Pub Date : 2024-08-28DOI: 10.1177/1063293x241277189
Thinh Quy-Duc Pham, Van-Xuan Tran
This study employs a deep learning (DL) based stochastic approach to comprehensively interpret the effects of current intensity and velocity variations on temperature evolutions and cooling rates in the wire arc additive manufacturing (WAAM) process of a thin wall. Uncertainty raised from process parameters, material properties, and environmental conditions significantly impacts the final product quality. Furthermore, understanding the relationship between the process and temperature evolution within the WAAM process is complex. This study contributes to quantifying the uncertainty to the final product quality, such as temperature evolutions and cooling rates via a fast and accurate DL-based surrogate model. This contribution helps to precise adjustments and optimizations to enhance the overall WAAM process. Initially, a DL-based surrogate model is constructed using data obtained from a high-fidelity validated finite element (FE) model, ensuring an impressive 99% accuracy compared to the FE model while reducing computational costs. Subsequently, probabilistic methods are used to characterize uncertainties in current intensity and velocity, and the Monte-Carlo method is applied for uncertainty propagation. The findings illustrate that small variations in the input parameters can lead to significant fluctuations in temperature evolutions. Additionally, a sensitivity analysis is conducted to precisely quantify the influence of each input parameter. Finally, an uncertainty reduction is performed to enhance the variation of cooling rate. In general, this study is expected to make precise adjustments and optimizations to enhance the overall WAAM process for better quality of printed piece.
{"title":"Sensitivity study of process parameters of wire arc additive manufacturing using probabilistic deep learning and uncertainty quantification","authors":"Thinh Quy-Duc Pham, Van-Xuan Tran","doi":"10.1177/1063293x241277189","DOIUrl":"https://doi.org/10.1177/1063293x241277189","url":null,"abstract":"This study employs a deep learning (DL) based stochastic approach to comprehensively interpret the effects of current intensity and velocity variations on temperature evolutions and cooling rates in the wire arc additive manufacturing (WAAM) process of a thin wall. Uncertainty raised from process parameters, material properties, and environmental conditions significantly impacts the final product quality. Furthermore, understanding the relationship between the process and temperature evolution within the WAAM process is complex. This study contributes to quantifying the uncertainty to the final product quality, such as temperature evolutions and cooling rates via a fast and accurate DL-based surrogate model. This contribution helps to precise adjustments and optimizations to enhance the overall WAAM process. Initially, a DL-based surrogate model is constructed using data obtained from a high-fidelity validated finite element (FE) model, ensuring an impressive 99% accuracy compared to the FE model while reducing computational costs. Subsequently, probabilistic methods are used to characterize uncertainties in current intensity and velocity, and the Monte-Carlo method is applied for uncertainty propagation. The findings illustrate that small variations in the input parameters can lead to significant fluctuations in temperature evolutions. Additionally, a sensitivity analysis is conducted to precisely quantify the influence of each input parameter. Finally, an uncertainty reduction is performed to enhance the variation of cooling rate. In general, this study is expected to make precise adjustments and optimizations to enhance the overall WAAM process for better quality of printed piece.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221632","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 : 2024-08-21DOI: 10.1177/1063293x241266338
Ferdaws Ben Naceur, Sana Toumi, Chokri Ben Salah, Mohamed Ali Mahjoub, Mehdi Tlija
This paper describes a decentralised smart grid system containing renewable energies, storage systems and distributed generation with human control and intervention. The importance of each element and the interaction between them leads to think about a decision-making strategy. In fact, the integration of a Photovoltaic Panel (PVP) is used due to its availability and its participation in the carbon emissions reduction. Also, a battery is required to fill a power gap or absorb extra generated energy. Moreover, an optimal sizing is needed to get an efficient system with minimum cost. Also, an energy management strategy (EMS) is essential to ensure the power resources scheduling in order to keep a continuous equilibrium supply-demand of electricity and avoid instabilities in the grid, with guaranteeing a minimum cost of electricity. In the first part, the proposed smart grid optimal sizing is determined under real weather data (solar radiation) of the city of Sousse, Tunisia, using the Hybrid Optimization of Multiple Energy Resources (HOMER) software technique. This approach is chosen thanks to its simplicity, effectiveness, and high precision compared to traditional techniques. In this paper, several configurations (Grid, (Grid-battery), (Grid-PVP), (Grid-PVP-battery)) are studied. The obtained results prove that the (Grid-PVP-battery) system configuration