Pub Date : 2024-10-31DOI: 10.1016/j.cirpj.2024.10.014
Arpita Chari , Mélanie Despeisse , Björn Johansson , Sandra Morioka , Cláudia Fabiana Gohr , Johan Stahre
In uncertain manufacturing environments, tools that help companies and supply chains navigate unexpected events and promote sustainability are crucial. However, the application of resilience in manufacturing organizations is limited, often focusing on supply chain resilience. This study used mixed methods to minimize subjectivity in manufacturing resilience. A quantitative Content Validity Index (CVI) helped develop the 'resilience compass' assessment tool, while empirical applications in six manufacturing organizations demonstrated its usefulness. The study identifies relationships between 54 resilience practices, 11 dynamic capabilities, and three stages: anticipation, coping, and adaptation, providing decision-makers with actionable insights to enhance manufacturing resilience.
{"title":"Resilience compass navigation through manufacturing organization uncertainty – A dynamic capabilities approach using mixed methods","authors":"Arpita Chari , Mélanie Despeisse , Björn Johansson , Sandra Morioka , Cláudia Fabiana Gohr , Johan Stahre","doi":"10.1016/j.cirpj.2024.10.014","DOIUrl":"10.1016/j.cirpj.2024.10.014","url":null,"abstract":"<div><div>In uncertain manufacturing environments, tools that help companies and supply chains navigate unexpected events and promote sustainability are crucial. However, the application of resilience in manufacturing organizations is limited, often focusing on supply chain resilience. This study used mixed methods to minimize subjectivity in manufacturing resilience. A quantitative Content Validity Index (CVI) helped develop the 'resilience compass' assessment tool, while empirical applications in six manufacturing organizations demonstrated its usefulness. The study identifies relationships between 54 resilience practices, 11 dynamic capabilities, and three stages: anticipation, coping, and adaptation, providing decision-makers with actionable insights to enhance manufacturing resilience.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 375-389"},"PeriodicalIF":4.6,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142561217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-28DOI: 10.1016/j.cirpj.2024.10.010
Maaike Slot , Roy Damgrave , Eric Lutters
Companies aim to adapt their shopfloors to increase the efficiency and effectiveness of their production activities, adding value to their shopfloor. However, it has become increasingly challenging to obtain an accurate and comprehensive overview of the shop floor and organisation, leading to difficulties in making operational, tactical, and strategic decisions. Existing methods to support such companies either restrict access to information or pre-determine the perspectives on the information for decision-making. This research employs a research-by-design approach to develop the digital twinning approach that can facilitate companies to develop a solution that can provide the appropriate information at the right moment and in the right perspective. To structure the digital twinning approach, key functions in the approach are outlined in a functional architecture. Two case studies demonstrate and verify the applicability and added value of the architecture in developing an information provisioning solution. The positive outcomes and experiences from these case studies highlight the potential of the digital twinning approach to facilitate companies in developing adaptable and company-specific solutions to enhance decision-making processes.
{"title":"A structured digital twinning approach to improve decision-making in manufacturing SMEs","authors":"Maaike Slot , Roy Damgrave , Eric Lutters","doi":"10.1016/j.cirpj.2024.10.010","DOIUrl":"10.1016/j.cirpj.2024.10.010","url":null,"abstract":"<div><div>Companies aim to adapt their shopfloors to increase the efficiency and effectiveness of their production activities, adding value to their shopfloor. However, it has become increasingly challenging to obtain an accurate and comprehensive overview of the shop floor and organisation, leading to difficulties in making operational, tactical, and strategic decisions. Existing methods to support such companies either restrict access to information or pre-determine the perspectives on the information for decision-making. This research employs a research-by-design approach to develop the digital twinning approach that can facilitate companies to develop a solution that can provide the appropriate information at the right moment and in the right perspective. To structure the digital twinning approach, key functions in the approach are outlined in a functional architecture. Two case studies demonstrate and verify the applicability and added value of the architecture in developing an information provisioning solution. The positive outcomes and experiences from these case studies highlight the potential of the digital twinning approach to facilitate companies in developing adaptable and company-specific solutions to enhance decision-making processes.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 359-374"},"PeriodicalIF":4.6,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-25DOI: 10.1016/j.cirpj.2024.10.012
Keyu Nian, Weifeng Xie, Hao Tu
