Pub Date : 2024-07-26DOI: 10.3389/fieng.2024.1407367
Patrick Berger, Joerg von Garrel
This study investigates the diffusion of AI-based service applications within the business models of German manufacturing industries, surveying 162 decision-makers. The integration of AI into business model is assessed through the Business Model Canvas (BMC) framework, evaluating its value in terms of effectiveness as well as efficiency. Rather than focusing on specific use cases, the study delves into the intended usage of value-driven AI services references to enhance effectiveness and efficiency across various elements of the business models. Through this research, eleven service values have been identified. Each service vale corresponds to a distinct element of the BMC. Decision-makers were surveyed using a Confirmation/Disconfirmation (C/D) paradigm to measure the disparities between their current and target performance levels. Consequently, this study provides valuable insights from the perspective of decision makers regarding the current and desired state of AI integration in the German manufacturing industry, taking into account AI usage or no AI usage at the time of data collection.
{"title":"Diffusion of AI value-driven services in the German manufacturing industries—an empirical examination of value-driven service references classified by the business Model Canvas","authors":"Patrick Berger, Joerg von Garrel","doi":"10.3389/fieng.2024.1407367","DOIUrl":"https://doi.org/10.3389/fieng.2024.1407367","url":null,"abstract":"This study investigates the diffusion of AI-based service applications within the business models of German manufacturing industries, surveying 162 decision-makers. The integration of AI into business model is assessed through the Business Model Canvas (BMC) framework, evaluating its value in terms of effectiveness as well as efficiency. Rather than focusing on specific use cases, the study delves into the intended usage of value-driven AI services references to enhance effectiveness and efficiency across various elements of the business models. Through this research, eleven service values have been identified. Each service vale corresponds to a distinct element of the BMC. Decision-makers were surveyed using a Confirmation/Disconfirmation (C/D) paradigm to measure the disparities between their current and target performance levels. Consequently, this study provides valuable insights from the perspective of decision makers regarding the current and desired state of AI integration in the German manufacturing industry, taking into account AI usage or no AI usage at the time of data collection.","PeriodicalId":250772,"journal":{"name":"Frontiers in Industrial Engineering","volume":"48 50","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141799757","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 : 2024-07-19DOI: 10.3389/fieng.2024.1426631
Yagmur Atescan-Yuksek, John Patsavellas, Konstantinos Salonitis
In contemporary organizational landscapes, Equity, Diversity, and Inclusion (ED&I) stand as pivotal pillars for fostering innovation, resilience, and sustainable growth. This article explores the critical importance of ED&I within engineering organizations, focusing on the strategies for understanding ED&I dynamics, implementing inclusive environments, and extending ED&I principles through the industrial value chain. It investigates the complexities of individual identities, the significance of intersectionality, and the strategic advantage of diversity for organizational performance. By exploring comprehensive governance of ED&I initiatives, the role of leadership in fostering diversity, and the impact of ED&I on organizational sustainability and innovation, this study provides a holistic view of the challenges and opportunities in creating inclusive workplaces.
{"title":"Strategic implementation of ED&I: unveiling the multifaceted impact on innovation, governance, and ethical conduct in engineering organizations","authors":"Yagmur Atescan-Yuksek, John Patsavellas, Konstantinos Salonitis","doi":"10.3389/fieng.2024.1426631","DOIUrl":"https://doi.org/10.3389/fieng.2024.1426631","url":null,"abstract":"In contemporary organizational landscapes, Equity, Diversity, and Inclusion (ED&I) stand as pivotal pillars for fostering innovation, resilience, and sustainable growth. This article explores the critical importance of ED&I within engineering organizations, focusing on the strategies for understanding ED&I dynamics, implementing inclusive environments, and extending ED&I principles through the industrial value chain. It investigates the complexities of individual identities, the significance of intersectionality, and the strategic advantage of diversity for organizational performance. By exploring comprehensive governance of ED&I initiatives, the role of leadership in fostering diversity, and the impact of ED&I on organizational sustainability and innovation, this study provides a holistic view of the challenges and opportunities in creating inclusive workplaces.","PeriodicalId":250772,"journal":{"name":"Frontiers in Industrial Engineering","volume":"120 18","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822073","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 : 2023-11-23DOI: 10.3389/fieng.2023.1266651
Paulo Garcia, Warisa Sritriratanarak
Industrial informatics brings computational intelligence to industry, powering the “software-ization” of manufacturing processes. However, when faced with the myriad of legacy systems that cannot be fully replaced cost-effectively, practitioners must retrofit computational intelligence into legacy systems. This modernization of legacy industrial systems is deceptively challenging: poor retrofitting can cause more harm than good, hindering overall metrics. We argue for a theoretical framework for modernizing legacy industrial systems. We illustrate the challenge within the context of the real-time performance of industrial cyber-physical systems by depicting a formalization of the problem and illustrating its impact through Monte Carlo methods. We show how knowledge of extant system internals constrains possible optimizations. We conclude by highlighting several research directions, including some recommendations, that must be pursued to establish a common theoretical underpinning that can inform practitioners.
