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1 – 10 of over 6000Gabriel Bertholdo Vargas, Jefferson de Oliveira Gomes and Rolando Vargas Vallejos
The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate…
Abstract
Purpose
The purpose of this paper is to present a practical data-based framework for the prioritization of investment in manufacturing technologies, methods and tools, and to demonstrate its applicability and practical relevance through two case studies of manufacturing firms of different industrial segments.
Design/methodology/approach
The proposed framework is based on network theory applied on technology adoption. For this, the database of Industry 4.0 maturity assessments of SENAI was used to develop data visualization tools named “Technology Networks”. Thus, this study is descriptive research with correlational design. Besides, the framework was applied in two companies and semi-structured interviews were carried out with domain experts.
Findings
The technology networks highlight the technological adoption patterns of six industrial segments, by considering the answers of 863 Brazilian companies. In general, less sophisticated technologies were positioned in the center of the networks, which facilitates the visualization of adoption paths. Moreover, the networks presented a well-balanced adoption scenario of Industry 4.0 related technologies and lean manufacturing methods and tools.
Research limitations/implications
Since the database was not built under an experimental design, it is not expected to make statistical inferences about the variables. Furthermore, the decision to use an available database prevented the editing or inclusion of technologies. Besides, it is estimated that the technology networks given have few years for obsolescence due to the fast pace of technological development.
Practical implications
The framework is a tool that may be used by practicing manufacturing managers and entrepreneurs for taking assertive decisions regarding the adoption of manufacturing technologies, methods and tools. The proposition of using network theory to support decision making on this topic may lead to further studies, developments and adaptations of the framework.
Originality/value
This paper addresses the topics of lean manufacturing and Industry 4.0 in an unprecedented way, by quantifying the adoption of its technologies, methods and tools and presenting it in network visualizations. The main value of this paper is the comprehensive framework that applies the technology networks for supporting decision making regarding technology adoption.
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Recently, the concept of the circular economy (CE) has witnessed significant momentum in academic and professional circles. However, there is a dearth of research that studies the…
Abstract
Purpose
Recently, the concept of the circular economy (CE) has witnessed significant momentum in academic and professional circles. However, there is a dearth of research that studies the enabling factors of the CE in the era of digital transformation. The existing research aimed to identify the impact of Industry 4.0 readiness on the CE in manufacturing firms operating in Jordan, as well as to identify the mediating role of the industrial Internet of things and big data analytics.
Design/methodology/approach
For this work objectives, 380 questionnaires were analyzed. Convergent validity and discriminant validity tests were performed through partial least squares-structural equation modelling (PLS-SEM) in the Smart-PLS programme. Data reliability was confirmed. A bootstrapping technique was used to analyze the data and then hypothesis testing was performed.
Findings
The results indicate that Industry 4.0 readiness, industrial Internet of things (IIoT) and big data analytics positively enable CE, also the IIoT and big data analytics positively mediate the nexus between Industry 4.0 readiness and CE.
Practical implications
This study promotes the idea of focusing on Industry 4.0 readiness to enhance CE in the Jordanian manufacturing sector and knowing the effect of IIoT and big data analytics in this relationship.
Originality/value
This research developed a theoretical model to understand how Industry 4.0 readiness might enhance the CE in manufacturing firms by invoking the IIoT and big data analytics as mediating constructs in the relationship between Industry 4.0 readiness and CE. This paper offers new theoretical and practical contributions that add value to industry 4.0 and CE literature by testing these constructs' mediation models in the manufacturing sector.
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Temitayo Seyi Abiodun, Giselle Rampersad and Russell Brinkworth
The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation…
Abstract
Purpose
The internationalization of business has grown the production value chains and created performance challenges for industrial production. Industry 4.0, the digital transformation of industrial processes, promises to deliver performance improvements through smart functionalities. This study investigates how digital transformation translates to performance gain by adopting a systems perspective to drive smartness.
Design/methodology/approach
This study uses qualitative research to collect data on the lived experiences of digital transformation practitioners for theory development. It uses semi-structured interviews with industry experts and applies the Gioia methodology for analysis.
Findings
The study determined that enterprise smartness is an organizational capability developed by digital transformation, it is a function of integration and the enabler of organizational performance gains in the Industry 4.0 context. The study determined that performance gains are experienced in productivity, sustainability, safety and customer experience, which represents performance metrics for Industry 4.0.
