Pub Date : 2023-12-15DOI: 10.1080/0951192x.2023.2294443
Jiaqi Zhao, El-Houssaine Aghezzaf, Johannes Cottyn
To achieve interoperability between different 3D virtual commissioning software, a generic virtual commissioning data model is required. AutomationML is a standard neutral format for interoperabili...
为了实现不同 3D 虚拟调试软件之间的互操作性，需要一个通用的虚拟调试数据模型。AutomationML 是一种用于互操作性的标准中立格式。
{"title":"An AutomationML extension towards interoperability of 3D virtual commissioning software applications","authors":"Jiaqi Zhao, El-Houssaine Aghezzaf, Johannes Cottyn","doi":"10.1080/0951192x.2023.2294443","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2294443","url":null,"abstract":"To achieve interoperability between different 3D virtual commissioning software, a generic virtual commissioning data model is required. AutomationML is a standard neutral format for interoperabili...","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"20 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138715311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-24DOI: 10.1080/0951192x.2023.2278114
Bo Tian, Mukund Janardhanan, Marina Marinelli
Human-robot collaboration (HRC) is putting humans back at the centre of manufacturing via tech-empowered workers. On human-robot assembly line (HRAL), humans and collaborative robots (cobots) can p...
{"title":"A systematic investigation of the barriers to effective implementation of human-robot assembly line: an integrated multi-criteria decision-making approach","authors":"Bo Tian, Mukund Janardhanan, Marina Marinelli","doi":"10.1080/0951192x.2023.2278114","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278114","url":null,"abstract":"Human-robot collaboration (HRC) is putting humans back at the centre of manufacturing via tech-empowered workers. On human-robot assembly line (HRAL), humans and collaborative robots (cobots) can p...","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"65 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138541898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-20DOI: 10.1080/0951192x.2023.2278110
Bilal Muhammed, P. Srimannarayana, Prasenjit Das, B. P. Gautham
Cutting tool manufacturers face a tough challenge in developing custom solutions for specific customer requirements. Several trials are required, encompassing the selection of materials, tool confi...
{"title":"An intelligent recommender system for tool selection in conventional machining","authors":"Bilal Muhammed, P. Srimannarayana, Prasenjit Das, B. P. Gautham","doi":"10.1080/0951192x.2023.2278110","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278110","url":null,"abstract":"Cutting tool manufacturers face a tough challenge in developing custom solutions for specific customer requirements. Several trials are required, encompassing the selection of materials, tool confi...","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"33 4","pages":""},"PeriodicalIF":4.1,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138506137","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-14DOI: 10.1080/0951192x.2023.2278105
Marta Pinzone, Paola Fantini, Marco Taisch
ABSTRACTThis paper outlines a conceptual framework and a repository of skills for Industry 4.0 that manufacturing managers and other stakeholders can use for training, hiring and developing human resources. The framework and the repository of Industry 4.0 skills were developed by involving industrial practitioners, technology providers, recruitment agencies, research and education organizations in scenario-based focus groups and semi-structured interviews. The results of this study contribute to improving our current understanding of the skills required for Industry 4.0, and they can be used for the identification and assessment of workers’ skills as well as the design of skill development programs that match the needs of the industry and for the definition of policies that support the development of human capital to improve the employability of individuals and the performance of manufacturing companies.KEYWORDS: Industry 4.0skillcompetencyforesighthuman resourcetraining AcknowledgmentsThe Authors wish to thank the “Industry 4.0” Observatory of the School of Management of Politecnico di Milano, the experts and all the actors participating in the focus groups for their valuable inputs to the work.Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis research has been supported by donations of the Caterpillar Foundation, US in the context of the Chair Industry 4.h (human).
