Despite the recent interest in the Industry 4.0 applications for sustainability, little is known on the processes through which digital transformation and Industry 4.0 technologies enable sustainable ...innovation in manufacturing. The present study addresses this knowledge gap by developing a strategic roadmap that explains how businesses can leverage Industry 4.0 technologies to introduce sustainability into innovative practices. For this purpose, the study conducts a systematic review of extant literature to identify Industry 4.0 functions for sustainable innovation and applies interpretive structural modeling to devise the promised roadmap. The results offer interesting insights into Industry 4.0 applications for sustainable innovation. The strategic roadmap developed reveals that Industry 4.0 enables sustainable innovation through 11 functions. Industry 4.0 and the underlying digital technologies and principles allow businesses to improve interfunctional collaboration and better integrate with internal and external stakeholders. Industry 4.0 further improves the knowledge base and advanced manufacturing competency and promotes organizational capabilities valuable to sustainable innovation such as green absorptive capacity, sustainable partnership, and sustainable innovation orientation. Through these functions, Industry 4.0 subsequently enhances green process innovation capacity and the ability to develop or reintroduce eco‐friendly products economically and competitively. Overall, the roadmap explains the complex precedence relationships among the 11 sustainable innovation functions of Industry 4.0, offering important implications for businesses that seek to leverage Industry 4.0 sustainability implications and manage sustainable development.
There is an increasing interest in understanding the interdependencies between conventional lean and agile implementations and Industry 4.0 technology adoptions. Our knowledge of how they interact ...and enable Industry 4.0 implementations in learning organisations is still immature. Informed by the Strategic Momentum Theory and the contextual ambidexterity framework, this paper empirically investigates the effects of lean and agile implementations on Industry 4.0 technology adoptions with exploratory and exploitative learning as mediators. Using the data collected from an online survey of 166 Australian firms and analysed using the PLS-SEM method, we found that only lean practices have significant and positive direct effects on Industry 4.0 implementations, and exploitative learning partially mediates the relationship. We also found that agility does not have direct effects on Industry 4.0 implementations, and exploitative learning fully mediates their relationship. However, the mediating role of exploratory learning is not empirically confirmed. This study confirms several recent exploratory research studies that found evidence for the significant role lean implementations play in Industry 4.0 technology adoption. Agile practices need to first translate into exploitative learning. The findings inform practitioners that firms with investments in lean, agility and exploitative learning capability development will have advantages in technology implementations.
•Conventional agile and lean practices interact with Industry 4.0 (I4.0) technologies.•Lean practices have significant and positive direct effects on I4.0 implementations.•Exploitative learning partially mediates the relationship between lean and I4.0.•Exploitative learning fully mediates the relationship between agility and I4.0.•The mediating role of exploratory learning is not empirically confirmed.
Retrofitting is a sustainable approach to improving the capabilities and extending the life of aging machine tools. Reusing the mechanical construction and replacing only the control electronics and ...software is a viable option to upgrade an aging machine tool to a cutting-edge level. During the last decades, the evolution of machine tools has focused on developing computer numerical control (CNC) rather than on mechanical construction. Retrofitting the CNC enables Industry 4.0 connectivity and improved usability sustainably, preserving finite raw material resources and reducing carbon emissions created during the casting process of heavy blank parts for physically large machine tools.
This publication presents methods to retrofit machine tools using open-source CNC software and a feasibility study after seven years of operation. Our study highlights retrofitting as more profitable than repairing an aging CNC and compares the sustainability of retrofitting or replacing the aging machine tool with a new unit. In conclusion, retrofitting enables sustainability, connectivity, and accuracy comparable to modern machine tools. Retrofitting also paves the way for using artificial intelligence to monitor and adapt to tool wear, chatter, and surface roughness.
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•The presented retrofit approach is scalable, enabling retrofitting large and small machine tools.•A feasibility study and usability survey of the CNC retrofit are presented.•A study on the carbon footprint of casting a frame for machine tools is presented.