is the most efficient and economical solution. In the second part, a robust energy management strategy (EMS) is proposed for two smart grid configurations (grid-battery, grid-PVP-battery). This strategy is based on Fuzzy Logic Control (FLC) thanks to its non-linear modelling and its ability to make decisions relating to energy management. The primary goal of the suggested (EMS) is to ensure the energy resources scheduling in order to keep a continuous equilibrium among the production and consumption of electricity and avoid instabilities in the grid, with guaranteeing a minimum cost of electricity. As input data, (FLC) used time-varying price electricity (Price (t)) to solve an instant decision problem by choosing, at each instant, the optimal energy source (which provide electricity at the cheapest price possible). The obtained results, carrying out Matlab simulation, prove the efficacy of the proposed strategy, not only, in the energy resources scheduling to meet the load, but also, for the system cost reduction since the PVP has been used as much as possible since it is inexpensive relative to the costs of battery capacity and the grid.
{"title":"Decision-making solutions based artificial intelligence and hybrid software for optimal sizing and energy management in a smart grid system","authors":"Ferdaws Ben Naceur, Sana Toumi, Chokri Ben Salah, Mohamed Ali Mahjoub, Mehdi Tlija","doi":"10.1177/1063293x241266338","DOIUrl":"https://doi.org/10.1177/1063293x241266338","url":null,"abstract":"This paper describes a decentralised smart grid system containing renewable energies, storage systems and distributed generation with human control and intervention. The importance of each element and the interaction between them leads to think about a decision-making strategy. In fact, the integration of a Photovoltaic Panel (PVP) is used due to its availability and its participation in the carbon emissions reduction. Also, a battery is required to fill a power gap or absorb extra generated energy. Moreover, an optimal sizing is needed to get an efficient system with minimum cost. Also, an energy management strategy (EMS) is essential to ensure the power resources scheduling in order to keep a continuous equilibrium supply-demand of electricity and avoid instabilities in the grid, with guaranteeing a minimum cost of electricity. In the first part, the proposed smart grid optimal sizing is determined under real weather data (solar radiation) of the city of Sousse, Tunisia, using the Hybrid Optimization of Multiple Energy Resources (HOMER) software technique. This approach is chosen thanks to its simplicity, effectiveness, and high precision compared to traditional techniques. In this paper, several configurations (Grid, (Grid-battery), (Grid-PVP), (Grid-PVP-battery)) are studied. The obtained results prove that the (Grid-PVP-battery) system configuration is the most efficient and economical solution. In the second part, a robust energy management strategy (EMS) is proposed for two smart grid configurations (grid-battery, grid-PVP-battery). This strategy is based on Fuzzy Logic Control (FLC) thanks to its non-linear modelling and its ability to make decisions relating to energy management. The primary goal of the suggested (EMS) is to ensure the energy resources scheduling in order to keep a continuous equilibrium among the production and consumption of electricity and avoid instabilities in the grid, with guaranteeing a minimum cost of electricity. As input data, (FLC) used time-varying price electricity (Price (t)) to solve an instant decision problem by choosing, at each instant, the optimal energy source (which provide electricity at the cheapest price possible). The obtained results, carrying out Matlab simulation, prove the efficacy of the proposed strategy, not only, in the energy resources scheduling to meet the load, but also, for the system cost reduction since the PVP has been used as much as possible since it is inexpensive relative to the costs of battery capacity and the grid.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"30 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142221633","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 : 2023-11-03DOI: 10.1177/1063293x231213510
Mélick Proulx, Mickaël Gardoni
Innovation, open innovation, and collaborative platforms are concepts in effervescence in the last few years. Innovation’s future will observe a growing number of collaborations. The links between collaboration and collaborative platforms are known in the transport and accommodation sector (such as Uber) however are less used in manufacturing. This paper aims to identify the main challenges between manufacturing firms which intend to collaborate enabled by a prototype platform. A collaborative business model was designed using the business model canvas and tested using a real case to generate valuable collaboration. Collaboration experimentation was monitored over 21 weeks between two firms of the Quebec aerospace cluster and ended with a semi-structured interview. Six challenges were identified: partner selection, commitment and trust, intellectual property management, collaboration evaluation, collaboration symmetry and terminology difficulties. Suggested solutions included, compatibility criteria between the partners, creating a vocabulary lexicon, and establishing collaboration expectations prior to collaboration.
