{"title":"Towards Sustainable and Intelligent Machining: Energy Footprint and Tool Condition Monitoring for Media-Assisted Processes","authors":"H. Dogan, Llyr Jones, S. Hall, A. Shokrani","doi":"10.36897/jme/166463","DOIUrl":null,"url":null,"abstract":"Reducing energy consumption is a necessity towards achieving the goal of net-zero manufacturing. In this paper, the overall energy footprint of machining Ti-6Al-4V using various cooling/lubrication methods is investigated taking the embodied energy of cutting tools and cutting fluids into account. Previous studies concentrated on reducing the energy consumption associated with the machine tool and cutting fluids. However, the investigations in this study show the significance of the embodied energy of cutting tool. New cooling/lubrication methods such as WS 2 -oil suspension can reduce the energy footprint of machining through extending tool life. Cutting tools are commonly replaced early before reaching their end of useful life to prevent damage to the workpiece, effectively wasting a portion of the embodied energy in cutting tools. A deep learning method is trained and validated to identify when a tool change is required based on sensor signals from a wireless sensory toolholder. The results indicated that the network is capable of classifying over 90% of the tools correctly. This enables capitalising on the entirety of a tool’s useful life before replacing the tool and thus reducing the overall energy footprint of machining processes","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Machine Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36897/jme/166463","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0
Abstract
Reducing energy consumption is a necessity towards achieving the goal of net-zero manufacturing. In this paper, the overall energy footprint of machining Ti-6Al-4V using various cooling/lubrication methods is investigated taking the embodied energy of cutting tools and cutting fluids into account. Previous studies concentrated on reducing the energy consumption associated with the machine tool and cutting fluids. However, the investigations in this study show the significance of the embodied energy of cutting tool. New cooling/lubrication methods such as WS 2 -oil suspension can reduce the energy footprint of machining through extending tool life. Cutting tools are commonly replaced early before reaching their end of useful life to prevent damage to the workpiece, effectively wasting a portion of the embodied energy in cutting tools. A deep learning method is trained and validated to identify when a tool change is required based on sensor signals from a wireless sensory toolholder. The results indicated that the network is capable of classifying over 90% of the tools correctly. This enables capitalising on the entirety of a tool’s useful life before replacing the tool and thus reducing the overall energy footprint of machining processes
期刊介绍：
ournal of Machine Engineering is a scientific journal devoted to current issues of design and manufacturing - aided by innovative computer techniques and state-of-the-art computer systems - of products which meet the demands of the current global market. It favours solutions harmonizing with the up-to-date manufacturing strategies, the quality requirements and the needs of design, planning, scheduling and production process management. The Journal'' s subject matter also covers the design and operation of high efficient, precision, process machines. The Journal is a continuator of Machine Engineering Publisher for five years. The Journal appears quarterly, with a circulation of 100 copies, with each issue devoted entirely to a different topic. The papers are carefully selected and reviewed by distinguished world famous scientists and practitioners. The authors of the publications are eminent specialists from all over the world and Poland. Journal of Machine Engineering provides the best assistance to factories and universities. It enables factories to solve their difficult problems and manufacture good products at a low cost and fast rate. It enables educators to update their teaching and scientists to deepen their knowledge and pursue their research in the right direction.
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