Journal of Manufacturing Technology Management最新文献

{"title":"Utilizing organizational ambidexterity to implement long-term technical change in fast-paced manufacturing settings","authors":"Anna Sannö, Sandra Rothenberg, Ezekiel Leo","doi":"10.1108/jmtm-07-2023-0268","DOIUrl":"https://doi.org/10.1108/jmtm-07-2023-0268","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>In this paper, we focus on how and when organizations adopt different types of ambidexterity to facilitate projects that operate with fundamentally different time scales compared with the dominant functions of the organization.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>Using a comparative case study design, four case studies were conducted of long-term projects in two similar manufacturing plants within the same organization.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>We found organizations first use structural and sequential ambidexterity in change efforts, during which new process knowledge is developed. When structural and sequential ambidexterity are not viable, change agents use this developed knowledge to support contextual ambidexterity. This contextual ambidexterity allows change agents to move between distinct time conceptions of event time and clock time.</p><!--/ Abstract__block -->\u0000<h3>Research limitations/implications</h3>\u0000<p>One of the limitations of this study was that it only focused on two plants within one organization in order to control for variation. Future studies should look at a wider range of companies, technologies and industries.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>While structurally and temporally decoupling change efforts help with differentiation of new technological change, there are limitations with these efforts. It is important to build an organization’s contextual ambidexterity as well as organizational supports to facilitate switching between clock time and event time.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This paper helps explain how and when organizations use different types of ambidexterity in resolving temporal conflicts when implementing longer-term technological change in fast-paced manufacturing settings.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576898","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}

{"title":"Lean and industry 4.0 principles toward industry 5.0: a conceptual framework and empirical insights from fashion industry","authors":"Virginia Fani, Ilaria Bucci, Monica Rossi, Romeo Bandinelli","doi":"10.1108/jmtm-11-2023-0509","DOIUrl":"https://doi.org/10.1108/jmtm-11-2023-0509","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Examining synergies between Lean, Industry 4.0, and Industry 5.0 principles, the aim is to showcase how Lean's focus on people enhances Industry 5.0 implementations, leading to the development of the Lean 5.0 paradigm. In addition, insights from artisanal industries, like the fashion one, are specifically collected.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>First, a literature review was conducted to define a comprehensive framework to understand how Lean fits into the Human-Centric (HC) paradigm of Industry 5.0. Second, a case study was employed to give empirical insights and identify practical initiatives that brands can pursue, involving two best-in-class leather goods brands located in Italy.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>A conceptual framework to pave the way for new paradigm Lean 5.0 was defined and validated through a case study. To path the way for a case study in the fashion industry, the Lean HC paradigm is detailed into domains and related categories to group practices. The empirical insights demonstrate that Lean HC actions can be effectively supported by Industry 4.0 technologies in traditional sectors like the fashion industry, shifting towards Industry 5.0.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The proposed framework and related practices can be used by companies to facilitate their transition towards Industry 5.0, leveraging on Lean Manufacturing.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>The innovative contribution of the present work mainly refers to the proposed conceptual framework, encompassing Lean, HC and Industry 4.0 and introducing Lean 5.0 paradigm. The case study enriches the empirical contributions in the fashion industry.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141576895","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}