Research limitations/implications
This study contributes a model that inserts smartness in the linkage between digital transformation and organizational outcomes to the digital transformation and production management literature.
Practical implications
The study indicates that digital transformation programs should focus on developing smartness rather than technology implementations, which must be considered an enabling activity.
Originality/value
Existing studies recognized the positive impact of technology on performance in industrial production. The study addresses a missing link in the Industry 4.0 value creation process. It adopts a systems perspective to establish the role of smartness in translating technology use to performance outcomes. Smart capabilities have been the critical missing link in the literature on harnessing digital transformation in organizations. The study advances theory development by contributing an Industry 4.0 value model that establishes a link between digital technologies, smartness and organizational performance.
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Desirée H. van Dun and Maneesh Kumar
Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech…
Abstract
Purpose
Many manufacturers are exploring adopting smart technologies in their operations, also referred to as the shift towards “Industry 4.0”. Employees' contribution to high-tech initiatives is key to successful Industry 4.0 technology adoption, but few studies have examined the determinants of employee acceptance. This study, therefore, aims to explore how managers affect employees' acceptance of Industry 4.0 technology, and, in turn, Industry 4.0 technology adoption.
Design/methodology/approach
Rooted in the unified theory of acceptance and use of technology model and social exchange theory, this inductive research follows an in-depth comparative case study approach. The two studied Dutch manufacturing firms engaged in the adoption of Industry 4.0 technologies in their primary processes, including cyber-physical systems and augmented reality. A mix of qualitative methods was used, consisting of field visits and 14 semi-structured interviews with managers and frontline employees engaged in Industry 4.0 technology adoption.
Findings
The cross-case comparison introduces the manager's need to adopt a transformational leadership style for employees to accept Industry 4.0 technology adoption as an organisational-level factor that extends existing Industry 4.0 technology user acceptance theorising. Secondly, manager's and employee's recognition and serving of their own and others' emotions through emotional intelligence are proposed as an additional individual-level factor impacting employees' acceptance and use of Industry 4.0 technologies.
Originality/value
Synthesising these insights with those from the domain of Organisational Behaviour, propositions were derived from theorising the social aspects of effective Industry 4.0 technology adoption.
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This study aims to propose and develop a new digital collaborative supply chain (CSC) model completely based on the emerging Industry 4.0 technologies. The digital model aims to…
Abstract
Purpose
This study aims to propose and develop a new digital collaborative supply chain (CSC) model completely based on the emerging Industry 4.0 technologies. The digital model aims to support the main factors likely to affect CSC. This proposed model combines the most well-known digital tools such as blockchain technology, Internet of Things (IoT) and cloud computing (CC).
Design/methodology/approach
Motivated by its effective solution to enhance trust, traceability, transparency and minimize costs and risks, the combination of the most well-known digital tools such as blockchain technology, IoT and CC to develop a new digital CSC model is addressed in this research. This study first investigates and conducts a deep review analysis that explores how Industry 4.0 technologies can enable collaboration mechanisms. Second, based on an analysis of literature review, the main factors likely to affect CSC have been identified and analysed. Finally, the authors combine digital tools to support the identified factors to enhance transparency, traceability and trust by proposing a new digital CSC model. This proposed model will be used as a referential guide to encourage and motivate SC actors to collaborate in digital CSC.
Findings
This work provides many important contributions to theory and practice. First, role and impacts of the most well-known digital tools such as blockchain technology, IoT and CC for digitizing CSC have separately presented and developed. Second, the authors conceptualized a framework by developing a new digital CSC model. This conceptual digital model can be used as a referential guide for all SC actors in order to motivate them to collaborate in a modern, intelligent, secure and reliable SC. It can also support all factors affecting CSC.
Originality/value
The originality of this study is first investigating separately the roles and impacts of each digital tool on CSC performance. Second, the authors combine the most well-known digital tools such as blockchain technology, IoT and CC in order to develop an efficient, smart, modern and new digital CSC model. In this combination, CC is used as platform as a service enabling to link and connect the blockchain and IoT to support the main factors affecting CSC. Unlike to digital CSC model with only one digital tool, the proposed model is more realistic since depending on the information to be shared with other actors, the most appropriate tool will be automatically detected and used. This solution offers a large choice to SC actors for real time data and information sharing. In addition, the proposed model will largely enhance traceability, transparency and trust in CSC.