{"title":"Harness collaboration between manufacturing Small and medium-sized enterprises through a collaborative platform based on the business model canvas","authors":"Mélick Proulx, Mickaël Gardoni","doi":"10.1177/1063293x231213510","DOIUrl":"https://doi.org/10.1177/1063293x231213510","url":null,"abstract":"Innovation, open innovation, and collaborative platforms are concepts in effervescence in the last few years. Innovation’s future will observe a growing number of collaborations. The links between collaboration and collaborative platforms are known in the transport and accommodation sector (such as Uber) however are less used in manufacturing. This paper aims to identify the main challenges between manufacturing firms which intend to collaborate enabled by a prototype platform. A collaborative business model was designed using the business model canvas and tested using a real case to generate valuable collaboration. Collaboration experimentation was monitored over 21 weeks between two firms of the Quebec aerospace cluster and ended with a semi-structured interview. Six challenges were identified: partner selection, commitment and trust, intellectual property management, collaboration evaluation, collaboration symmetry and terminology difficulties. Suggested solutions included, compatibility criteria between the partners, creating a vocabulary lexicon, and establishing collaboration expectations prior to collaboration.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"41 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135873683","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 : 2023-10-30DOI: 10.1177/1063293x231211517
Yuanfa Dong, Xiaocan Li, Wei Peng, Lei Wang, Bin Zhou
Monitoring and evaluating the health of the cloud manufacturing service ecosystem (CMSE) is critical to ensuring the long-term development of the cloud manufacturing service platform. The behavior patterns of three types of market entities, service demander (SD), service provider (SP) and platform operator (PO), have an important impact on the evolution trend of CMSE. The formulation of platform transaction rules and development of operation and regulation strategies need clarified the evolution law of the CMSE. Therefore, the evolution framework of the CMSE is constructed, the behavior modes of market entities such as SP, SD, and PO are established respectively, and multi-agent behavior simulation experiments are carried out. Simulation analysis showed that the more sensitive the SP was to the transaction activity in the system, the earlier the ecosystem in which it was located enters the stable period. When the sensitivity k of SD to the number of SPs that are available for required services in the system was between 0.45 and 0.5, the evolution trend of CMSE would show an obvious turning point from rapid growth to shrinkage. PO could adopt flexible charging strategies at different stages of the evolution of the CMSE to maximize revenue.
