{"title":"Adaptive Management Shell for Mapping the Process Capability of Manufacturing Components: A Systematic Mapping Study","authors":"David Heik, Javad Ghofrani, Dirk Reichelt","doi":"10.1109/INDIN45582.2020.9442143","DOIUrl":null,"url":null,"abstract":"Being successful and competitive on the market means that companies have to adapt to the demands of their customers. Personalised products are increasingly becoming a matter of course for consumers, which leads to a reduction in the number of similar orders for manufacturing companies. To satisfy these requirements, new information and communication technologies are needed in industrial manufacturing. Industry 4.0 aims to address these challenges. However, many approaches are not yet implemented or mature, so there is a need for further research in this field. For this reason, a comprehensive and systematic mapping study was conducted to structure and categorize the current state of research in the field of self-describing and self-organizing manufacturing. The literature considered was published between January 2014 and May 2019. The research carried out is based on the guidelines for conducting systematic mapping studies. With regard to the technical implementation of this technology, a number of research questions are carefully defined. Based on these questions, data from different levels of information are extracted and analyzed for the considered papers. The study results show in which areas more work is required and where there are future research perspectives. Furthermore, this study can help to better understand the field of research and the research gaps identified.","PeriodicalId":185948,"journal":{"name":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 18th International Conference on Industrial Informatics (INDIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIN45582.2020.9442143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Being successful and competitive on the market means that companies have to adapt to the demands of their customers. Personalised products are increasingly becoming a matter of course for consumers, which leads to a reduction in the number of similar orders for manufacturing companies. To satisfy these requirements, new information and communication technologies are needed in industrial manufacturing. Industry 4.0 aims to address these challenges. However, many approaches are not yet implemented or mature, so there is a need for further research in this field. For this reason, a comprehensive and systematic mapping study was conducted to structure and categorize the current state of research in the field of self-describing and self-organizing manufacturing. The literature considered was published between January 2014 and May 2019. The research carried out is based on the guidelines for conducting systematic mapping studies. With regard to the technical implementation of this technology, a number of research questions are carefully defined. Based on these questions, data from different levels of information are extracted and analyzed for the considered papers. The study results show in which areas more work is required and where there are future research perspectives. Furthermore, this study can help to better understand the field of research and the research gaps identified.