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Morteza Ghobakhloo, Mantas Vilkas, Alessandro Stefanini, Andrius Grybauskas, Gediminas Marcinkevicius, Monika Petraite and Peiman Alipour Sarvari
Using a dynamic capabilities approach, the present study aims to identify and assess the effects of organizational determinants on capabilities underlying Industry 4.0 design…
Abstract
Purpose
Using a dynamic capabilities approach, the present study aims to identify and assess the effects of organizational determinants on capabilities underlying Industry 4.0 design principles, such as integration, virtualization, real-time, automation and servitization.
Design/methodology/approach
PLS-SEM enables a two-stage hierarchical latent variable reflective-formative model which was used for assessing the effect of organizational determinants on Industry 4.0 design principles. Five hundred six manufacturing companies constitute the effective sample, representing a population of manufacturing companies in an industrialized country.
Findings
The findings reveal that Industry 4.0 design principles extensively depend on digitalization resource availability. At the same time, companies that possess digitalization and change management capabilities tend to devote more resources to digitalization. Finally, the paper reveals that networking and partnership capability is the critical enabler for change management and digitalization capabilities.
Practical implications
The paper provides empirical evidence that the successful development of Industry 4.0 design principles and their underlying integration, virtualization, real-time, automation and servitization capabilities are resource dependent, requiring significant upfront investment and continuous resource allocation. Further, the study implies that companies with networking and partnership, change management and digitalization capabilities tend to allocate more resources for Industry 4.0 transformation.
Originality/value
Exclusively focusing on empirical research that reported applied insights into determinants of Industry 4.0 design principles, the study offers unique implications for promoting Industry 4.0 digital transformation among manufacturing companies.
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Lyn Liq Ooi, Sin Yin Teh and Peck Yeng Sharon Cheang
A paradigm shift of industry revolution 4.0 is made possible by technological advances that constitute a reversal of conventional lean production (LP) processes. In addition…
Abstract
Purpose
A paradigm shift of industry revolution 4.0 is made possible by technological advances that constitute a reversal of conventional lean production (LP) processes. In addition, there is increasing pressure on the manufacturing industry to manage operations responsibly towards the environmental and social impact, on top of the economic. These have motivated the manufacturing industry to identify approaches to implementing LP to achieve sustainable organizational performance. Hence, this study aims to examine the moderating role of industry 4.0 technologies adoption in the relationship between LP and sustainable organizational performance.
Design/methodology/approach
This study proposed a research framework on the relationship between LP and sustainable organizational performance supported by LP theory and triple bottom line theory, with industry 4.0 technologies adoption as a moderator. A quantitative survey method was used in this study for data collection. The respondents in this study were middle or top management in manufacturing companies, including directors, managers, supervisors and coordinators. To investigate the demographic variables of respondents, descriptive statistics were generated by using IBM Statistical Packages for the Social Sciences. For measurement and structural model evaluations, partial least square structural equation modelling was used.
Findings
Based on the proposed research framework in this study, supplier feedback, just-in-time delivery, supplier development, customer involvement, pull system, continuous flow, set-up time reduction (STR), statistical process control, total productive maintenance (TPM) and employee involvement are the dimensions for LP. This study revealed that industry 4.0 technologies adoption positively moderated the relationships of five LP dimensions towards a sustainable organizational performance, namely, supplier feedback, supplier development, continuous flow, STR and TPM.
Originality/value
This study provided insights that would enable practitioners to better strategize the co-existence of LP and industry 4.0 technologies adoption in mutually supporting sustainable organizational performance (environmental, social and economic).
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Larissa Statsenko, Aparna Samaraweera, Javad Bakhshi and Nicholas Chileshe
Based on the systematic literature review, this paper aims to propose a framework of Construction 4.0 (C4.0) scenarios, identifying Industry 4.0 (I4.0) enabling technologies and…
Abstract
Purpose
Based on the systematic literature review, this paper aims to propose a framework of Construction 4.0 (C4.0) scenarios, identifying Industry 4.0 (I4.0) enabling technologies and their applications in the construction industry. The paper reviews C4.0 trends and potential areas for development.