{"title":"Research on the evolution law of cloud manufacturing service ecosystem based on multi-agent behavior simulation","authors":"Yuanfa Dong, Xiaocan Li, Wei Peng, Lei Wang, Bin Zhou","doi":"10.1177/1063293x231211517","DOIUrl":"https://doi.org/10.1177/1063293x231211517","url":null,"abstract":"Monitoring and evaluating the health of the cloud manufacturing service ecosystem (CMSE) is critical to ensuring the long-term development of the cloud manufacturing service platform. The behavior patterns of three types of market entities, service demander (SD), service provider (SP) and platform operator (PO), have an important impact on the evolution trend of CMSE. The formulation of platform transaction rules and development of operation and regulation strategies need clarified the evolution law of the CMSE. Therefore, the evolution framework of the CMSE is constructed, the behavior modes of market entities such as SP, SD, and PO are established respectively, and multi-agent behavior simulation experiments are carried out. Simulation analysis showed that the more sensitive the SP was to the transaction activity in the system, the earlier the ecosystem in which it was located enters the stable period. When the sensitivity k of SD to the number of SPs that are available for required services in the system was between 0.45 and 0.5, the evolution trend of CMSE would show an obvious turning point from rapid growth to shrinkage. PO could adopt flexible charging strategies at different stages of the evolution of the CMSE to maximize revenue.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136104734","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 : 2023-10-26DOI: 10.1177/1063293x231209680
Mayara Silvestre De Oliveira, Guilherme Fidelis Peixer, Fernando Antônio Forcellini, Jader Riso Barbosa, Jaime Andrés Lozano Cadena
The literature acknowledges the advantages of Set-Based Concurrent Engineering (SBCE), but there is a lack of models for its adoption and documented cases of its implementation, mostly on products with consolidated technology, which raises the possibility of expanding SBCE for highly innovative products. These projects often have extensive resource limitations, leading to computational tools and mathematical modelling as fundamental sources of information. This paper proposes a method for model-based Trade-off Curves (ToC) generation to support SBCE. We adopted it to develop a magnetic air conditioner. The use of model-based ToC enabled the narrowing of the design space and monitoring of the design parameters and performance metrics and enabled SBCE adoption in the design process. The main contributions of this research are presenting the state-of-the-art in ToC generation and application, proposing the model, and demonstrating SBCE in highly innovative projects, while its importance lies in the opportunity to further disseminate SBCE to different development environments.
{"title":"Model-based trade-off curves to support the set-based concurrent engineering of highly innovative projects","authors":"Mayara Silvestre De Oliveira, Guilherme Fidelis Peixer, Fernando Antônio Forcellini, Jader Riso Barbosa, Jaime Andrés Lozano Cadena","doi":"10.1177/1063293x231209680","DOIUrl":"https://doi.org/10.1177/1063293x231209680","url":null,"abstract":"The literature acknowledges the advantages of Set-Based Concurrent Engineering (SBCE), but there is a lack of models for its adoption and documented cases of its implementation, mostly on products with consolidated technology, which raises the possibility of expanding SBCE for highly innovative products. These projects often have extensive resource limitations, leading to computational tools and mathematical modelling as fundamental sources of information. This paper proposes a method for model-based Trade-off Curves (ToC) generation to support SBCE. We adopted it to develop a magnetic air conditioner. The use of model-based ToC enabled the narrowing of the design space and monitoring of the design parameters and performance metrics and enabled SBCE adoption in the design process. The main contributions of this research are presenting the state-of-the-art in ToC generation and application, proposing the model, and demonstrating SBCE in highly innovative projects, while its importance lies in the opportunity to further disseminate SBCE to different development environments.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134908327","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 : 2023-09-01DOI: 10.1177/1063293x231220717
{"title":"Call for guest editors for special issues in: Concurrent engineering: Research and applications","authors":"","doi":"10.1177/1063293x231220717","DOIUrl":"https://doi.org/10.1177/1063293x231220717","url":null,"abstract":"","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"9 1","pages":"139 - 139"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139343521","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 : 2023-09-01DOI: 10.1177/1063293X231217543
E. L. Synnes, T. Welo
This paper investigates concerns related to product data and digital data flow when aiming to automate company processes. Accurate data is necessary to create value by enabling improved decision-making in product development, including sustainability capabilities. The case analyzed is an engineer-to-order (ETO) company operating in a low-volume marine manufacturing context. A participatory research approach is used to study two projects that are part of the company’s digital business transformation, aiming to digitalize information and autogenerate downstream processes. Building on the strengths promised by digitalization requires precise and extensive product and process information. An important facilitation capability is to create a digital thread from design to finished product, including product documentation. This is necessary to establish capabilities both to autogenerate appropriate compliance reporting as part of the product development process and to conduct virtual testing and validation before the physical equipment is acquired, resulting in a manufacturing process that is ‘right first time’. In addition, data capabilities guide and enable sound-decision making for improved sustainable practices in the early phase of product development. It is found that the data quality required to utilize tools within the context of Industry 4.0 demands changes to existing product design practices and focus on the three pillars harmonization, integration and automation of data and systems.