The beneficial effects of ultrasonic vibration-assisted arc welding on the performance of welded joints have been experimentally confirmed. However, the mechanism of the influence of ultrasonic vibration on the temperature and flow fields of the welding pool is still not clear, which also limits further application prospects of this technology. The present study established a three-dimensional molten pool model for ultrasonic vibration-assisted gas tungsten arc (UV-GTA) welding of low-alloy high-strength steel, considering free deformation of the molten pool surface and different ultrasonic vibration amplitudes. The temperature field evolution and the molten pool flow behavior under various ultrasonic vibration amplitudes were systematically analyzed. Compared with GTA welding, the ultrasonic vibration in UV-GTA welding enhanced uniformity of the temperature distribution in molten pool. Moreover, the larger the ultrasonic amplitude in UV-GTA welding, the smaller the depth of the molten pool and the time required for the molten pool to reach a quasi-steady state, but the larger the maximum flow rate at the surface as well as at the center of the molten pool. At an ultrasonic vibration amplitude of 40 µm, the molten pool depth in UV-GTA welding decreased by 34.8 % compared with GTA molten pool depth. The time for this UV-GTA molten pool to reach a quasi-steady state was just 0.57 s, and the maximum velocity at its center increased by 88.1 % over that of the GTA molten pool. Comparative analysis of the UV-GTA molten pool and the GTA molten pool revealed a shorter circulating flow field on the upper surface and periodic variations in the internal flow field motion. The simulation outcomes closely align with the experimental findings, confirming both the validity of the model and the accuracy of the pertinent conclusions. This research may lay a solid theoretical foundation for further systematic exploration of the wider application prospects of ultrasonic vibration-assisted arc welding.
{"title":"Numerical simulation of molten pool flow behavior in ultrasonic vibration-assisted gas tungsten arc welding of low-alloy high-strength steel","authors":"Keyu Nian, Weifeng Xie, Hao Tu","doi":"10.1016/j.cirpj.2024.10.012","DOIUrl":"10.1016/j.cirpj.2024.10.012","url":null,"abstract":"<div><div>The beneficial effects of ultrasonic vibration-assisted arc welding on the performance of welded joints have been experimentally confirmed. However, the mechanism of the influence of ultrasonic vibration on the temperature and flow fields of the welding pool is still not clear, which also limits further application prospects of this technology. The present study established a three-dimensional molten pool model for ultrasonic vibration-assisted gas tungsten arc (UV-GTA) welding of low-alloy high-strength steel, considering free deformation of the molten pool surface and different ultrasonic vibration amplitudes. The temperature field evolution and the molten pool flow behavior under various ultrasonic vibration amplitudes were systematically analyzed. Compared with GTA welding, the ultrasonic vibration in UV-GTA welding enhanced uniformity of the temperature distribution in molten pool. Moreover, the larger the ultrasonic amplitude in UV-GTA welding, the smaller the depth of the molten pool and the time required for the molten pool to reach a quasi-steady state, but the larger the maximum flow rate at the surface as well as at the center of the molten pool. At an ultrasonic vibration amplitude of 40 µm, the molten pool depth in UV-GTA welding decreased by 34.8 % compared with GTA molten pool depth. The time for this UV-GTA molten pool to reach a quasi-steady state was just 0.57 s, and the maximum velocity at its center increased by 88.1 % over that of the GTA molten pool. Comparative analysis of the UV-GTA molten pool and the GTA molten pool revealed a shorter circulating flow field on the upper surface and periodic variations in the internal flow field motion. The simulation outcomes closely align with the experimental findings, confirming both the validity of the model and the accuracy of the pertinent conclusions. This research may lay a solid theoretical foundation for further systematic exploration of the wider application prospects of ultrasonic vibration-assisted arc welding.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 347-358"},"PeriodicalIF":4.6,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-10-24DOI: 10.1016/j.cirpj.2024.10.003
Sampsa Vili Antero Laakso, Andrey Mityakov, Tom Niinimäki, Kandice Suane Barros Ribeiro, Wallace Moreira Bessa
Metal cutting processes contribute significant share of the added value of industrial products. The need for machining has grown exponentially with increasing demands for quality and accuracy, and despite of more than a century of research in the field, there are no reliable and accurate models that describe all the physical phenomena needed to optimize the machining processes. The scientific community has begun to explore hybrid methods instead of expanding the capabilities of individual modelling schemes, which has been more efficient than efficacious direction. Following this trend, we propose a hybrid finite element — machine learning method (FEML) for modelling metal cutting. The advantages of the FEML method are reduced need for experimental data, reduced computational time and improved prediction accuracy. This paper describes the FEML model, which uses a Coupled Eulerian Lagrangian (CEL) formulation and deep neural networks (DNN) from the TensorFlow Python library. The machining experiments include forces, chip morphology and surface roughness. The experimental data was divided into training dataset and validation dataset to confirm the model predictions outside the experimental data range. The hybrid FEML model outperformed the DNN and FEM models independently, by reducing the computational time, improving the average prediction error from 23% to 13% and reduced the need for experimental data by half.