{"title":"We need a theoretical framework for the modernization of industrial legacy systems","authors":"Paulo Garcia, Warisa Sritriratanarak","doi":"10.3389/fieng.2023.1266651","DOIUrl":"https://doi.org/10.3389/fieng.2023.1266651","url":null,"abstract":"Industrial informatics brings computational intelligence to industry, powering the “software-ization” of manufacturing processes. However, when faced with the myriad of legacy systems that cannot be fully replaced cost-effectively, practitioners must retrofit computational intelligence into legacy systems. This modernization of legacy industrial systems is deceptively challenging: poor retrofitting can cause more harm than good, hindering overall metrics. We argue for a theoretical framework for modernizing legacy industrial systems. We illustrate the challenge within the context of the real-time performance of industrial cyber-physical systems by depicting a formalization of the problem and illustrating its impact through Monte Carlo methods. We show how knowledge of extant system internals constrains possible optimizations. We conclude by highlighting several research directions, including some recommendations, that must be pursued to establish a common theoretical underpinning that can inform practitioners.","PeriodicalId":250772,"journal":{"name":"Frontiers in Industrial Engineering","volume":"529 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139244767","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 : 2023-11-16DOI: 10.3389/fieng.2023.1267244
G. J. L. Micheli, A. Martino, F. Porta, A. Cravello, M. Panaro, A. Calabrese
Workforce Planning (WFP) has become a crucial part of the governance of project-driven companies and has been deemed fundamental to drive critical decisions on resource management. To manage manpower planning, companies independently developed internal procedures according to their sector, size, and skills. Despite the efforts to create a reliable workforce planning process, a lack of knowledge, standardization and sharing might lead to misalignment and to heterogeneous approaches among different organizations. This study aims at investigating the current knowledge of the WFP, pointing at the detection of its key factors in terms of process steps, application context, methods, input data, actors, tools and reports’ frequency. Additionally, it attempts to define WFP high-level guidelines which can be generally valid for project-driven organizations. The research seeks to meet these goals by combining the results of the academic literature review on the WFP with the findings of the empirical study in which the representatives of ten project-based enterprises participated. The paper describes the key principles of WFP and its main process’ sections, offering high-level guidelines in terms of recommended process steps, actors involved, operative models, data input, report’s frequency, and tools. The presented features, generated by the literature review and the empirical study, are meant to be generally applicable to project-driven companies and to support the practitioners initiating this process in their organization.
