, reduce bottlenecks, and test scenarios. The study reviews energy‑analysis methodologies at the machine‑process level and emphasizes the need for a comprehensive, high‑accuracy computational model to capture material, energy, and resource interactions. The authors present a multi‑level holistic analysis using discrete‑event and continuous simulation of individual machines, process chains, and the built environment, and review Industry 4.0 technologies—including automation, connectivity, digital twins, and AR/VR—to enhance automation, flexibility, and process understanding. The study identifies challenges in creating a holistic simulation of the entire facility with all relevant parameters and outlines areas for future development.
With increasing governmental pressures to reduce energy consumption, manufacturing companies are faced with the challenge of reducing energy consumption whilst maintaining or increasing profits and productivity. Computational modelling is a powerful tool for energy analysis within the manufacturing industry as an effective decision making technique in order to optimise throughput, effectively plan and manage operations, reduce bottlenecks and test various scenarios. This study reviewed methodologies and frameworks developed for analysing energy consumption on a machine process level. Multi-level holistic analysis allowing for consideration of individual machines, the manufacturing process chain and built environment, with both discrete event and continuous based simulation are also presented. The requirement of a complete, high accuracy computational model is highlighted in order to understand the interaction between all relevant material, energy and resource flows. Challenges associated with achieving a holistic simulation of the manufacturing facility with all relevant parameters is presented, along with areas for further development. Furthermore, the development of Industry 4.0 is reviewed, along with new and emerging technologies allowing for increased automation, connectivity and flexibility within manufacturing, as well as visual techniques to provide further understanding and clarity of manufacturing processes such as digital twins, virtual and augmented reality.
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Shaping the digital twin for design and production engineering
Benjamin Schleich, Nabil Anwer, Luc Mathieu et al. · CIRP Annals · 2017 · 1.3K citations · Full text