{"title":"Unleashing the power of cloud adoption and artificial intelligence in optimizing resilience and sustainable manufacturing supply chain in the USA","authors":"Aamir Rashid, Rizwana Rasheed, Abdul Hafaz Ngah, Noor Aina Amirah","doi":"10.1108/jmtm-02-2024-0080","DOIUrl":"https://doi.org/10.1108/jmtm-02-2024-0080","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Recent disruptions have sparked concern about building a resilient and sustainable manufacturing supply chain. While artificial intelligence (AI) strengthens resilience, research is needed to understand how cloud adoption can foster integration, collaboration, adaptation and sustainable manufacturing. Therefore, this study aimed to unleash the power of cloud adoption and AI in optimizing resilience and sustainable performance through collaboration and adaptive capabilities at manufacturing firms.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>This research followed a deductive approach and employed a quantitative method with a survey technique to collect data from its target population. The study used stratified random sampling with a sample size of 1,279 participants working in diverse manufacturing industries across California, Texas and New York.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>This research investigated how companies can make their manufacturing supply chains more resilient and sustainable. The findings revealed that integrating the manufacturing supply chains can foster collaboration and enhance adaptability, leading to better performance (hypotheses H1-H7, except H5). Additionally, utilizing artificial intelligence helps improve adaptability, further strengthening resilience and sustainability (H8-H11). Interestingly, the study found that internal integration alone does not significantly impact collaboration (H5). This suggests that external factors are more critical in fostering collaboration within the manufacturing supply chain during disruptions.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This study dives into the complex world of interconnected factors (formative constructs in higher order) influencing manufacturing supply chains. Using advanced modeling techniques, it highlights the powerful impact of cloud-based integration. Cloud-based integration and artificial intelligence unlock significant improvements for manufacturers and decision-makers by enabling information processes and dynamic capability theory.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141529127","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}

{"title":"Linking dynamic capability with mass customization capability: the mediating role of supply chain resilience","authors":"Haiqing Shi, Taiwen Feng, Lucheng Chen, Xiaoping Lu","doi":"10.1108/jmtm-06-2023-0246","DOIUrl":"https://doi.org/10.1108/jmtm-06-2023-0246","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Despite the growing interest in enhancing mass customization capability (MCC), firms still have little knowledge of dealing with the superimposed challenges of increased market uncertainty and supply chain disruptions. Based on the dynamic capability view, this study focuses on the impacts of frequent sensing and reconfiguring processes on MCC and the mediating roles of proactive and reactive supply chain resilience (SCR).</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>We collected survey data from 277 manufacturing firms and conducted a structural equation model to test hypotheses.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The results reveal that although its direct effect on MCC is insignificant, sensing process improves MCC indirectly via reactive SCR. Our findings also show that reconfiguring process enhances MCC both directly and indirectly via reactive SCR.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This study provides theoretical and practical insights into how to combine dynamic capability and SCR to strengthen MCC.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505202","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}

{"title":"Supply chain resilience and international manufacturing strategy: a case study from the semiconductor industry","authors":"Lukas Fleisch, Oliver von Dzengelevski","doi":"10.1108/jmtm-03-2023-0091","DOIUrl":"https://doi.org/10.1108/jmtm-03-2023-0091","url":null,"abstract":"PurposeThis paper studies the interrelations between the concepts of supply chain resilience and international manufacturing strategy. On the basis of an in-depth case study of a company in the semiconductor industry, the paper seeks to integrate the concept of resilience into international manufacturing strategy.Design/methodology/approachIn an explorative qualitative single case study of a semiconductor manufacturer, a systems thinking model is developed from expert interviews and literature research that displays the interrelations of constituent constructs of supply chain resilience and international manufacturing strategy.FindingsForecast accuracy and organizational inertia are identified as barriers to resilience, whereas information technology (IT) capabilities and vertical integration are identified as major levers. Causal relations between constructs are identified, and a concrete suggestion for theory refinement of the manufacturing strategy framework of Miltenburg (2009) is provided.Originality/valuePrior literature on international manufacturing networks (IMNs) has not sufficiently taken into account the importance of resilience in the formulation of international manufacturing strategies. This paper aids in the integration of this increasingly important concept, in a critical industry that has recently been subject to major disruptions.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141344392","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}