{"title":"Skills for Industry 4.0: a structured repository grounded on a generalized enterprise reference architecture and methodology-based framework","authors":"Marta Pinzone, Paola Fantini, Marco Taisch","doi":"10.1080/0951192x.2023.2278105","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278105","url":null,"abstract":"ABSTRACTThis paper outlines a conceptual framework and a repository of skills for Industry 4.0 that manufacturing managers and other stakeholders can use for training, hiring and developing human resources. The framework and the repository of Industry 4.0 skills were developed by involving industrial practitioners, technology providers, recruitment agencies, research and education organizations in scenario-based focus groups and semi-structured interviews. The results of this study contribute to improving our current understanding of the skills required for Industry 4.0, and they can be used for the identification and assessment of workers’ skills as well as the design of skill development programs that match the needs of the industry and for the definition of policies that support the development of human capital to improve the employability of individuals and the performance of manufacturing companies.KEYWORDS: Industry 4.0skillcompetencyforesighthuman resourcetraining AcknowledgmentsThe Authors wish to thank the “Industry 4.0” Observatory of the School of Management of Politecnico di Milano, the experts and all the actors participating in the focus groups for their valuable inputs to the work.Disclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThis research has been supported by donations of the Caterpillar Foundation, US in the context of the Chair Industry 4.h (human).","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"2 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134954211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-11DOI: 10.1080/0951192x.2023.2278115
Alberto Cannavò, Massimo Gismondi, Fabrizio Lamberti
ABSTRACTOver the last years, many progresses have been made in the field of virtual prototyping, pushed by the interest of industries and artisans. Especially in the context of the textile industry, the digitizing of the prototyping stage offers the possibility to validate the product design choices before committing to the market. This paper presents a framework for the virtual prototyping of crocheted objects. The core of the framework is an algorithm that is capable of generating the crocheting patterns for a given object and the corresponding instructions. The instructions are leveraged by the framework to visualize the 3D geometry of the object, and can be also used to craft it. Compared to previous works, the proposed algorithm combines a number of features (primarily, the use of parametric surfaces and the support for short rows) that can reduce the distortions in crafted object shape while also lowering computational cost; the algorithm is also able to consider material- and style-related information. The results of a comparison between the proposed algorithm and state-of-the-art approaches showed improved performance in terms of similarity of the generated shape with the target one, computation time, and appearance of the crafted object.KEYWORDS: Virtual prototypingcrocheting instruction generation algorithmshort rowsdigital craftingparametric design AcknowledgmentsThe authors would like to thank Özgüç Çapunaman, co-author of the reference of work considered in the experimental evaluation, for making available the surfaces used in their research, thus enabling the comparison of achieved results.Disclosure statementThe authors have no relevant financial or non-financial interests to disclose.Author contributorsAll the authors contributed to the study conception and design. The software was developed by Massimo Gismondi, under the supervision of Fabrizio Lamberti and Alberto Cannavò. The experimental analysis was performed by Massimo Gismondi with the support of Alberto Cannavò, and revised by Fabrizio Lamberti. The first draft of the manuscript was written by Alberto Cannavò, and all the authors worked on its revisions. All the authors read and approved the final manuscript.Additional informationFundingResearch was supported by PON “Ricerca e Innovazione” 2014–2020 – DM 1062/2021 funds.
{"title":"Virtual prototyping for the textile industry: a framework supporting the production of crocheted objects","authors":"Alberto Cannavò, Massimo Gismondi, Fabrizio Lamberti","doi":"10.1080/0951192x.2023.2278115","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278115","url":null,"abstract":"ABSTRACTOver the last years, many progresses have been made in the field of virtual prototyping, pushed by the interest of industries and artisans. Especially in the context of the textile industry, the digitizing of the prototyping stage offers the possibility to validate the product design choices before committing to the market. This paper presents a framework for the virtual prototyping of crocheted objects. The core of the framework is an algorithm that is capable of generating the crocheting patterns for a given object and the corresponding instructions. The instructions are leveraged by the framework to visualize the 3D geometry of the object, and can be also used to craft it. Compared to previous works, the proposed algorithm combines a number of features (primarily, the use of parametric surfaces and the support for short rows) that can reduce the distortions in crafted object shape while also lowering computational cost; the algorithm is also able to consider material- and style-related information. The results of a comparison between the proposed algorithm and state-of-the-art approaches showed improved performance in terms of similarity of the generated shape with the target one, computation time, and appearance of the crafted object.KEYWORDS: Virtual prototypingcrocheting instruction generation algorithmshort rowsdigital craftingparametric design AcknowledgmentsThe authors would like to thank Özgüç Çapunaman, co-author of the reference of work considered in the experimental evaluation, for making available the surfaces used in their research, thus enabling the comparison of achieved results.Disclosure statementThe authors have no relevant financial or non-financial interests to disclose.Author contributorsAll the authors contributed to the study conception and design. The software was developed by Massimo Gismondi, under the supervision of Fabrizio Lamberti and Alberto Cannavò. The experimental analysis was performed by Massimo Gismondi with the support of Alberto Cannavò, and revised by Fabrizio Lamberti. The first draft of the manuscript was written by Alberto Cannavò, and all the authors worked on its revisions. All the authors read and approved the final manuscript.Additional informationFundingResearch was supported by PON “Ricerca e Innovazione” 2014–2020 – DM 1062/2021 funds.","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"22 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135041808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-11DOI: 10.1080/0951192x.2023.2278108
Vincenzo Cutrona, Niko Bonomi, Elias Montini, Tamas Ruppert, Giacomo Delinavelli, Paolo Pedrazzoli
This paper extends the traditional factory digital twins by incorporating human characterisation in Asset Administration Shell (AAS). The extension lays the basis for human-centred control and management, as demonstrated by employing a prototype of the extended AAS in two proposed use cases. Referred to Industry 5.0, an accurate digital representation of humans as a basis of the data-based decision support to improve operators’ well-being and resilience. The AAS is extended to include dedicated digital models accommodating a set of properties to describe the human operators and its interactions with the surrounding shop-floor resources. Two reference use cases have been designed in the context of a complete lab-scale manufacturing system: equipment and devices have been modelled according to the AAS standard, exposing information via MQTT, and have been integrated with the proposed AAS definition of human operators. Operators have been equipped with wearable sensors and a dashboard providing them with feedback from the manufacturing environment and notifications about changes. As part of the extension process, some ethical and regulation concerns are discussed, highlighting that the extended AAS is mature enough to support the inclusion of human operators, but regulations struggle to keep up with technological advances.
