Pub Date : 2022-06-14DOI: 10.3389/fmtec.2022.880332
Qian Tang, Zeng Zhang, Zhonglei Yuan, Z. Li
The problems of additional inventory costs and inaccurate demand estimation caused by information asymmetry has severely damaged the profits of all participants and restricted the overall development of the supply chain. New technologies and ideas are urgently needed to solve these problems. The blockchain technology is widely accepted as a disruptive technology and a powerful tool to resolve information asymmetry with its advantage in decentralization, transparency, traceability, confidentiality, immutability, etc. The introduction of blockchain into the information system will effectively promote supply chain collaboration by facilitating information sharing among enterprises at various nodes. The paper builds a consortium chain model suitable for supply chain information sharing, uses evolutionary game theory to analyze the strategy changes and influencing factors in the information sharing choices of supply chain participants, and finally verifies the correctness of the results through MATLAB simulation.
{"title":"The Game Analysis of Information Sharing for Supply Chain Enterprises in the Blockchain","authors":"Qian Tang, Zeng Zhang, Zhonglei Yuan, Z. Li","doi":"10.3389/fmtec.2022.880332","DOIUrl":"https://doi.org/10.3389/fmtec.2022.880332","url":null,"abstract":"The problems of additional inventory costs and inaccurate demand estimation caused by information asymmetry has severely damaged the profits of all participants and restricted the overall development of the supply chain. New technologies and ideas are urgently needed to solve these problems. The blockchain technology is widely accepted as a disruptive technology and a powerful tool to resolve information asymmetry with its advantage in decentralization, transparency, traceability, confidentiality, immutability, etc. The introduction of blockchain into the information system will effectively promote supply chain collaboration by facilitating information sharing among enterprises at various nodes. The paper builds a consortium chain model suitable for supply chain information sharing, uses evolutionary game theory to analyze the strategy changes and influencing factors in the information sharing choices of supply chain participants, and finally verifies the correctness of the results through MATLAB simulation.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124809432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The Prognostic and Health Management (PHM) system of an aircraft has complex structures and diverse functions. It is highly coupled with other systems, such as the avionics system and flight management system. The Model-based Systems Engineering (MBSE) method is effective to support the design and verification of the aircraft PHM system. As a powerful semantic web construction method, ontology has been widely used to express design information, such as the concepts and the relationships between them. However, traditional graphical MBSE models have a natural weakness in transforming into ontology. In this paper, a semantic MBSE method is proposed to support the transform of the ontology model. Firstly, according to the design characteristics of the aircraft PHM system, a meta-model library of the aircraft PHM system is developed to support the design and evaluation. An MBSE modeling method based on requirement analysis, function analysis, logical architecture design, and physic architecture design is applied in the PHM design process. Secondly, the semantic system modeling language KARMA based on “graph, object, property, point, relationship, role, and extension” (GOPPRRE) is used to transfer the graphical MBSE model to the semantic MBSE model, which can be easily transformed to an ontology model. Finally, an ontology based on semantic modeling is developed to describe the MBSE entities and to support MBSE design. In this paper, a case study of an aircraft fuel PHM system is carried out to validate the proposed method. Based on the developed meta-model library, a complete MBSE design process for the aircraft PHM system is realized. And then an ontology model supporting PHM system design is generated from the semantic MBSE model. The MBSE ontology provides a shareable capability to help designers communicate effectively. Quantitative analysis based on ontology is also provided to verify the complexity and scale of the MBSE design process. Moreover, logical reasoning ability can also be provided to support the early requirement traceability for MBSE design. In general, the case study results show the feasibility and effectiveness of the proposed method for the aircraft PHM system design.