{"title":"ChatGPT in supply chains: exploring potential applications, benefits and challenges","authors":"Abubaker Haddud","doi":"10.1108/jmtm-02-2024-0075","DOIUrl":"https://doi.org/10.1108/jmtm-02-2024-0075","url":null,"abstract":"PurposeWhile ChatGPT is gaining popularity, its potential role in supply chains (SCs) remains unexplored. This study explores the potential applications, benefits and challenges of using ChatGPT as a tool in SCs.Design/methodology/approachThe data were gathered through an online survey involving 116 respondents from the academic and industrial sectors who have knowledge of ChatGPT and SC management. These participants were affiliated with the Decision Science Institute (DSI) in the USA and contributed to the published DSI conference proceedings from 2019 to 2022. The survey is structured in three main sections: (1) general information (5 background questions), (2) ChatGPT's potential applications and benefits in SCs (15 pre-determined questions) and (3) potential challenges with using ChatGPT in SCs (5 pre-determined questions). The collected data underwent analysis using IBM SPSS Statistics software.FindingsChatGPT can potentially benefit SC operations in 15 areas. Eight potential benefits received more support than the rest, including enhanced process efficiency, cost reduction, providing sustainability reports, better demand forecasting, improved data analysis, streamlined supplier communication, streamlined customer communication, supported promotional activities and enhanced customer satisfaction, but all were supported. Also, the study identified some challenges and hurdles currently impacting the use of ChatGPT in the SC, including that ChatGPT cannot replace experts, it is not an immediate game changer, its uses may lack accuracy, and ChatGPT may take time to reach maturity.Originality/valueThe study is the first to offer empirically grounded evidence of ChatGPT's potential in SCs. The research enhances academic literature by deepening our comprehension of the potential applications of ChatGPT within SCs. Therefore, the study makes an invaluable contribution to the extant literature on ChatGPT in SCs. It can benefit manufacturers, suppliers, logistics providers and other types of businesses through more efficient procurement practices, supplier management, operations and inventory management, logistics practices and customer relationships. Future research may explore how and why ChatGPT is used in SCs.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141361751","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}

{"title":"Enablers for green lean six sigma adoption in the manufacturing industry","authors":"Monserrat Perez-Burgoin, Yolanda Baez-Lopez, Jorge Limon-Romero, Diego Tlapa, Jorge Luis García-Alcaraz","doi":"10.1108/jmtm-09-2023-0396","DOIUrl":"https://doi.org/10.1108/jmtm-09-2023-0396","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>The objective of this article is to identify the relationships between the enablers in the implementation of Green Lean Six Sigma (GLSS) in the Mexican manufacturing industry (MMI).</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>To create the survey instrument, the authors did an extensive literature research, which they then applied in the MMI to find the relationships between enablers and their impact on the positive effects of implementing GLSS projects. Using exploratory and confirmatory factor analyses (EFA and CFA), the data were empirically and statistically corroborated. Furthermore, the authors validated the hypotheses that support the research using the structural equation modeling (SEM) approach in SPSS Amos.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>The findings reveal that leadership has a positive impact on social and economic benefits (EcB), as well as an indirect impact on the environmental benefits (EB) of GLSS projects, with organizational involvement (OI) and performance measurement (PM) functioning as mediators.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>This study represents an empirical reference for practitioners and researchers pursuing high-quality, low-cost, environmentally and socially sustainable products or processes through the implementation of GLSS projects in the manufacturing industry.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This study provides a statistically validated model using the SEM technique to represent the relationships between GLSS enablers in the MMI.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141251908","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}

{"title":"The effect of green supply chain management practices on carbon-neutral supply chain performance: the mediating role of logistics eco-centricity","authors":"Farheen Naz, Ashutosh Samadhiya, Anil Kumar, Jose Arturo Garza-Reyes, Yigit Kazancoglu, Vikas Kumar, Arvind Upadhyay","doi":"10.1108/jmtm-09-2023-0401","DOIUrl":"https://doi.org/10.1108/jmtm-09-2023-0401","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>Using the lens of the natural resource-based view (NRBV) theory, this study investigates the effect of green supply chain management (GSCM) practices such as green manufacturing (GM), eco-design (ED), green purchasing (GP) and investment recovery (IR) on the carbon-neutral supply chain (CNSC) performance of firms through the mediating influence of logistics eco-centricity (LE).</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>A conceptual framework that hypothesizes the relationship between GSCM practices, LE and the CNSC performance of firms is developed. Key GSCM practices are then identified using experts’ opinions. Furthermore, we collected responses from logistics companies to validate the conceptual framework using the partial least squares structural equation modeling (PLS-SEM) method.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>Through this study, we found that GSCM practices significantly improve a firm's CNSC performance, and the relationships between GSCM practices and CNSC performance are positively mediated by LE.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>The implications of the study suggest that logistics managers can benefit from the findings of this study to comprehend the impact of various GSCM techniques on LE and CNSC from the viewpoint of the NRBV paradigm.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This research provides valuable perspectives for managers and supply chain (SC) practitioners in their quest for sustainable and environmentally responsible SC operations through an extensive and novel analysis of the connection between GSCM practices, LE and CNSC performance.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141166540","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}