It is critical for organizations to self-assess their Industry 4.0 readiness to survive and thrive in the age of the Fourth Industrial Revolution. Thereon, conceptualization or development of an ...Industry 4.0 readiness model with the fundamental model dimensions is needed. This paper used a systematic literature review (SLR) methodology with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and content analysis strategy to review 97 papers in peer-reviewed academic journals and industry reports published from 2000 to 2019. The review identifies 30 Industry 4.0 readiness models with 158 unique model dimensions. Based on this review, there are two theoretical contributions. First, this paper proposes six dimensions (Technology, People, Strategy, Leadership, Process and Innovation) that can be considered as the most important dimensions for organizations. Second, this review reveals that 70 (44%) out of total 158 total unique dimensions on Industry 4.0 pertain to the assessment of technology alone. This establishes that organizations need to largely improve on their technology readiness, to strengthen their Industry 4.0 readiness. In summary, these six most common dimensions, and in particular, the dominance of the technology dimension provides a research agenda for future research on Industry 4.0 readiness.
The ever-growing concern of sustainability and survivability attracts academicians and practitioners to develop strategies and supply chain capabilities that cater to the challenges and helps in ...achieving the sustainability development goals. There is a need to develop a holistic model that facilitates understanding the relationships among supply chain practices, industry 4.0 technologies, and supply chain performance measures. Thus, this study examines the mediating effect of industry 4.0 technologies on supply chain management practices and supply chain performance measures. A survey-based data was collected from manufacturing organizations across India, and 361 complete responses were obtained. Structural equation modeling (SEM) was utilized for data analysis. This study has multiple contributions. First, the results indicate that the supply chain management practices influence the industry 4.0 technologies adoption. Second, the results also revealed that the industry 4.0 technologies significantly positively affect supply chain performance measures. Finally, industry 4.0 technologies mediated the relations between supply chain management practices and supply chain performance measures. Furthermore, the findings offer important insights into understanding the underlying mechanisms in successfully adopting and effectively using industry 4.0 technologies. The implications for theory and practices are also discussed.
•Examining the inter-relationships among SC, I4.0, and performance measures.•Data is collected from the Indian manufacturing sector.•Structural equation modeling (SEM) is used to test the relationships.
•Industry 4.0 is transmuting the organizational structures of businesses.•Organization's ambidexterity can be critical for capability for Industry4.0.•Intellectual capital and technology's absorptive ...capacity improve organizational ambidexterity.•All dimensions of IC improve exploration and exploitation capabilities of an organization.•The study integrates the TAC with the IC-ambidexterity relationship.
Industry 4.0, which features the Internet of things (IoT), cloud computing, big-data, digitalization, and cyber-physical systems, is transforming the way businesses are being run. It is making the business processes more autonomous, automated and intelligent, and is transmuting the organizational structures of businesses by digitalizing their end-to-end business processes. In this context, balancing innovation and exploitation—organization's ambidexterity—while stepping into the fourth industrial revolution can be critical for organizational capability. This study examines the role of intellectual capital (IC)—human capital, structural capital and relational capital—in balancing the innovation and exploitation activities. It also examines the role of technology's absorptive capacity in the relationship between IC and organizational ambidexterity (OA). Data were collected from 217 small and medium enterprises from the manufacturing sector of Pakistan using a closed-ended Likert scale-based questionnaire. The study employs partial least square-Structural Equation Modeling (PLS-SEM) for data analysis. Findings indicate a profound influence of all dimensions of IC, both overall and by dimensions on organizations’ ambidexterity. Findings also exhibit a significant partial mediating role of technology absorptive capacity (TAC) in the association of IC and ambidexterity. The findings of the study emphasize the creation of specific policies aimed to develop IC of a firm, which in turn can enable a firm to maintain a balance between innovation and market exploitation activities. The study integrates the TAC with the IC-OA relationship, which is the novelty of the study.
