F. Corradini, Sara Pettinari, B. Re, Lorenzo Rossi, F. Tiezzi
{"title":"可执行数字过程双胞胎:迈向过程驱动系统的增强","authors":"F. Corradini, Sara Pettinari, B. Re, Lorenzo Rossi, F. Tiezzi","doi":"10.3390/bdcc7030139","DOIUrl":null,"url":null,"abstract":"The development of process-driven systems and the advancements in digital twins have led to the birth of new ways of monitoring and analyzing systems, i.e., digital process twins. Specifically, a digital process twin can allow the monitoring of system behavior and the analysis of the execution status to improve the whole system. However, the concept of the digital process twin is still theoretical, and process-driven systems cannot really benefit from them. In this regard, this work discusses how to effectively exploit a digital process twin and proposes an implementation that combines the monitoring, refinement, and enactment of system behavior. We demonstrated the proposed solution in a multi-robot scenario.","PeriodicalId":36397,"journal":{"name":"Big Data and Cognitive Computing","volume":" ","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Executable Digital Process Twins: Towards the Enhancement of Process-Driven Systems\",\"authors\":\"F. Corradini, Sara Pettinari, B. Re, Lorenzo Rossi, F. Tiezzi\",\"doi\":\"10.3390/bdcc7030139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of process-driven systems and the advancements in digital twins have led to the birth of new ways of monitoring and analyzing systems, i.e., digital process twins. Specifically, a digital process twin can allow the monitoring of system behavior and the analysis of the execution status to improve the whole system. However, the concept of the digital process twin is still theoretical, and process-driven systems cannot really benefit from them. In this regard, this work discusses how to effectively exploit a digital process twin and proposes an implementation that combines the monitoring, refinement, and enactment of system behavior. We demonstrated the proposed solution in a multi-robot scenario.\",\"PeriodicalId\":36397,\"journal\":{\"name\":\"Big Data and Cognitive Computing\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-08-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Big Data and Cognitive Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/bdcc7030139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Data and Cognitive Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/bdcc7030139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Executable Digital Process Twins: Towards the Enhancement of Process-Driven Systems
The development of process-driven systems and the advancements in digital twins have led to the birth of new ways of monitoring and analyzing systems, i.e., digital process twins. Specifically, a digital process twin can allow the monitoring of system behavior and the analysis of the execution status to improve the whole system. However, the concept of the digital process twin is still theoretical, and process-driven systems cannot really benefit from them. In this regard, this work discusses how to effectively exploit a digital process twin and proposes an implementation that combines the monitoring, refinement, and enactment of system behavior. We demonstrated the proposed solution in a multi-robot scenario.