{"title":"MetaFactory: A cloud-based framework to configure and generate dynamic data structures from the STEP-NC knowledge graph","authors":"Wenlei Xiao , Tianze Qiu , Jiurong Guo , Gang Zhao","doi":"10.1016/j.jmsy.2025.02.012","DOIUrl":null,"url":null,"abstract":"<div><div>In our previous studies, twin-oriented manufacturing has been identified as a crucial solution to address the manufacturing crisis. Within this context, the notion of “digital twin as a service” necessitates that various twin services share and communicate with each other in a standardized manner. STEP-NC offers a potentially unified model to facilitate data exchange, providing object-oriented and standardized data models for a comprehensive representation of manufacturing resources in the digital realm. However, the complexity of STEP-NC renders it too cumbersome for implementation in diverse cloud-based services or PC-based software. This complexity is a fundamental reason why STEP-NC has struggled to find application in commercial CNC systems despite years of research. To overcome this technical challenge, this paper introduces a novel concept termed “dynamic STEP-NC data structure”, inspired by the dynamic language philosophy of dynamic programming language (such as Python). This approach allows different services and software packages to maintain their own data definitions while still aligning with the original STEP-NC definition. We have developed a framework called MetaFactory that supports the configuration of streamlined data structures and generates the corresponding program code required by various service developers. On this basis, we implemented automatic modeling for a STEP-NC object-oriented database. Using the data trimming and dimensionality reduction methods provided by MetaFactory, several prototype systems for different application scenarios have been developed.</div></div>","PeriodicalId":16227,"journal":{"name":"Journal of Manufacturing Systems","volume":"80 ","pages":"Pages 89-107"},"PeriodicalIF":12.2000,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Systems","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0278612525000421","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
引用次数: 0
Abstract
In our previous studies, twin-oriented manufacturing has been identified as a crucial solution to address the manufacturing crisis. Within this context, the notion of “digital twin as a service” necessitates that various twin services share and communicate with each other in a standardized manner. STEP-NC offers a potentially unified model to facilitate data exchange, providing object-oriented and standardized data models for a comprehensive representation of manufacturing resources in the digital realm. However, the complexity of STEP-NC renders it too cumbersome for implementation in diverse cloud-based services or PC-based software. This complexity is a fundamental reason why STEP-NC has struggled to find application in commercial CNC systems despite years of research. To overcome this technical challenge, this paper introduces a novel concept termed “dynamic STEP-NC data structure”, inspired by the dynamic language philosophy of dynamic programming language (such as Python). This approach allows different services and software packages to maintain their own data definitions while still aligning with the original STEP-NC definition. We have developed a framework called MetaFactory that supports the configuration of streamlined data structures and generates the corresponding program code required by various service developers. On this basis, we implemented automatic modeling for a STEP-NC object-oriented database. Using the data trimming and dimensionality reduction methods provided by MetaFactory, several prototype systems for different application scenarios have been developed.
期刊介绍:
The Journal of Manufacturing Systems is dedicated to showcasing cutting-edge fundamental and applied research in manufacturing at the systems level. Encompassing products, equipment, people, information, control, and support functions, manufacturing systems play a pivotal role in the economical and competitive development, production, delivery, and total lifecycle of products, meeting market and societal needs.
With a commitment to publishing archival scholarly literature, the journal strives to advance the state of the art in manufacturing systems and foster innovation in crafting efficient, robust, and sustainable manufacturing systems. The focus extends from equipment-level considerations to the broader scope of the extended enterprise. The Journal welcomes research addressing challenges across various scales, including nano, micro, and macro-scale manufacturing, and spanning diverse sectors such as aerospace, automotive, energy, and medical device manufacturing.