Sensors play a crucial role in factory automation in making the system intellectual. Different types of sensors are available as per the suitability and applications; some of them are produced in ...mass and available in the market at affordable costs. The standard sensor types available are position sensors, pressure sensors, flow sensors, temperature sensors, and force sensors. They are used in many sectors, such as motorsport, medical, industry, aerospace, agriculture, and daily life. The objective of Industry 4.0 is to increase efficiency through automation. Sensors are vital components of Industry 4.0, allowing several transitions such as changes in positions, length, height, external and dislocations in industrial production facilities to be detected, measured, analysed, and processed. Smart factories will also enhance sustainability by tracking real-time output, and automated control systems will minimise potential factory maintenance costs. It can also be seen that digitalisation can improve production mobility, which gives advanced manufacturing firms a competitive advantage. This paper discusses sensors and their various types, along with significant capabilities for manufacturing. The step-by-step working Blocks and Quality Services of Sensors during implementation in Industry 4.0 are elaborated diagrammatically. Finally, we identified thirteen significant applications of sensors for Industry 4.0. Industry 4.0 provides an excellent opportunity for the development of the sensor market across the globe. In Industry 4.0, sensors will enjoy higher acceptance rates and benefit from a fully enabled connecting and data exchange and logistics integration. In the coming years, sensor installations may grow in process management, automated production lines, and digital supply chains.
Objective: This research aimed to analyze the implications of the use of additive manufacturing for sustainability in production processes.
Methodology: The research was characterized as ...exploratory qualitative approach, which was carried out with 15 professionals from a Brazilian industry. Data collection was conducted through in-depth interviews, and analysis of the speech revealed insights into the environmental implications of additive manufacturing.
Results and discussion: As a result, it was evidenced that despite the benefits offered by additive manufacturing for sustainability, such as reducing material waste and personalized production, there are significant challenges to be faced. Concern about the recyclability of materials used in 3D printing has been identified as a critical point, underlining the pressing need to develop more efficient and sustainable recycling processes to deal with the waste generated. In addition, mentioning the importance of considering the full life cycle of products emphasizes the complexity of environmental issues associated with additive manufacturing, requiring holistic approaches that consider environmental impacts at all stages of the process.
Conclusion: Therefore, the need for an integrated approach to sustainability in additive manufacturing is highlighted, which not only maximizes the environmental benefits of the technology, but also proactively deals with emerging challenges, thus ensuring a positive impact on the environment.
Recently, there have been great advances in internet of things (IoT) and wireless sensor networks (WSNs) technologies for promoting electricity industrial upgrades and even allow the introduction of ...the fourth industrial revolution, namely, Smart Grid Industry (SGI) 4.0. The main functions of SGI4.0 are:
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•We propose a novel BMO-based dynamic clustering algorithm to balance the data traffic and energy consumption load evenly among clusters in the smart grid.•We propose an innovative BMO-based routing algorithm to solve energy consumption and QoS-aware reliable data transmission in the smart grid.•The performance evaluations show that EQRP has successfully minimized the end-to-end delay and has improved the other routing QoS performance metrics, such as packet delivery ratio, efficient memory utilization, residual energy, and throughput.
Recently, there have been great advances in internet of things (IoT) and wireless sensor networks (WSNs) leading to the fourth industrial revolution in power grid, namely, Smart Grid Industry 4.0 (SGI 4.0). In the Smart Grid Industry 4.0 framework, the WSNs have the potential to improve power grid efficiency by cable replacement, deployment flexibility, and cost reduction. However, the smart grid (SG) environment that the WSNs operate in is very challenging because of equipment noise, dust, heat, electromagnetic interference, multipath effects and fading, which make it difficult for current WSNs to provide reliable communication. For SGI 4.0 to come true, a WSN-based highly reliable communication infrastructure is essential for successful operation of the next-generation electricity power grids. To address this need, in this paper a novel dynamic clustering based energy efficient and quality-of-service (QoS)-aware routing protocol (called EQRP), which is inspired by the real behavior of the bird mating optimization (BMO), has been proposed. The proposed distributed scheme improves network reliability significantly and reduces excessive packets retransmissions for WSN-based SG applications. Performance results show that the proposed protocol has successfully reduced the end-to-end delay and has improved packet delivery ratio, memory utilization, residual energy, and throughput.
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