{"title":"On blockchain technology and machine learning algorithms in concurrent engineering","authors":"K. Vijayakumar","doi":"10.1177/1063293X221136215","DOIUrl":null,"url":null,"abstract":"The available computational facilities in recent years have helped engineers to develop new applications in the realworld problems, implement automation to reduce the complexity and improve productivity of the existing systems. The modern technologies such as remote monitoring, artificial intelligence, machine learning procedures, industrial and production automation, sustainable engineering and block chain techniques are commonly employed in concurrent engineering applications to enhance the product development/monitoring and speed-up the production capabilities. The employment of such computational facilities and modern technologies have helped companies in improving the overall performance in various sectors including, financial, medical, consumer, manufacturing, product design and implementation, manufacturing sector improvement and task scheduling applications. The main focus of this issue is to collect the cutting-edge research articles related to block chain, machine learning and other advanced virtual methods to promote concurrent engineering application in a variety of applicable domains. This issue collected the research works from different domains of the authors based on the theme of the issue. A summary of these collected articles is presented below;","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"66 1","pages":"315 - 316"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrent Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/1063293X221136215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The available computational facilities in recent years have helped engineers to develop new applications in the realworld problems, implement automation to reduce the complexity and improve productivity of the existing systems. The modern technologies such as remote monitoring, artificial intelligence, machine learning procedures, industrial and production automation, sustainable engineering and block chain techniques are commonly employed in concurrent engineering applications to enhance the product development/monitoring and speed-up the production capabilities. The employment of such computational facilities and modern technologies have helped companies in improving the overall performance in various sectors including, financial, medical, consumer, manufacturing, product design and implementation, manufacturing sector improvement and task scheduling applications. The main focus of this issue is to collect the cutting-edge research articles related to block chain, machine learning and other advanced virtual methods to promote concurrent engineering application in a variety of applicable domains. This issue collected the research works from different domains of the authors based on the theme of the issue. A summary of these collected articles is presented below;