{"title":"Generative artificial intelligence in manufacturing: opportunities for actualizing Industry 5.0 sustainability goals","authors":"Morteza Ghobakhloo, Masood Fathi, Mohammad Iranmanesh, Mantas Vilkas, Andrius Grybauskas, Azlan Amran","doi":"10.1108/jmtm-12-2023-0530","DOIUrl":"https://doi.org/10.1108/jmtm-12-2023-0530","url":null,"abstract":"<h3>Purpose</h3>\u0000<p>This study offers practical insights into how generative artificial intelligence (AI) can enhance responsible manufacturing within the context of Industry 5.0. It explores how manufacturers can strategically maximize the potential benefits of generative AI through a synergistic approach.</p><!--/ Abstract__block -->\u0000<h3>Design/methodology/approach</h3>\u0000<p>The study developed a strategic roadmap by employing a mixed qualitative-quantitative research method involving case studies, interviews and interpretive structural modeling (ISM). This roadmap visualizes and elucidates the mechanisms through which generative AI can contribute to advancing the sustainability goals of Industry 5.0.</p><!--/ Abstract__block -->\u0000<h3>Findings</h3>\u0000<p>Generative AI has demonstrated the capability to promote various sustainability objectives within Industry 5.0 through ten distinct functions. These multifaceted functions address multiple facets of manufacturing, ranging from providing data-driven production insights to enhancing the resilience of manufacturing operations.</p><!--/ Abstract__block -->\u0000<h3>Practical implications</h3>\u0000<p>While each identified generative AI function independently contributes to responsible manufacturing under Industry 5.0, leveraging them individually is a viable strategy. However, they synergistically enhance each other when systematically employed in a specific order. Manufacturers are advised to strategically leverage these functions, drawing on their complementarities to maximize their benefits.</p><!--/ Abstract__block -->\u0000<h3>Originality/value</h3>\u0000<p>This study pioneers by providing early practical insights into how generative AI enhances the sustainability performance of manufacturers within the Industry 5.0 framework. The proposed strategic roadmap suggests prioritization orders, guiding manufacturers in decision-making processes regarding where and for what purpose to integrate generative AI.</p><!--/ Abstract__block -->","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141173551","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}

{"title":"Driving success through digital transformation: influence of Industry 4.0 on lean, agile, resilient, green supply chain practices","authors":"Arsalan Zahid Piprani, Syed Abdul Rehman Khan, Zhang Yu","doi":"10.1108/jmtm-05-2023-0179","DOIUrl":"https://doi.org/10.1108/jmtm-05-2023-0179","url":null,"abstract":"PurposeGrowing emphasis on long-term viability prompts researchers and industry professionals to collaborate on innovative approaches for sustainability and survival. Industry 4.0 (I4.0) technology's importance drives active adoption by firms amidst evolving business dynamics. This research examines the influence of I4.0 technologies on lean, agile resilient and green practices and their impact on supply chain performance.Design/methodology/approachSurvey data from Pakistani manufacturing enterprises were analyzed using SMART PLS to explore the relationship between I4.0 technology, supply chain practices and supply chain performance.Findings I4.0 technologies significantly impact all practices, while agile and resilient supply chain approaches partially mediate the relationship with supply chain performance.Practical implicationsInsights from this research guide policymakers and business experts in implementing and managing lean, agile, resilient and green practices. Integrating these principles with digital technology solutions enhances supply chain performance.Originality/valueThis study advances understanding of the interplay between I4.0 technologies, practices and supply chain performance, providing a basis for further research and practical implications.","PeriodicalId":16301,"journal":{"name":"Journal of Manufacturing Technology Management","volume":null,"pages":null},"PeriodicalIF":7.6,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141102354","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}