{"title":"Hybrid FE-ML model for turning of 42CrMo4 steel","authors":"Sampsa Vili Antero Laakso, Andrey Mityakov, Tom Niinimäki, Kandice Suane Barros Ribeiro, Wallace Moreira Bessa","doi":"10.1016/j.cirpj.2024.10.003","DOIUrl":"10.1016/j.cirpj.2024.10.003","url":null,"abstract":"<div><div>Metal cutting processes contribute significant share of the added value of industrial products. The need for machining has grown exponentially with increasing demands for quality and accuracy, and despite of more than a century of research in the field, there are no reliable and accurate models that describe all the physical phenomena needed to optimize the machining processes. The scientific community has begun to explore hybrid methods instead of expanding the capabilities of individual modelling schemes, which has been more efficient than efficacious direction. Following this trend, we propose a hybrid finite element — machine learning method (FEML) for modelling metal cutting. The advantages of the FEML method are reduced need for experimental data, reduced computational time and improved prediction accuracy. This paper describes the FEML model, which uses a Coupled Eulerian Lagrangian (CEL) formulation and deep neural networks (DNN) from the TensorFlow Python library. The machining experiments include forces, chip morphology and surface roughness. The experimental data was divided into training dataset and validation dataset to confirm the model predictions outside the experimental data range. The hybrid FEML model outperformed the DNN and FEM models independently, by reducing the computational time, improving the average prediction error from 23% to 13% and reduced the need for experimental data by half.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 333-346"},"PeriodicalIF":4.6,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-23DOI: 10.1016/j.cirpj.2024.10.011
Di Wu , Jiyuan Tian , Maocheng Liao , Man Zhao , Gang Liu
In the laser directed energy deposition (LDED) process, cyclic thermal stress loading induces significant temperature variations on the surface and subsurface of the workpiece during repeated heating, leading to the formation of residual tensile stress during cooling. This adversely affects the mechanical properties of the parts, causing deformation and defects. In this study, a heat transfer model and a three-dimensional stress model were established based on finite element analysis. A variable laser power (VLP) deposition strategy was proposed to dynamically simulate the temperature and stress fields of Ti6Al4V titanium alloy under different deposition strategies. The model was validated by collecting substrate temperature variations using thermocouples and measuring residual stress with an X-ray diffractometer (XRD). Experimental results showed that the temperature error between the simulation and the experiment ranged from 6.25 % to 10.12 %, with an average stress simulation error of 6.92 %. Among the four strategies, the samples using the VLP strategy showed a reduction in the average substrate temperature by 12.68 % to 15.08 % compared to the other three strategies. The maximum principal stress in the layer was reduced by 7.8 % to 32.14 %, and the residual stress distribution was more uniform in all directions. The microstructure of the deposition layer further indicated that the VLP strategy improves residual stress distribution and leading to better deposition quality.