{"title":"Workforce planning in project-driven companies: a high-level guideline","authors":"G. J. L. Micheli, A. Martino, F. Porta, A. Cravello, M. Panaro, A. Calabrese","doi":"10.3389/fieng.2023.1267244","DOIUrl":"https://doi.org/10.3389/fieng.2023.1267244","url":null,"abstract":"Workforce Planning (WFP) has become a crucial part of the governance of project-driven companies and has been deemed fundamental to drive critical decisions on resource management. To manage manpower planning, companies independently developed internal procedures according to their sector, size, and skills. Despite the efforts to create a reliable workforce planning process, a lack of knowledge, standardization and sharing might lead to misalignment and to heterogeneous approaches among different organizations. This study aims at investigating the current knowledge of the WFP, pointing at the detection of its key factors in terms of process steps, application context, methods, input data, actors, tools and reports’ frequency. Additionally, it attempts to define WFP high-level guidelines which can be generally valid for project-driven organizations. The research seeks to meet these goals by combining the results of the academic literature review on the WFP with the findings of the empirical study in which the representatives of ten project-based enterprises participated. The paper describes the key principles of WFP and its main process’ sections, offering high-level guidelines in terms of recommended process steps, actors involved, operative models, data input, report’s frequency, and tools. The presented features, generated by the literature review and the empirical study, are meant to be generally applicable to project-driven companies and to support the practitioners initiating this process in their organization.","PeriodicalId":250772,"journal":{"name":"Frontiers in Industrial Engineering","volume":"162 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139266986","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 : 2023-07-21DOI: 10.3389/fieng.2023.1223989
R. Cranford
Environmental, social, and governance (ESG) focus continues to gain traction in the mining industry through publicly made policies, promises, and commitments. In 2022, both ESG and technological investments were identified in the top trends by Deloitte and in the top risks and opportunities by Ernst and Young. As the first step in the value chain, the mining industry sets the foundation for most industries in meeting their ESG targets. Beyond providing sustainable materials, the mining industry is required to produce the critical minerals needed for the creation of sustainable technologies. With an ongoing debate on how ESG factors should be measured and inconsistent reporting between mining companies, there remains a gap in consistent and auditable progress in ESG reporting. This study evaluates the application of a digital twin technology to bridge the gap in ESG reporting. By examining the use of digital twin technology through thirty case studies and theoretical applications across industries that share commonalities with mining, this study analyzes the opportunity to apply the technology to the mining industry. The research found that digital twin technology can be applied across all mining project phases and can provide added value to improve multiple ESG factors and measure them. Though the research identifies that there are benefits from the application of digital twin technology to all project phases, and across all three ESG dimensions, there remains challenges to implementation. Successful implementation of digital twin technology will require the right people with the right capabilities. Though suggested that the mining industry should let other industries stabilize the digital twin market due to their history and substantial investment in data systems, it is arguable through literature, case studies and leading mining companies’ investments in precursor technologies to digital twins, that solutions are available and scalable, and the time to wait is over.
通过公开制定政策、承诺和承诺，对环境、社会和治理(ESG)的关注继续在采矿业中获得牵引力。2022年，德勤(Deloitte)将ESG和技术投资列为主要趋势，安永(Ernst and Young)将其列为主要风险和机遇。作为价值链的第一步，采矿业为大多数行业实现其ESG目标奠定了基础。除了提供可持续的材料外，采矿业还必须生产创造可持续技术所需的关键矿物。随着关于如何衡量ESG因素以及矿业公司之间不一致的报告的持续争论，ESG报告的一致性和可审计进展仍然存在差距。本研究评估了数字孪生技术的应用，以弥合ESG报告的差距。本研究通过30个案例研究和与采矿业有共性的行业的理论应用来研究数字孪生技术的使用，分析了将该技术应用于采矿业的机会。研究发现，数字孪生技术可以应用于所有采矿项目阶段，并可以为改善多个ESG因素和衡量它们提供附加价值。尽管研究表明，将数字孪生技术应用于所有项目阶段，以及所有三个ESG维度都有好处，但实施起来仍然存在挑战。数字孪生技术的成功实施需要具备合适能力的合适人员。虽然建议采矿业应该让其他行业稳定数字孪生市场，因为它们的历史和对数据系统的大量投资，但通过文献，案例研究和领先的矿业公司对数字孪生先驱技术的投资，可以论证解决方案是可用的和可扩展的，等待的时间已经结束。
{"title":"Conceptual application of digital twins to meet ESG targets in the mining industry","authors":"R. Cranford","doi":"10.3389/fieng.2023.1223989","DOIUrl":"https://doi.org/10.3389/fieng.2023.1223989","url":null,"abstract":"Environmental, social, and governance (ESG) focus continues to gain traction in the mining industry through publicly made policies, promises, and commitments. In 2022, both ESG and technological investments were identified in the top trends by Deloitte and in the top risks and opportunities by Ernst and Young. As the first step in the value chain, the mining industry sets the foundation for most industries in meeting their ESG targets. Beyond providing sustainable materials, the mining industry is required to produce the critical minerals needed for the creation of sustainable technologies. With an ongoing debate on how ESG factors should be measured and inconsistent reporting between mining companies, there remains a gap in consistent and auditable progress in ESG reporting. This study evaluates the application of a digital twin technology to bridge the gap in ESG reporting. By examining the use of digital twin technology through thirty case studies and theoretical applications across industries that