{"title":"Extending factory digital Twins through human characterisation in Asset Administration Shell","authors":"Vincenzo Cutrona, Niko Bonomi, Elias Montini, Tamas Ruppert, Giacomo Delinavelli, Paolo Pedrazzoli","doi":"10.1080/0951192x.2023.2278108","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278108","url":null,"abstract":"This paper extends the traditional factory digital twins by incorporating human characterisation in Asset Administration Shell (AAS). The extension lays the basis for human-centred control and management, as demonstrated by employing a prototype of the extended AAS in two proposed use cases. Referred to Industry 5.0, an accurate digital representation of humans as a basis of the data-based decision support to improve operators’ well-being and resilience. The AAS is extended to include dedicated digital models accommodating a set of properties to describe the human operators and its interactions with the surrounding shop-floor resources. Two reference use cases have been designed in the context of a complete lab-scale manufacturing system: equipment and devices have been modelled according to the AAS standard, exposing information via MQTT, and have been integrated with the proposed AAS definition of human operators. Operators have been equipped with wearable sensors and a dashboard providing them with feedback from the manufacturing environment and notifications about changes. As part of the extension process, some ethical and regulation concerns are discussed, highlighting that the extended AAS is mature enough to support the inclusion of human operators, but regulations struggle to keep up with technological advances.","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"20 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135041672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-05DOI: 10.1080/0951192x.2023.2278113
Xiaohong Lu, Zhuo Sun, Yihan Luan, Le Teng, Steven Y. Liang
ABSTRACTTemperature field distribution of friction stir welding (FSW) influences weld quality directly, so real-time monitoring of the welding temperature is significant. However, it is difficult to monitor the temperature in the core zone due to mechanical obstructions, material plastic deformation and complex thermal-mechanical coupling. To tackle this issue, this study develops a digital twin-based temperature monitoring system of FSW. Initially, a five-dimensional integrated framework based on the digital twin concept is proposed, outlining the process of building a digital twin-based temperature monitoring system of FSW. Subsequently, a motion simulation model of FSW is established, and synchronous motion simulation of the welding process is achieved. Real-time temperature readings from the FSW workpiece surface are gathered via an infrared thermal imager and synchronously transmitted to the FSW temperature monitoring system using socket communication. Additionally, a predictive model utilizing Support Vector Regression (SVR) is incorporated, enabling real-time and precise prediction of extremum temperatures in the core zone and over-limit alarm functionality. Finally, the temperature monitoring system of FSW, grounded in the digital twin concept and integrating the outlined models and features, is developed and experimentally validated. The system enables operators to exercise timely control over the welding process to ensure weld quality.KEYWORDS: Friction stir weldingmonitoring systemtemperaturedigital twin AcknowledgmentsThe research was supported by the National Key Research and Development Program of China (Grant No. 2019YFA0709003) and Natural Science Foundation of Liaoning Province of China (2023-MS-101). The financial contributions are gratefully acknowledged.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the National Key Research and Development Program of China [2019YFA0709003]; Natural Science Foundation of Liaoning Province of China [2023-MS-101].