{"title":"Data-driven product optimization capabilities to enhance sustainability and environmental compliance in a marine manufacturing context","authors":"E. L. Synnes, T. Welo","doi":"10.1177/1063293X231217543","DOIUrl":"https://doi.org/10.1177/1063293X231217543","url":null,"abstract":"This paper investigates concerns related to product data and digital data flow when aiming to automate company processes. Accurate data is necessary to create value by enabling improved decision-making in product development, including sustainability capabilities. The case analyzed is an engineer-to-order (ETO) company operating in a low-volume marine manufacturing context. A participatory research approach is used to study two projects that are part of the company’s digital business transformation, aiming to digitalize information and autogenerate downstream processes. Building on the strengths promised by digitalization requires precise and extensive product and process information. An important facilitation capability is to create a digital thread from design to finished product, including product documentation. This is necessary to establish capabilities both to autogenerate appropriate compliance reporting as part of the product development process and to conduct virtual testing and validation before the physical equipment is acquired, resulting in a manufacturing process that is ‘right first time’. In addition, data capabilities guide and enable sound-decision making for improved sustainable practices in the early phase of product development. It is found that the data quality required to utilize tools within the context of Industry 4.0 demands changes to existing product design practices and focus on the three pillars harmonization, integration and automation of data and systems.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"2013 1","pages":"113 - 125"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139344058","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 : 2023-06-01DOI: 10.1177/1063293x221144305
Qing Yang, Pingye Tian
The research in relation to new product development (NPD) project management has been very rich in the past decade. However, there has been a lack of quantitative literature reviews investigating the status and evolution of research. In this study, we aimed to fill this gap by reviewing the NPD project management literature in the SCI-E and SSCI databases from 2012 to 2021 using the bibliometric method and the CiteSpace tool. First, we provided an overview of publications and identified several leading journals. Second, based on a keyword co-occurrence network, we identified five important research themes in NPD project management: optimization and simulation, knowledge management, product innovation, performance and success factors, and development strategy and firm strategy. Furthermore, we reviewed the important literature relating to each theme. Third, we analyzed the evolution of the NPD project management literature, as well as identifying research hotpots in the last 10 years, by creating a keyword time zone network. Finally, we proposed future trends in NPD project management research to fill the existing gaps.
{"title":"New product development project management: Insights and research tendency from a bibliometric-based literature review","authors":"Qing Yang, Pingye Tian","doi":"10.1177/1063293x221144305","DOIUrl":"https://doi.org/10.1177/1063293x221144305","url":null,"abstract":"The research in relation to new product development (NPD) project management has been very rich in the past decade. However, there has been a lack of quantitative literature reviews investigating the status and evolution of research. In this study, we aimed to fill this gap by reviewing the NPD project management literature in the SCI-E and SSCI databases from 2012 to 2021 using the bibliometric method and the CiteSpace tool. First, we provided an overview of publications and identified several leading journals. Second, based on a keyword co-occurrence network, we identified five important research themes in NPD project management: optimization and simulation, knowledge management, product innovation, performance and success factors, and development strategy and firm strategy. Furthermore, we reviewed the important literature relating to each theme. Third, we analyzed the evolution of the NPD project management literature, as well as identifying research hotpots in the last 10 years, by creating a keyword time zone network. Finally, we proposed future trends in NPD project management research to fill the existing gaps.","PeriodicalId":10680,"journal":{"name":"Concurrent Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135146057","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}
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