{"title":"A Semantic Ontology-Based Approach to Support Model-Based Systems Engineering Design for an Aircraft Prognostic Health Management System","authors":"Jinwei Chen, Yifan Chen, Zhenchao Hu, Jinzhi Lu, Xiaochen Zheng, Hui-sheng Zhang, Dimitris Kiritsis ","doi":"10.3389/fmtec.2022.886518","DOIUrl":"https://doi.org/10.3389/fmtec.2022.886518","url":null,"abstract":"The Prognostic and Health Management (PHM) system of an aircraft has complex structures and diverse functions. It is highly coupled with other systems, such as the avionics system and flight management system. The Model-based Systems Engineering (MBSE) method is effective to support the design and verification of the aircraft PHM system. As a powerful semantic web construction method, ontology has been widely used to express design information, such as the concepts and the relationships between them. However, traditional graphical MBSE models have a natural weakness in transforming into ontology. In this paper, a semantic MBSE method is proposed to support the transform of the ontology model. Firstly, according to the design characteristics of the aircraft PHM system, a meta-model library of the aircraft PHM system is developed to support the design and evaluation. An MBSE modeling method based on requirement analysis, function analysis, logical architecture design, and physic architecture design is applied in the PHM design process. Secondly, the semantic system modeling language KARMA based on “graph, object, property, point, relationship, role, and extension” (GOPPRRE) is used to transfer the graphical MBSE model to the semantic MBSE model, which can be easily transformed to an ontology model. Finally, an ontology based on semantic modeling is developed to describe the MBSE entities and to support MBSE design. In this paper, a case study of an aircraft fuel PHM system is carried out to validate the proposed method. Based on the developed meta-model library, a complete MBSE design process for the aircraft PHM system is realized. And then an ontology model supporting PHM system design is generated from the semantic MBSE model. The MBSE ontology provides a shareable capability to help designers communicate effectively. Quantitative analysis based on ontology is also provided to verify the complexity and scale of the MBSE design process. Moreover, logical reasoning ability can also be provided to support the early requirement traceability for MBSE design. In general, the case study results show the feasibility and effectiveness of the proposed method for the aircraft PHM system design.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128546367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-24DOI: 10.3389/fmtec.2022.901364
Xiaochen Zheng, P. Petrali, Jinzhi Lu, C. Turrin, D. Kiritsis
Digital Twin is one of the fundamental enabling technologies for Industry 4.0 as it allows the convergence between a physical system and its digital representation. A proper modelling method is the prerequisite for successful digital twin implementation. The manufacturing process determines critically the quality of the manufactured products. The influential elements need to be systematically organized when modelling a manufacturing process. This paper proposes a semantic modelling method named RMPFQ (Resource, Material, Process, Function/Feature, Quality) aiming to interlink the main influential factors related to product quality during manufacturing processes. The proposed RMPFQ model is formalized with an application ontology following the IOF-Core middle-level and BFO top-level ontologies. Based on this ontology, a semantic-driven digital twin architecture is designed and mapped to the recently proposed Cognitive Digital Twin concept. A correlation matrix is designed to quantify the relationships among RMPFQ elements thus to facilitate the industrial applications. A case study based on the assembly process of a washing machine is conducted to demonstrate the implementation procedures of the proposed RMPFQ method.
{"title":"RMPFQ: A Quality-Oriented Knowledge Modelling Method for Manufacturing Systems Towards Cognitive Digital Twins","authors":"Xiaochen Zheng, P. Petrali, Jinzhi Lu, C. Turrin, D. Kiritsis","doi":"10.3389/fmtec.2022.901364","DOIUrl":"https://doi.org/10.3389/fmtec.2022.901364","url":null,"abstract":"Digital Twin is one of the fundamental enabling technologies for Industry 4.0 as it allows the convergence between a physical system and its digital representation. A proper modelling method is the prerequisite for successful digital twin implementation. The manufacturing process determines critically the quality of the manufactured products. The influential elements need to be systematically organized when modelling a manufacturing process. This paper proposes a semantic modelling method named RMPFQ (Resource, Material, Process, Function/Feature, Quality) aiming to interlink the main influential factors related to product quality during manufacturing processes. The proposed RMPFQ model is formalized with an application ontology following the IOF-Core middle-level and BFO top-level ontologies. Based on this ontology, a semantic-driven digital twin architecture is designed and mapped to the recently proposed Cognitive Digital Twin concept. A correlation matrix is designed to quantify the relationships among RMPFQ elements thus to facilitate the industrial applications. A case study based on the assembly process of a washing machine is conducted to demonstrate the implementation procedures of the proposed RMPFQ method.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132247478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-11DOI: 10.3389/fmtec.2022.884164
Pinkesh K. Patel, F. Defersha, Sheng Yang
Unparalleled level of globalization and fierce competition have made supply chains (SCs) exceedingly complex and fragile as ever before. Increased incidences of natural disasters and unprecedented COVID-19 have highlighted the significance of improving supply chain resilience (SCR) by divulging its susceptibility to the external events. Additive manufacturing (AM) is envisioned as the disruptive technology that allows layer-wised fabrication and has been claimed to be an important contributor to the improved SCR as it could bring new opportunities through expanded design freedom, improved material efficiency, shortened supply chains, and decentralized manufacturing. Nonetheless, rare research has quantitatively measured the impacts of AM on SCR. To fill this research gap, the indices for assessing SCR of AM-enabled supply chains (AM-SCs) are first proposed, and then, the technique for order of preference by similarity to ideal solution (TOPSIS) is employed to derive a quantifiable SCR score that can be used to measure the performance of different SCs. A case study of a gas pedal assembly is presented with three different SC configurations: the original assembly with conventional manufacturing, original assembly with AM, and redesigned assembly with AM. The exploratory study shows that the redesigned assembly with AM considerations could improve the SCR by 200%. Sensitivity analysis also revealed that part count and reaction time of suppliers are influential factors of improving SCR. Last, challenges and limitations of the proposed framework are also deliberated upon alongside future research scope.