{"title":"Temperature monitoring system of friction stir welding based on digital twin","authors":"Xiaohong Lu, Zhuo Sun, Yihan Luan, Le Teng, Steven Y. Liang","doi":"10.1080/0951192x.2023.2278113","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278113","url":null,"abstract":"ABSTRACTTemperature field distribution of friction stir welding (FSW) influences weld quality directly, so real-time monitoring of the welding temperature is significant. However, it is difficult to monitor the temperature in the core zone due to mechanical obstructions, material plastic deformation and complex thermal-mechanical coupling. To tackle this issue, this study develops a digital twin-based temperature monitoring system of FSW. Initially, a five-dimensional integrated framework based on the digital twin concept is proposed, outlining the process of building a digital twin-based temperature monitoring system of FSW. Subsequently, a motion simulation model of FSW is established, and synchronous motion simulation of the welding process is achieved. Real-time temperature readings from the FSW workpiece surface are gathered via an infrared thermal imager and synchronously transmitted to the FSW temperature monitoring system using socket communication. Additionally, a predictive model utilizing Support Vector Regression (SVR) is incorporated, enabling real-time and precise prediction of extremum temperatures in the core zone and over-limit alarm functionality. Finally, the temperature monitoring system of FSW, grounded in the digital twin concept and integrating the outlined models and features, is developed and experimentally validated. The system enables operators to exercise timely control over the welding process to ensure weld quality.KEYWORDS: Friction stir weldingmonitoring systemtemperaturedigital twin AcknowledgmentsThe research was supported by the National Key Research and Development Program of China (Grant No. 2019YFA0709003) and Natural Science Foundation of Liaoning Province of China (2023-MS-101). The financial contributions are gratefully acknowledged.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the National Key Research and Development Program of China [2019YFA0709003]; Natural Science Foundation of Liaoning Province of China [2023-MS-101].","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"134 15","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135724652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-05DOI: 10.1080/0951192x.2023.2278100
Zhenyong Wu, Rong Zhou, Mark Goh, Yuan Wang, Zhitao Xu, Wenyan Song
ABSTRACTThe rapid emergence and widespread adoption of next-generation information technologies have led to a growing recognition of the need for digitalized warehouse designs. However, creating a digital replica of a physical warehouse in a virtual environment is a complex task. This research introduces a framework for designing smart warehouses based on digital twins, consisting of four key steps: (1) defining the dimensions of the digital twin, (2) establishing a digital twin framework that encompasses the physical warehouse, digital twin, and design processes, (3) implementing modularization techniques for the digital twin, and (4) operating the smart warehouse based on the digital twin. To validate the proposed framework, we present a detailed case study involving a semiconductor manufacturing plant. The results demonstrate the effectiveness of the digital twin-based smart warehouse design and its operational processes.KEYWORDS: Digital twinsmart warehousewarehouse designframework AcknowledgmentsThe authors thank the editor and the anonymous reviewers for their helpful comments. The authors disclose receipt of the following financial support for the research, authorship, and/or publication of this article. This work was supported by Jiangsu Social Science Fund of China (Grant No.2022SJYB0183), Introduction Program of High-Level Innovation and Entrepreneurship Talents in Jiangsu Province (Grant No. JSSCB20210481), Starting Research Fund from the Nanjing University of Information Science & Technology, and Singapore A*STAR IAF-PP fund (Grant No. A1895a0033) under the project “Digital Twin for Next Generation Warehouse”.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.Additional informationFundingThe work was supported by the Introduction Program of High-Level Innovation and Entrepreneurship Talents in Jiangsu Province [JSSCB20210481]; Singapore A*STAR IAF-PP fund [A1895a0033]; Starting Research Fund from the Nanjing University of Information Science & Technology .
