{"title":"工业4.0时代的制造业质量评价综述","authors":"N. Markatos, Alireza Mousavi","doi":"10.1080/14783363.2023.2194524","DOIUrl":null,"url":null,"abstract":"Maintaining high-quality standards has consistently been the main goal of industries. With rising demand and customisation, industries must strike a balance between cost, manufacturing time, and quality. The technological advancements of Industry 4.0 have allowed the implementation of accurate quality prediction frameworks in the manufacturing lines. For quality prediction in manufacturing, machine learning, and artificial intelligence offer several benefits, but there are also a number of limitations that must be taken into consideration. The current study aims to highlight the aforementioned benefits and drawbacks. To do this, a literature review on the area of quality prediction and monitoring in Industry 4.0 manufacturing lines is conducted. The results demonstrate that the merits of the reviewed methods are many but six significant drawbacks must be accounted for the successful implementation of the studied quality prediction frameworks. The current study can serve as a ‘map’ for production managers in industries as well as experts in the field of manufacturing as they weigh the benefits and drawbacks of popular quality prediction models, as it provides information needed to determine to what extent these methods can be applied to new or existing manufacturing lines.","PeriodicalId":23149,"journal":{"name":"Total Quality Management & Business Excellence","volume":null,"pages":null},"PeriodicalIF":3.6000,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Manufacturing quality assessment in the industry 4.0 era: a review\",\"authors\":\"N. Markatos, Alireza Mousavi\",\"doi\":\"10.1080/14783363.2023.2194524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Maintaining high-quality standards has consistently been the main goal of industries. With rising demand and customisation, industries must strike a balance between cost, manufacturing time, and quality. The technological advancements of Industry 4.0 have allowed the implementation of accurate quality prediction frameworks in the manufacturing lines. For quality prediction in manufacturing, machine learning, and artificial intelligence offer several benefits, but there are also a number of limitations that must be taken into consideration. The current study aims to highlight the aforementioned benefits and drawbacks. To do this, a literature review on the area of quality prediction and monitoring in Industry 4.0 manufacturing lines is conducted. The results demonstrate that the merits of the reviewed methods are many but six significant drawbacks must be accounted for the successful implementation of the studied quality prediction frameworks. The current study can serve as a ‘map’ for production managers in industries as well as experts in the field of manufacturing as they weigh the benefits and drawbacks of popular quality prediction models, as it provides information needed to determine to what extent these methods can be applied to new or existing manufacturing lines.\",\"PeriodicalId\":23149,\"journal\":{\"name\":\"Total Quality Management & Business Excellence\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2023-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Total Quality Management & Business Excellence\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1080/14783363.2023.2194524\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"MANAGEMENT\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Total Quality Management & Business Excellence","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1080/14783363.2023.2194524","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MANAGEMENT","Score":null,"Total":0}
Manufacturing quality assessment in the industry 4.0 era: a review
Maintaining high-quality standards has consistently been the main goal of industries. With rising demand and customisation, industries must strike a balance between cost, manufacturing time, and quality. The technological advancements of Industry 4.0 have allowed the implementation of accurate quality prediction frameworks in the manufacturing lines. For quality prediction in manufacturing, machine learning, and artificial intelligence offer several benefits, but there are also a number of limitations that must be taken into consideration. The current study aims to highlight the aforementioned benefits and drawbacks. To do this, a literature review on the area of quality prediction and monitoring in Industry 4.0 manufacturing lines is conducted. The results demonstrate that the merits of the reviewed methods are many but six significant drawbacks must be accounted for the successful implementation of the studied quality prediction frameworks. The current study can serve as a ‘map’ for production managers in industries as well as experts in the field of manufacturing as they weigh the benefits and drawbacks of popular quality prediction models, as it provides information needed to determine to what extent these methods can be applied to new or existing manufacturing lines.
期刊介绍:
Total Quality Management & Business Excellence is an international journal which sets out to stimulate thought and research in all aspects of total quality management and to provide a natural forum for discussion and dissemination of research results. The journal is designed to encourage interest in all matters relating to total quality management and is intended to appeal to both the academic and professional community working in this area. Total Quality Management & Business Excellence is the culture of an organization committed to customer satisfaction through continuous improvement. This culture varies both from one country to another and between different industries, but has certain essential principles which can be implemented to secure greater market share, increased profits and reduced costs. The journal provides up-to-date research, consultancy work and case studies right across the whole field including quality culture, quality strategy, quality systems, tools and techniques of total quality management and the implementation in both the manufacturing and service sectors. No topics relating to total quality management are excluded from consideration in order to develop business excellence.