{"title":"Resilience Analysis of Additive Manufacturing-enabled Supply Chains: An Exploratory Study","authors":"Pinkesh K. Patel, F. Defersha, Sheng Yang","doi":"10.3389/fmtec.2022.884164","DOIUrl":"https://doi.org/10.3389/fmtec.2022.884164","url":null,"abstract":"Unparalleled level of globalization and fierce competition have made supply chains (SCs) exceedingly complex and fragile as ever before. Increased incidences of natural disasters and unprecedented COVID-19 have highlighted the significance of improving supply chain resilience (SCR) by divulging its susceptibility to the external events. Additive manufacturing (AM) is envisioned as the disruptive technology that allows layer-wised fabrication and has been claimed to be an important contributor to the improved SCR as it could bring new opportunities through expanded design freedom, improved material efficiency, shortened supply chains, and decentralized manufacturing. Nonetheless, rare research has quantitatively measured the impacts of AM on SCR. To fill this research gap, the indices for assessing SCR of AM-enabled supply chains (AM-SCs) are first proposed, and then, the technique for order of preference by similarity to ideal solution (TOPSIS) is employed to derive a quantifiable SCR score that can be used to measure the performance of different SCs. A case study of a gas pedal assembly is presented with three different SC configurations: the original assembly with conventional manufacturing, original assembly with AM, and redesigned assembly with AM. The exploratory study shows that the redesigned assembly with AM considerations could improve the SCR by 200%. Sensitivity analysis also revealed that part count and reaction time of suppliers are influential factors of improving SCR. Last, challenges and limitations of the proposed framework are also deliberated upon alongside future research scope.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"199 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132682871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-05-03DOI: 10.3389/fmtec.2022.854155
Ramon Martinez Pereira, A. L. Szejka, Osiris Canciglieri Jr.
Digital manufacturing has been challenged by the manufacturing industry to rationalize different ways to connect and exchange information and knowledge across different phases of manufacturing systems. One of the Industry 4.0 pillars is the horizontal and vertical integration with intelligent and self-adaptive systems. For this to be possible, the manufacturing industry applies an extensive range of software tools, such as GRAI, CIMOSA, MO2GO, ARIS, SCADA, MES, ERP, CAD, and CAM. Individually, each one performs its function to support the manufacturing process. However, when these multiple tools operate together using technical standards, some misinterpretation and mistake gaps are identified due to a lack of machine-to-machine (M2M) communication and users’ interpretation. This is recognized as a semantic interoperability problem. Semantic technologies, such as ontologies, have been proven to be a promising way to overcome semantic interoperability obstacles. Based on this context, this study is proposing a conceptual framework based on semantic technologies to create a solution to the horizontal and vertical integration and semantic interoperability obstacle. MANUMATE is the framework proposed, and it consists of three artifacts, 1) reference ontologies, 2) requirements, and 3) application ontology, and two processes, 1) ontology specialization and 2) information application. The MANUMATE framework is applied to two experimental case studies to validate the conceptual solution in two different applications, in the context of a long-life package for the beverages industry. These case studies help elucidate how the application of the framework could improve the information and knowledge exchange by providing a standard way to represent information among different stakeholders in the productive process. A discussion about the results is presented, revealing the benefits and limitations of the solution.