{"title":"(DT4Smart) a digital twin-based modularized design approach for smart warehouses","authors":"Zhenyong Wu, Rong Zhou, Mark Goh, Yuan Wang, Zhitao Xu, Wenyan Song","doi":"10.1080/0951192x.2023.2278100","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2278100","url":null,"abstract":"ABSTRACTThe rapid emergence and widespread adoption of next-generation information technologies have led to a growing recognition of the need for digitalized warehouse designs. However, creating a digital replica of a physical warehouse in a virtual environment is a complex task. This research introduces a framework for designing smart warehouses based on digital twins, consisting of four key steps: (1) defining the dimensions of the digital twin, (2) establishing a digital twin framework that encompasses the physical warehouse, digital twin, and design processes, (3) implementing modularization techniques for the digital twin, and (4) operating the smart warehouse based on the digital twin. To validate the proposed framework, we present a detailed case study involving a semiconductor manufacturing plant. The results demonstrate the effectiveness of the digital twin-based smart warehouse design and its operational processes.KEYWORDS: Digital twinsmart warehousewarehouse designframework AcknowledgmentsThe authors thank the editor and the anonymous reviewers for their helpful comments. The authors disclose receipt of the following financial support for the research, authorship, and/or publication of this article. This work was supported by Jiangsu Social Science Fund of China (Grant No.2022SJYB0183), Introduction Program of High-Level Innovation and Entrepreneurship Talents in Jiangsu Province (Grant No. JSSCB20210481), Starting Research Fund from the Nanjing University of Information Science & Technology, and Singapore A*STAR IAF-PP fund (Grant No. A1895a0033) under the project “Digital Twin for Next Generation Warehouse”.Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementThe authors confirm that the data supporting the findings of this study are available within the article.Additional informationFundingThe work was supported by the Introduction Program of High-Level Innovation and Entrepreneurship Talents in Jiangsu Province [JSSCB20210481]; Singapore A*STAR IAF-PP fund [A1895a0033]; Starting Research Fund from the Nanjing University of Information Science & Technology .","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"133 33","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135724505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACTQuality and efficiency prediction, as well as coupling optimization, is very important for improving product production. However, most of the researches are studying the quality and efficiency separately, which makes it difficult to improveproduction. Therefore, this paper proposes a quality–efficiency coupling prediction and monitoring-based process optimization method to effectively improve the quality and efficiency of thin plate parts with multi-machining features at the same time. And the best process parameters are recommended to better improve machining stability. Firstly, based on the generalized multi-layer residual network and deep neural network (MLResNet-DNN), the prediction models of quality and efficiency are constructed, respectively. Secondly, the quality–efficiency coupling index is constructed based on coupled permutation entropy (CPE) accordingly. Finally, the process optimization model based on the hybrid artificial bee colony–particle swarm optimization (HABC-PSO) algorithm is established to recommend the best process parameters according to the monitoring results of quality–efficiency CPE. The RMSE average value of the proposed quality and machining time prediction model has an average improvement of at least 10.8% and 25.9%, respectively, than other prediction model. The process parameters recommended by the proposed HABC-PSO method have improved the machining stability of quality and efficiency by at least 25.6%, and machining time is reduced by at least 25.7% compared with other optimization algorithms.KEYWORDS: Quality–efficiency couplingMLResNet-DNNcoupling permutation entropyT-square statisticscoupling monitorprocess optimization Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is financially supported in part by the project supported by the National Natural Science Foundation of China (52275507) and in part by the Major Science and Technology Special Project in Shannxi Province of China (2019zdzx01-01-02).
{"title":"Quality–efficiency coupling prediction and monitoring-based process optimization of thin plate parts with multi-machining feature","authors":"Pei Wang, Fanhui Bu, Xianguang Kong, Jiantao Chang, Yixin Cui, Anji Zhang","doi":"10.1080/0951192x.2023.2264831","DOIUrl":"https://doi.org/10.1080/0951192x.2023.2264831","url":null,"abstract":"ABSTRACTQuality and efficiency prediction, as well as coupling optimization, is very important for improving product production. However, most of the researches are studying the quality and efficiency separately, which makes it difficult to improveproduction. Therefore, this paper proposes a quality–efficiency coupling prediction and monitoring-based process optimization method to effectively improve the quality and efficiency of thin plate parts with multi-machining features at the same time. And the best process parameters are recommended to better improve machining stability. Firstly, based on the generalized multi-layer residual network and deep neural network (MLResNet-DNN), the prediction models of quality and efficiency are constructed, respectively. Secondly, the quality–efficiency coupling index is constructed based on coupled permutation entropy (CPE) accordingly. Finally, the process optimization model based on the hybrid artificial bee colony–particle swarm optimization (HABC-PSO) algorithm is established to recommend the best process parameters according to the monitoring results of quality–efficiency CPE. The RMSE average value of the proposed quality and machining time prediction model has an average improvement of at least 10.8% and 25.9%, respectively, than other prediction model. The process parameters recommended by the proposed HABC-PSO method have improved the machining stability of quality and efficiency by at least 25.6%, and machining time is reduced by at least 25.7% compared with other optimization algorithms.KEYWORDS: Quality–efficiency couplingMLResNet-DNNcoupling permutation entropyT-square statisticscoupling monitorprocess optimization Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work is financially supported in part by the project supported by the National Natural Science Foundation of China (52275507) and in part by the Major Science and Technology Special Project in Shannxi Province of China (2019zdzx01-01-02).","PeriodicalId":13907,"journal":{"name":"International Journal of Computer Integrated Manufacturing","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136113235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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