{"title":"Study on the effect of variable laser power on residual stress distribution in laser directed energy deposition of Ti6Al4V","authors":"Di Wu , Jiyuan Tian , Maocheng Liao , Man Zhao , Gang Liu","doi":"10.1016/j.cirpj.2024.10.011","DOIUrl":"10.1016/j.cirpj.2024.10.011","url":null,"abstract":"<div><div>In the laser directed energy deposition (LDED) process, cyclic thermal stress loading induces significant temperature variations on the surface and subsurface of the workpiece during repeated heating, leading to the formation of residual tensile stress during cooling. This adversely affects the mechanical properties of the parts, causing deformation and defects. In this study, a heat transfer model and a three-dimensional stress model were established based on finite element analysis. A variable laser power (VLP) deposition strategy was proposed to dynamically simulate the temperature and stress fields of Ti6Al4V titanium alloy under different deposition strategies. The model was validated by collecting substrate temperature variations using thermocouples and measuring residual stress with an X-ray diffractometer (XRD). Experimental results showed that the temperature error between the simulation and the experiment ranged from 6.25 % to 10.12 %, with an average stress simulation error of 6.92 %. Among the four strategies, the samples using the VLP strategy showed a reduction in the average substrate temperature by 12.68 % to 15.08 % compared to the other three strategies. The maximum principal stress in the layer was reduced by 7.8 % to 32.14 %, and the residual stress distribution was more uniform in all directions. The microstructure of the deposition layer further indicated that the VLP strategy improves residual stress distribution and leading to better deposition quality.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 322-332"},"PeriodicalIF":4.6,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-10-22DOI: 10.1016/j.cirpj.2024.10.005
E. Ulular , Y. Altintas , A. Liljerehn
This paper presents digital modeling of shell face mills in milling cylinder heads. The cutter's structural dynamics and its mode shapes are predicted using a Finite Element system. The geometries of the cutter body and inserts are imported from their Computer Aided Design (CAD) models. The insert edge is discretized into small segments to model its varying normal rake and inclination angles, which affect the cutting mechanics. The cutter is dynamically assembled with the target machine tool spindle using the receptance coupling method. A general dynamic cutting force model, which considers the varying edge geometry and inserts’ run-outs, is developed and used to predict cutting forces and chatter stability diagrams. The proposed model is experimentally verified to demonstrate the feasibility of the systematic application of physics-based digital design and analysis of tools for the mass machining of specific parts. The cutter body shape is optimized to increase the stiffness of the bending mode shape that caused chatter via topology optimization, which led to five-fold increase in the absolute stable depth of cut.
{"title":"Digital dynamic modeling and topology optimized design of shell face mills","authors":"E. Ulular , Y. Altintas , A. Liljerehn","doi":"10.1016/j.cirpj.2024.10.005","DOIUrl":"10.1016/j.cirpj.2024.10.005","url":null,"abstract":"<div><div>This paper presents digital modeling of shell face mills in milling cylinder heads. The cutter's structural dynamics and its mode shapes are predicted using a Finite Element system. The geometries of the cutter body and inserts are imported from their Computer Aided Design (CAD) models. The insert edge is discretized into small segments to model its varying normal rake and inclination angles, which affect the cutting mechanics. The cutter is dynamically assembled with the target machine tool spindle using the receptance coupling method. A general dynamic cutting force model, which considers the varying edge geometry and inserts’ run-outs, is developed and used to predict cutting forces and chatter stability diagrams. The proposed model is experimentally verified to demonstrate the feasibility of the systematic application of physics-based digital design and analysis of tools for the mass machining of specific parts. The cutter body shape is optimized to increase the stiffness of the bending mode shape that caused chatter via topology optimization, which led to five-fold increase in the absolute stable depth of cut.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 308-321"},"PeriodicalIF":4.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-10-22DOI: 10.1016/j.cirpj.2024.10.002
Florian Stamer , Roman Girke , Shun Yang , Jung-Hoon Chun , Gisela Lanza
In the realm of production systems, determining the optimal segment allocation remains a central concern. While several existing models address this issue, a significant gap remains as many overlook the critical role of innovation and lack a holistic perspective. This paper presents a model that emphasizes innovation capabilities and introduces the concept of a “Technology Multiplier” underscoring the compounding influence of technology and innovation on production segment allocation decisions. Within this work, we focus on preliminary studies to establish the “Technology Multiplier” concept employing an Analytical Hierarchy Process (AHP) with sensitivity analysis. The validity of our approach is demonstrated through four case studies from three industries, illustrating the relevance of our elaborated metrics for the concept of “Technology Multipliers”. In particular, a leading automotive company uses our findings to reach a more appropriate strategic decision aligned with innovation and production growth, compared to its previous decisions. These results not only demonstrate a robust fit with our proposed metrics but also indicate that our framework lays the foundation for further research on the “Technology Multiplier”, enriching the decision-making process for production segment allocation.