{"title":"Ontological Approach to Support the Horizontal and Vertical Information Integration in Smart Manufacturing Systems: An Experimental Case in a Long-Life Packaging Factory","authors":"Ramon Martinez Pereira, A. L. Szejka, Osiris Canciglieri Jr.","doi":"10.3389/fmtec.2022.854155","DOIUrl":"https://doi.org/10.3389/fmtec.2022.854155","url":null,"abstract":"Digital manufacturing has been challenged by the manufacturing industry to rationalize different ways to connect and exchange information and knowledge across different phases of manufacturing systems. One of the Industry 4.0 pillars is the horizontal and vertical integration with intelligent and self-adaptive systems. For this to be possible, the manufacturing industry applies an extensive range of software tools, such as GRAI, CIMOSA, MO2GO, ARIS, SCADA, MES, ERP, CAD, and CAM. Individually, each one performs its function to support the manufacturing process. However, when these multiple tools operate together using technical standards, some misinterpretation and mistake gaps are identified due to a lack of machine-to-machine (M2M) communication and users’ interpretation. This is recognized as a semantic interoperability problem. Semantic technologies, such as ontologies, have been proven to be a promising way to overcome semantic interoperability obstacles. Based on this context, this study is proposing a conceptual framework based on semantic technologies to create a solution to the horizontal and vertical integration and semantic interoperability obstacle. MANUMATE is the framework proposed, and it consists of three artifacts, 1) reference ontologies, 2) requirements, and 3) application ontology, and two processes, 1) ontology specialization and 2) information application. The MANUMATE framework is applied to two experimental case studies to validate the conceptual solution in two different applications, in the context of a long-life package for the beverages industry. These case studies help elucidate how the application of the framework could improve the information and knowledge exchange by providing a standard way to represent information among different stakeholders in the productive process. A discussion about the results is presented, revealing the benefits and limitations of the solution.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130124768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-25DOI: 10.3389/fmtec.2022.837478
S. West, M. Ebel, M. Anderson, O. Stoll, J. Poeppelbuss, M. Khan
Within the smart factory environment, we have a complex system of systems composed of Industry 4.0/digital technologies and assets with varying lifespans. Different degrees of innovation maturity and different lifespans of integrated assets within the industrial internet of things (IIOT) are considered problematic and lead to different perspectives on asset lifecycles as they impact significantly on the asset lifespans. This leads to the loss of a clear end-of-life phase defined in existing Product Lifecycle Management (PLM) models. Through an integrative literature review, this study introduces the concept of nested lifecycles that takes a systems perspective to asset management, and considers subsystems with different lifespans that must be managed holistically by different actors with different perspectives. Additionally, this study provides a framework to derive strategies for lifecycle management by allowing the nested lifecycles to be clearly identified and then addressed. From the theoretical perspective, the notion of nested lifecycles provides a novel viewpoint for the asset management and PLM research community. From the managerial perspective, the proposed framework will help managers identify why and where collaboration between different actors may create difficulties due to their varying outlooks and training.
{"title":"Nested Lifecycles-Improving the Visibility of Product Lifespans in Smart Factories","authors":"S. West, M. Ebel, M. Anderson, O. Stoll, J. Poeppelbuss, M. Khan","doi":"10.3389/fmtec.2022.837478","DOIUrl":"https://doi.org/10.3389/fmtec.2022.837478","url":null,"abstract":"Within the smart factory environment, we have a complex system of systems composed of Industry 4.0/digital technologies and assets with varying lifespans. Different degrees of innovation maturity and different lifespans of integrated assets within the industrial internet of things (IIOT) are considered problematic and lead to different perspectives on asset lifecycles as they impact significantly on the asset lifespans. This leads to the loss of a clear end-of-life phase defined in existing Product Lifecycle Management (PLM) models. Through an integrative literature review, this study introduces the concept of nested lifecycles that takes a systems perspective to asset management, and considers subsystems with different lifespans that must be managed holistically by different actors with different perspectives. Additionally, this study provides a framework to derive strategies for lifecycle management by allowing the nested lifecycles to be clearly identified and then addressed. From the theoretical perspective, the notion of nested lifecycles provides a novel viewpoint for the asset management and PLM research community. From the managerial perspective, the proposed framework will help managers identify why and where collaboration between different actors may create difficulties due to their varying outlooks and training.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116784146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-25DOI: 10.3389/fmtec.2022.863593
Cecilia Hagman, Per Svanborg
Objective: The purpose of this study was to measure the surface roughness and compare the fit of a cobalt-chromium selective laser-melted removable partial denture framework and a titanium binder jetting removable partial denture framework. Materials and methods: A design for a removable partial prosthesis framework was made using 3Shape software, and thereafter, one framework was additively manufactured in cobalt-chromium with selective laser melting and one in titanium using binder jetting technology. The weight of the frameworks was measured, and the surface parameters Sa, Sds, and Sdr were measured by white light interferometry. The fit of the frameworks was analyzed using visual inspection and the pressing test. Results: The weight of the frameworks in their post-printed state was 15.66 g and 7.43 g for cobalt-chromium and titanium, respectively. After finishing and polishing, the cobalt-chromium framework’s outer surface showed a high shine and smooth surface, with lower values in the Sa and Sdr parameters. The visual inspection showed gaps in the titanium framework, and the pressing test detected movement greater than 0.5 mm for the same material. Conclusion: The Ti framework showed higher surface roughness and was left with a lackluster finish after polishing. Also, the fit of the Ti framework was not clinically acceptable. The additive manufacturing binder jetting technology for titanium needs improvement or an adjustment of the settings to be used for clinically removable partial dentures. The cobalt-chromium framework manufactured by selective laser melting showed an acceptable clinical fit and surface roughness.