Design/methodology/approach
In this research, a systematic literature review (SLR) methodology has been applied, including bibliographic coupling analysis (BCA), co-citation network analysis of keywords, the content analysis with the visualisation of similarities (VOSviewer) software and aggregative thematic analysis (ATA). In total, 170 articles from the top 22 top construction journals in the Scopus database between 2013 and 2021 were analysed.
Findings
Six C4.0 scenarios of applications were identified. Out of nine I4.0 technology domains, Industrial Internet of Things (IIoT), Cloud Computing, Big Data and Analytics had the most references in C4.0 research, while applications of augmented/virtual reality, vertical and horizontal integration and autonomous robotics yet provide ample avenues for the future applied research. The C4.0 application scenarios include efficient energy usage, prefabricated construction, sustainability, safety and environmental management, indoor occupant comfort and efficient asset utilisation.
Originality/value
This research contributes to the body of knowledge by offering a framework of C4.0 scenarios revealing the status quo of research published in the top construction journals into I4.0 technology applications in the sector. The framework evaluates current C4.0 research trends and gaps in relation to nine I4.0 technology domains as compared with more advanced industry sectors and informs academic community, practitioners and strategic policymakers with interest in C4.0 trends.
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Armin Samani and Fatemeh Saghafi
This study aims to introduce the model of implementation to run the smart production factories. The study also aims to investigate the Industry 4.0 technologies as enablers to…
Abstract
Purpose
This study aims to introduce the model of implementation to run the smart production factories. The study also aims to investigate the Industry 4.0 technologies as enablers to deal with challenges in the way of implementation.
Design/methodology/approach
This contribution benefits from two teams of experts to evaluate the challenges and technologies of Industry 4.0. The Hanlon method is applied to evaluate, rank and prioritise the challenges which are initially scored by experts’ Team 1. Then, the adjacency matrix among enablers and challenges is extracted through the opinions of experts’ Team 2. The study also uses fuzzy cognitive map (FCM) to evaluate the real weights of technologies and challenges, rank and prioritise subsequently.
Findings
A total of 8 challenging obstacles and 24 key technologies have been evaluated. The findings reveals that recruit and retention of experienced managers, undefined return on investment and recruit and retention of multi-skilled workers are the most serious challenges in the way of implementing smart production factories. Furthermore, big data, IT-based management and Internet of Things are the top-ranked key enablers to face the challenges.
Originality/value
To the best of the authors’ knowledge, this study is one of the pioneering studies that uses Hanlon method to evaluate industrial challenges. Integrating Hanlon method and FCM leads to a comprehensive model of evaluation and ranking which is another novelty of this contribution. Although many research studies have been released to implement the smart factories, practical model of implementation for production factories is identified as a literature gap.
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Sudhanshu Joshi, Manu Sharma, Shalini Bartwal, Tanuja Joshi and Mukesh Prasad
The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance…
Abstract
Purpose
The study proposes to determine the impending challenges to lean integration with Industry 4.0 (I4.0) in manufacturing that aims at achieving desired operational performance. Integrating lean and Industry 4.0 as the two industrial approaches is synergetic in providing operational benefits such as increasing flexibility, improving productivity, reducing cost, reducing delivery time, improving quality and value stream mapping (VSM). There is an urgent need to understand the integrated potential of OPEX strategies like lean manufacturing and also to determine the challenges for manufacturing SMEs and further suggest a strategic roadmap for the future.
Design/methodology/approach
The current work has used a combined approach on interpretative structural modeling (ISM) and fuzzy Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) approach to structure the multiple level analysis for the implementation challenges to integrate OPEX strategies with Industry 4.0.
Findings
The research has found that the indulgence of various implementation issues like lack of standardization, lack of vision and lack of trained support, all are the major challenges that inhibit the integration of OPEX strategies with I4.0 technologies in manufacturing.
Research limitations/implications
The research has investigated the internal factors acting as a roadblock to lean and Industry 4.0 adoption. Further studies may consider external factors to lean and Industry 4.0 implementation. Also, further research may consider other operational excellence approaches and extend further to relevant sectors.
Practical implications
This study provides the analysis of barriers that is useful for the managers to take strategic actions for implementing OPEX strategies with I4.0 in smart manufacturing.
Originality/value
The research determines the adoption challenges towards the integrated framework. This is the first study to explore challenges in integrating OPEX strategies with I4.0 technologies in manufacturing SMEs.
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