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Energy Efficiency in Industry 4.0: The Case of Batch Production Processes

doi: 10.3390/su12166631
handle: 11386/4749987
Energy Efficiency in Industry 4.0: The Case of Batch Production Processes
We derived a promising approach to reducing the energy consumption necessary in manufacturing processes from the combination of management methodologies and Industry 4.0 technologies. Based on a literature review and experts’ opinions, this work contributes to the efficient use of energy in batch production processes combining the analysis of the overall equipment effectiveness with the study of variables managed by cyber-physical production systems. Starting from the analysis of loss cause identification, we propose a method that obtains quantitative data about energy losses during the execution of batch processes. The contributions of this research include the acquisition of precise information about energy losses and the improvement of value co-creation practices so that energy consumption can be reduced in manufacturing processes. Decision-makers can use the findings to start a virtuous process aiming at carbon footprint and energy costs reductions while ensuring production goals are met.
energy efficiency; multi-disciplinary analysis; sustainable value co-creation; industry 4.0, Environmental effects of industries and plants, sustainable value co-creation, multi-disciplinary analysis, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, industry 4.0, energy efficiency
energy efficiency; multi-disciplinary analysis; sustainable value co-creation; industry 4.0, Environmental effects of industries and plants, sustainable value co-creation, multi-disciplinary analysis, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, GE1-350, industry 4.0, energy efficiency
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).41 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