{"title":"Additive Manufacturing of a Removable Partial Prosthesis in Titanium Using Binder Jetting Technology: A Brief Research Report","authors":"Cecilia Hagman, Per Svanborg","doi":"10.3389/fmtec.2022.863593","DOIUrl":"https://doi.org/10.3389/fmtec.2022.863593","url":null,"abstract":"Objective: The purpose of this study was to measure the surface roughness and compare the fit of a cobalt-chromium selective laser-melted removable partial denture framework and a titanium binder jetting removable partial denture framework. Materials and methods: A design for a removable partial prosthesis framework was made using 3Shape software, and thereafter, one framework was additively manufactured in cobalt-chromium with selective laser melting and one in titanium using binder jetting technology. The weight of the frameworks was measured, and the surface parameters Sa, Sds, and Sdr were measured by white light interferometry. The fit of the frameworks was analyzed using visual inspection and the pressing test. Results: The weight of the frameworks in their post-printed state was 15.66 g and 7.43 g for cobalt-chromium and titanium, respectively. After finishing and polishing, the cobalt-chromium framework’s outer surface showed a high shine and smooth surface, with lower values in the Sa and Sdr parameters. The visual inspection showed gaps in the titanium framework, and the pressing test detected movement greater than 0.5 mm for the same material. Conclusion: The Ti framework showed higher surface roughness and was left with a lackluster finish after polishing. Also, the fit of the Ti framework was not clinically acceptable. The additive manufacturing binder jetting technology for titanium needs improvement or an adjustment of the settings to be used for clinically removable partial dentures. The cobalt-chromium framework manufactured by selective laser melting showed an acceptable clinical fit and surface roughness.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131143891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-24DOI: 10.3389/fmtec.2022.828986
Theyab O. Alamri, J. Mo
Critical manufacturing systems consist of many different components working together. Each component is important to the operation and performance of the whole system. It is crucial to have a sound maintenance plan to ensure continuous production output. The strategy of current research is to focus on the failure mode modelling of the manufacturing system and divide it according to failure mode in production blocks. The preventive replacement intervals are determined using mean time to failure values of components, with group replacements of components within the production blocks to prevent unexpected functional breakdown failures. With the implementation of Industry 4.0 infrastructure, the mean time to failure values of components are constantly updated. The multi-mode mathematical model developed in this paper is able to adjust the preventive replacement schedule dynamically to suit changing system conditions. The results indicate that preventive replacement of components can achieve consistent minimum system reliability of 90% while minimizing system costs due to maintenance and downtime. Novelty of the approach lies in developing a holistic preventive maintenance schedule using failure mode and effects analysis for a complete system. The approach not only improves maintainability and reliability, lowers the cost of maintenance, but also keeps continuity of production.
{"title":"Failure Mode Structured Preventive Maintenance Scheduling With Changing Failure Rates in Industry 4.0 Environment","authors":"Theyab O. Alamri, J. Mo","doi":"10.3389/fmtec.2022.828986","DOIUrl":"https://doi.org/10.3389/fmtec.2022.828986","url":null,"abstract":"Critical manufacturing systems consist of many different components working together. Each component is important to the operation and performance of the whole system. It is crucial to have a sound maintenance plan to ensure continuous production output. The strategy of current research is to focus on the failure mode modelling of the manufacturing system and divide it according to failure mode in production blocks. The preventive replacement intervals are determined using mean time to failure values of components, with group replacements of components within the production blocks to prevent unexpected functional breakdown failures. With the implementation of Industry 4.0 infrastructure, the mean time to failure values of components are constantly updated. The multi-mode mathematical model developed in this paper is able to adjust the preventive replacement schedule dynamically to suit changing system conditions. The results indicate that preventive replacement of components can achieve consistent minimum system reliability of 90% while minimizing system costs due to maintenance and downtime. Novelty of the approach lies in developing a holistic preventive maintenance schedule using failure mode and effects analysis for a complete system. The approach not only improves maintainability and reliability, lowers the cost of maintenance, but also keeps continuity of production.","PeriodicalId":330401,"journal":{"name":"Frontiers in Manufacturing Technology","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115329220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：