{"title":"Effect of technology multiplier: A framework for analysis of innovation perspectives on production segment allocation","authors":"Florian Stamer , Roman Girke , Shun Yang , Jung-Hoon Chun , Gisela Lanza","doi":"10.1016/j.cirpj.2024.10.002","DOIUrl":"10.1016/j.cirpj.2024.10.002","url":null,"abstract":"<div><div>In the realm of production systems, determining the optimal segment allocation remains a central concern. While several existing models address this issue, a significant gap remains as many overlook the critical role of innovation and lack a holistic perspective. This paper presents a model that emphasizes innovation capabilities and introduces the concept of a “Technology Multiplier” underscoring the compounding influence of technology and innovation on production segment allocation decisions. Within this work, we focus on preliminary studies to establish the “Technology Multiplier” concept employing an Analytical Hierarchy Process (AHP) with sensitivity analysis. The validity of our approach is demonstrated through four case studies from three industries, illustrating the relevance of our elaborated metrics for the concept of “Technology Multipliers”. In particular, a leading automotive company uses our findings to reach a more appropriate strategic decision aligned with innovation and production growth, compared to its previous decisions. These results not only demonstrate a robust fit with our proposed metrics but also indicate that our framework lays the foundation for further research on the “Technology Multiplier”, enriching the decision-making process for production segment allocation.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 272-291"},"PeriodicalIF":4.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-22DOI: 10.1016/j.cirpj.2024.10.006
Peng Chen, Sanmin Wang
This paper presents an innovative digital tooth surface precision control model(DTS-PCM) for spiral bevel gears, focusing on the contact parameters derived from the surface synthesis method(SSM) and the pinion tooth surface contact control parameters under Gleason expert manufacturing system(GEMS). This model enables the direct derivation of tooth cutting adjustment parameters for Gleason machine tools, facilitating a seamless integration of design theory with practical processing. Firstly, a novel method for accurately determining the curvature parameters of pinion tooth surfaces, based on predefined contact parameters, has been developed using ease-off topology. Then, based on the pinion gear cutting pitch cone model, a coupled tooth line vector transformation model is proposed to calculate the principal curvature parameters of the nodes. Additionally, a set of equations for the pinion tooth surface contact control parameters is derived, and a formula for calculating the pinion gear cutting adjustment parameters is provided. Finally, two sets of pinion tooth surface contact control parameters were obtained using DTS-PCM: the calculated tooth contact analysis(TCA) and ease-of-topology results. The findings demonstrate that the proposed method is largely consistent with the outcomes of the GEMS calculations, thereby validating the accuracy of DTS-PCM. This indicates that the method can be directly integrated with GEMS software, facilitating practical applications that shorten the design and processing cycle.
{"title":"Digital tooth surface precision control model in spiral bevel gear processing through surface synthesis method combined with GEMS","authors":"Peng Chen, Sanmin Wang","doi":"10.1016/j.cirpj.2024.10.006","DOIUrl":"10.1016/j.cirpj.2024.10.006","url":null,"abstract":"<div><div>This paper presents an innovative digital tooth surface precision control model(DTS-PCM) for spiral bevel gears, focusing on the contact parameters derived from the surface synthesis method(SSM) and the pinion tooth surface contact control parameters under Gleason expert manufacturing system(GEMS). This model enables the direct derivation of tooth cutting adjustment parameters for Gleason machine tools, facilitating a seamless integration of design theory with practical processing. Firstly, a novel method for accurately determining the curvature parameters of pinion tooth surfaces, based on predefined contact parameters, has been developed using ease-off topology. Then, based on the pinion gear cutting pitch cone model, a coupled tooth line vector transformation model is proposed to calculate the principal curvature parameters of the nodes. Additionally, a set of equations for the pinion tooth surface contact control parameters is derived, and a formula for calculating the pinion gear cutting adjustment parameters is provided. Finally, two sets of pinion tooth surface contact control parameters were obtained using DTS-PCM: the calculated tooth contact analysis(TCA) and ease-of-topology results. The findings demonstrate that the proposed method is largely consistent with the outcomes of the GEMS calculations, thereby validating the accuracy of DTS-PCM. This indicates that the method can be directly integrated with GEMS software, facilitating practical applications that shorten the design and processing cycle.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 292-307"},"PeriodicalIF":4.6,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-10-21DOI: 10.1016/j.cirpj.2024.10.004
Saliha Karadayi-Usta
The Additive Manufacturing (AM) industry is of paramount importance as means of personalized design capabilities by rapid prototyping, using exact amount of required materials avoiding waste, and applying Industry 4.0 technologies with digital transformation ability. The characteristics of AM are regarded as the prerequisites for sustainability in the manufacturing industry. However, there are limited papers discussing the stakeholders and sustainability objectives in a single comprehensive analysis. Hence, the purpose of this research is to identify the degree of each stakeholder to achieve the objective of sustainability in AM supply chain by proposing a novel Plithogenic Fuzzy MACTOR approach. Results reveal that the customers are in triggering position to shape entire AM supply chain as the demand generators. Workforce is a significant player in the AM supply chain by creating the design, manufacturing, marketing, and communicating to provide the collaborations in this business segment. Academia positions here a supportive role to enable the whole supply chain members in terms of delivering technological advancements, training people, and providing the workforce. The AM manufacturers and material / software / printer suppliers are the key players leading to the supply chain by producing the main business products. Thus, a practitioner can interpret its position in the AM supply chain and understand the requirements of sustainability points in detail. Besides, this study provides a theoretical contribution to the literature by extending the MACTOR analysis with Plithogenic sets via including a different uncertainty measure.