share commonalities with mining, this study analyzes the opportunity to apply the technology to the mining industry. The research found that digital twin technology can be applied across all mining project phases and can provide added value to improve multiple ESG factors and measure them. Though the research identifies that there are benefits from the application of digital twin technology to all project phases, and across all three ESG dimensions, there remains challenges to implementation. Successful implementation of digital twin technology will require the right people with the right capabilities. Though suggested that the mining industry should let other industries stabilize the digital twin market due to their history and substantial investment in data systems, it is arguable through literature, case studies and leading mining companies’ investments in precursor technologies to digital twins, that solutions are available and scalable, and the time to wait is over.","PeriodicalId":250772,"journal":{"name":"Frontiers in Industrial Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129937426","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 : 2023-02-02DOI: 10.3389/fieng.2023.1100340
L. Camarinha-Matos
Industrial Informatics has been a key enabler and even a main inducer of novel developments in industrial engineering along the last decade. This relevant role has become more visible in the context of the ongoing digital transformation processes, triggered by the Industry 4.0 “movement.” The so-called fourth industrial revolution is, in fact, the result of a convergence and integration of multiple information and communication technologies (Camarinha-Matos et al., 2019) (Zheng et al., 2021) (Alexa et al., 2022). Although initially focused on the integration of the cyber and physical worlds, as reflected in the terms “Cyber-Physical Systems” and “Internet of Things”, soon the idea was gradually expanded by the addition of “smartness”/“intelligence” facets, as reflected in the terms “smart devices”, “smart sensors”, “smart machines”, “smart systems”, and “smart factories”. As Industry 4.0 became a kind of buzzword, with strong political support worldwide, several other technologies, often branded as “exponential technologies”, and including intelligent robotics, artificial intelligence/machine learning, nanotechnologies, neuro-technologies, sensing and perception, additive manufacturing/3D printing, mobile computing, etc., joined the movement and helped create momentum driving significant industrial transformation and even revitalization. More recent research agendas, as the European Commission’s Industry 5.0 (Breque et al., 2021) (Maddikunta et al., 2022) and Society 5.0 (Broeckaert, 2022) (Deguchi et al., 2020), in addition to a greater emphasis on smartness/artificial intelligence, put the need to consider sustainability and human-centricity aspects more clearly on the table. This is also well aligned with the “UN Agenda 2030 for sustainable development” (Division for Sustainable Development Goals (DSDG), 2015). The field of Industrial Informatics is thus called upon to move from a purely techno-centric perspective, which mainly characterized Industry 4.0, to a more general perspective in which general societal concerns and human-centric developments are required.
{"title":"Grand challenges in industrial informatics","authors":"L. Camarinha-Matos","doi":"10.3389/fieng.2023.1100340","DOIUrl":"https://doi.org/10.3389/fieng.2023.1100340","url":null,"abstract":"Industrial Informatics has been a key enabler and even a main inducer of novel developments in industrial engineering along the last decade. This relevant role has become more visible in the context of the ongoing digital transformation processes, triggered by the Industry 4.0 “movement.” The so-called fourth industrial revolution is, in fact, the result of a convergence and integration of multiple information and communication technologies (Camarinha-Matos et al., 2019) (Zheng et al., 2021) (Alexa et al., 2022). Although initially focused on the integration of the cyber and physical worlds, as reflected in the terms “Cyber-Physical Systems” and “Internet of Things”, soon the idea was gradually expanded by the addition of “smartness”/“intelligence” facets, as reflected in the terms “smart devices”, “smart sensors”, “smart machines”, “smart systems”, and “smart factories”. As Industry 4.0 became a kind of buzzword, with strong political support worldwide, several other technologies, often branded as “exponential technologies”, and including intelligent robotics, artificial intelligence/machine learning, nanotechnologies, neuro-technologies, sensing and perception, additive manufacturing/3D printing, mobile computing, etc., joined the movement and helped create momentum driving significant industrial transformation and even revitalization. More recent research agendas, as the European Commission’s Industry 5.0 (Breque et al., 2021) (Maddikunta et al., 2022) and Society 5.0 (Broeckaert, 2022) (Deguchi et al., 2020), in addition to a greater emphasis on smartness/artificial intelligence, put the need to consider sustainability and human-centricity aspects more clearly on the table. This is also well aligned with the “UN Agenda 2030 for sustainable development” (Division for Sustainable Development Goals (DSDG), 2015). The field of Industrial Informatics is thus called upon to move from a purely techno-centric perspective, which mainly characterized Industry 4.0, to a more general perspective in which general societal concerns and human-centric developments are required.","PeriodicalId":250772,"journal":{"name":"Frontiers in Industrial Engineering","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128032704","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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