{"title":"Intelligent Cyber-Physical Monitoring and Control of I4.0 Machining Systems - An Overview and Future Perspectives","authors":"Mahmoud Hassan, Ahmad Sadek, M. Attia","doi":"10.36897/jme/147157","DOIUrl":null,"url":null,"abstract":"Rapid evolution in sensing, data analysis, and industrial internet of things technologies had enabled the manufacturing of advanced smart tooling. This has been fused with effective digital inter-connectivity and integrated process control intelligence to form the industry I4.0 platform. This keynote paper presents the recent advances in smart tooling and intelligent control techniques for machining processes. Self-powered wireless sensing nodes have been utilized for non-intrusive measurement of process-born phenomena near the cutting zone, as well as tool wear and tool failure, to increase confidence in the process and tool condition monitoring accuracy. Cyber-physical adaptive control approaches have been developed to optimize the cycle time and cost while eliminating machined part defects. Novel artificial intelligence AI-based signal processing and modeling approaches were developed to guarantee the generalization and practicality of these systems. The paper concludes with the outlook for future work needed for seamless implementation of these developments in industry.","PeriodicalId":37821,"journal":{"name":"Journal of Machine Engineering","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Machine Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36897/jme/147157","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: 1
Abstract
Rapid evolution in sensing, data analysis, and industrial internet of things technologies had enabled the manufacturing of advanced smart tooling. This has been fused with effective digital inter-connectivity and integrated process control intelligence to form the industry I4.0 platform. This keynote paper presents the recent advances in smart tooling and intelligent control techniques for machining processes. Self-powered wireless sensing nodes have been utilized for non-intrusive measurement of process-born phenomena near the cutting zone, as well as tool wear and tool failure, to increase confidence in the process and tool condition monitoring accuracy. Cyber-physical adaptive control approaches have been developed to optimize the cycle time and cost while eliminating machined part defects. Novel artificial intelligence AI-based signal processing and modeling approaches were developed to guarantee the generalization and practicality of these systems. The paper concludes with the outlook for future work needed for seamless implementation of these developments in industry.
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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