快速成型制造（AM）工业作为通过快速原型设计实现个性化设计能力、使用精确数量的所需材料避免浪费以及应用具有数字化转型能力的工业 4.0 技术的手段，具有极其重要的意义。AM 的特性被视为制造业可持续发展的先决条件。然而，通过单一的综合分析来讨论利益相关者和可持续发展目标的论文却非常有限。因此，本研究的目的是通过提出一种新颖的 Plithogenic Fuzzy MACTOR 方法，确定各利益相关者对实现 AM 供应链可持续发展目标的影响程度。研究结果表明，客户作为需求产生者，对整个 AM 供应链的形成具有触发作用。劳动力在 AM 供应链中扮演着重要角色，他们创造设计、制造、营销和交流，为这一业务领域提供合作。学术界在提供技术进步、培训人员和提供劳动力方面发挥着支持整个供应链成员的作用。AM 制造商和材料/软件/打印机供应商是供应链的主要参与者，生产主要的商业产品。因此，从业人员可以解释其在 AM 供应链中的位置，并详细了解可持续性要点的要求。此外，本研究还通过加入不同的不确定性度量，将 MACTOR 分析与 Plithogenic 集进行了扩展，从而为相关文献做出了理论贡献。
{"title":"Sustainable additive manufacturing supply chains with a plithogenic stakeholder analysis: Waste reduction through digital transformation","authors":"Saliha Karadayi-Usta","doi":"10.1016/j.cirpj.2024.10.004","DOIUrl":"10.1016/j.cirpj.2024.10.004","url":null,"abstract":"<div><div>The Additive Manufacturing (AM) industry is of paramount importance as means of personalized design capabilities by rapid prototyping, using exact amount of required materials avoiding waste, and applying Industry 4.0 technologies with digital transformation ability. The characteristics of AM are regarded as the prerequisites for sustainability in the manufacturing industry. However, there are limited papers discussing the stakeholders and sustainability objectives in a single comprehensive analysis. Hence, the purpose of this research is to identify the degree of each stakeholder to achieve the objective of sustainability in AM supply chain by proposing a novel Plithogenic Fuzzy MACTOR approach. Results reveal that the customers are in triggering position to shape entire AM supply chain as the demand generators. Workforce is a significant player in the AM supply chain by creating the design, manufacturing, marketing, and communicating to provide the collaborations in this business segment. Academia positions here a supportive role to enable the whole supply chain members in terms of delivering technological advancements, training people, and providing the workforce. The AM manufacturers and material / software / printer suppliers are the key players leading to the supply chain by producing the main business products. Thus, a practitioner can interpret its position in the AM supply chain and understand the requirements of sustainability points in detail. Besides, this study provides a theoretical contribution to the literature by extending the MACTOR analysis with Plithogenic sets via including a different uncertainty measure.</div></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"55 ","pages":"Pages 261-271"},"PeriodicalIF":4.6,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142531514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2024-10-19DOI: 10.1016/j.cirpj.2024.10.007
Nicolas Béraud, Yann Ledoux, El-Haddi Mechekour, Frédéric Vignat, Franck Pourroy
Managing the quality of parts produced by the Wire Arc Additive Manufacturing (WAAM) process presents a significant challenge, particularly due to the complexity of thermal control. Effective thermal management is crucial for minimizing defects, making fast and accurate thermal simulations essential for testing and optimizing various manufacturing strategies. This article proposes a rapid simulation that decouples the calculation of heat conduction from convection and radiation. The proposed simulation is described and validated against experimental data. The influences of spatial and temporal discretization are examined. In conclusion, this developed approach provides a fast and efficient simulation of a manufacturing strategy for improvement.
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