{"title":"通过集成PLM和MES来存储和重用工业知识的开源框架","authors":"G. Bruno, Alberto Faveto, Emiliano Traini","doi":"10.24425/MPER.2020.133729","DOIUrl":null,"url":null,"abstract":"Received: 16 March 2020 Abstract Accepted: 6 June 2020 Today, the changes in market requirements and the technological advancements are influencing the product development process. Customers demand a product of high quality and fast delivery at a low price, while simultaneously expecting that the product meet their individual needs and requirements. For companies characterized by a highly customized production, it is essential to reduce the trial-and-errors cycles to design new products and process. In such situation most of the company’s knowledge relies on the lessons learnt by operators in years of work experience, and their ability to reuse this knowledge to face new problems. In order to develop unique product and complex processes in short time, it is mandatory to reuse the acquired information in the most efficient way. Several commercial software applications are already available for product lifecycle management (PLM) and manufacturing execution system (MES). However, these two applications are scarcely integrated, thus preventing an efficient and pervasive collection of data and the consequent creation of useful information. The aim of this paper is to develop a framework able to structure and relate information from design and execution of processes, especially the ones related to anomalies and critical situations occurring at the shop floor, in order to reduce the time for finalizing a new product. The framework has been developed by exploiting open source systems, such as ARAS PLM and PostgreSQL. A case study has been developed for a car prototyping company to illustrate the potentiality of the proposed solution.","PeriodicalId":45454,"journal":{"name":"Management and Production Engineering Review","volume":" ","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2023-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"An open source framework for the storage and reuse of industrial knowledge through the integrationof PLM and MES\",\"authors\":\"G. Bruno, Alberto Faveto, Emiliano Traini\",\"doi\":\"10.24425/MPER.2020.133729\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Received: 16 March 2020 Abstract Accepted: 6 June 2020 Today, the changes in market requirements and the technological advancements are influencing the product development process. Customers demand a product of high quality and fast delivery at a low price, while simultaneously expecting that the product meet their individual needs and requirements. For companies characterized by a highly customized production, it is essential to reduce the trial-and-errors cycles to design new products and process. In such situation most of the company’s knowledge relies on the lessons learnt by operators in years of work experience, and their ability to reuse this knowledge to face new problems. In order to develop unique product and complex processes in short time, it is mandatory to reuse the acquired information in the most efficient way. Several commercial software applications are already available for product lifecycle management (PLM) and manufacturing execution system (MES). However, these two applications are scarcely integrated, thus preventing an efficient and pervasive collection of data and the consequent creation of useful information. The aim of this paper is to develop a framework able to structure and relate information from design and execution of processes, especially the ones related to anomalies and critical situations occurring at the shop floor, in order to reduce the time for finalizing a new product. The framework has been developed by exploiting open source systems, such as ARAS PLM and PostgreSQL. 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An open source framework for the storage and reuse of industrial knowledge through the integrationof PLM and MES
Received: 16 March 2020 Abstract Accepted: 6 June 2020 Today, the changes in market requirements and the technological advancements are influencing the product development process. Customers demand a product of high quality and fast delivery at a low price, while simultaneously expecting that the product meet their individual needs and requirements. For companies characterized by a highly customized production, it is essential to reduce the trial-and-errors cycles to design new products and process. In such situation most of the company’s knowledge relies on the lessons learnt by operators in years of work experience, and their ability to reuse this knowledge to face new problems. In order to develop unique product and complex processes in short time, it is mandatory to reuse the acquired information in the most efficient way. Several commercial software applications are already available for product lifecycle management (PLM) and manufacturing execution system (MES). However, these two applications are scarcely integrated, thus preventing an efficient and pervasive collection of data and the consequent creation of useful information. The aim of this paper is to develop a framework able to structure and relate information from design and execution of processes, especially the ones related to anomalies and critical situations occurring at the shop floor, in order to reduce the time for finalizing a new product. The framework has been developed by exploiting open source systems, such as ARAS PLM and PostgreSQL. A case study has been developed for a car prototyping company to illustrate the potentiality of the proposed solution.
期刊介绍:
Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.