Data-driven decision making with Blockchain-IoT integrated architecture: a project resource management agility perspective of industry 4.0

Rane, Santosh B.; Narvel, Yahya Abdul Majid

doi:10.1007/s13198-021-01377-4

Cited by 28 publications

(13 citation statements)

References 40 publications

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“…In this area, issues such as knowledge management (e.g., [ 109 ]), machine learning (e.g., [ 22 , 88 ]), artificial intelligence (e.g., [ 110 , 111 , 112 ]), IoT technologies (e.g., [ 113 ]), or big data analyses (e.g., [ 114 ]) are addressed.…”

Section: Systematic Literature Review Of the Selected Papers Within T...mentioning

confidence: 99%

Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review

Werbińska-Wojciechowska

Winiarska

2023

Sensors

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Recently, there has been a growing interest in issues related to maintenance performance management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies indicate a lack of research on the systematic literature reviews and surveys of studies that would focus on the evolution of Industry 4.0 technologies used in the maintenance area in a cross-sectional manner. Therefore, the paper reviews the existing literature to present an up-to-date and content-relevant analysis in this field. The proposed methodology includes bibliometric performance analysis and a review of the systematic literature. First, the general bibliometric analysis was conducted based on the literature in Scopus and Web of Science databases. Later, the systematic search was performed using the Primo multi-search tool following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The main inclusion criteria included the publication dates (studies published from 2012–2022), studies published in English, and studies found in the selected databases. In addition, the authors focused on research work within the scope of the Maintenance 4.0 study. Therefore, papers within the following research fields were selected: (a) augmented reality, (b) virtual reality, (c) system architecture, (d) data-driven decision, (e) Operator 4.0, and (f) cybersecurity. This resulted in the selection of the 214 most relevant papers in the investigated area. Finally, the selected articles in this review were categorized into five groups: (1) Data-driven decision-making in Maintenance 4.0, (2) Operator 4.0, (3) Virtual and Augmented reality in maintenance, 4) Maintenance system architecture, and 5) Cybersecurity in maintenance. The obtained results have led the authors to specify the main research problems and trends related to the analyzed area and to identify the main research gaps for future investigation from academic and engineering perspectives.

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Section: Systematic Literature Review Of the Selected Papers Within T...mentioning

confidence: 99%

Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review

Werbińska-Wojciechowska

Winiarska

2023

Sensors

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“…Rane and Narvel [123] propose a data-driven decision-making technology by presenting an integrated model of Blockchain-IoT technologies for enhancing project resource management (PRM). For several reasons, including fierce competition, volatile markets, innovative new business models, and the ever-increasing complexity of technologies and developments, today's PRM methods are insufficient.…”

Section: Blockchainmentioning

confidence: 99%

Transformative Procurement Trends: Integrating Industry 4.0 Technologies for Enhanced Procurement Processes

Althabatah,

Yaqot,

Menezes

et al. 2023

Logistics

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Background: the advent of Industry 4.0 (I4.0) innovations has revolutionized supply chain management through technologies like the Internet of Things (IoT) and Artificial Intelligence (AI) integrated into procurement processes. Methods: this study addresses a critical knowledge gap by conducting a comprehensive review of 111 papers sourced from the Scopus database. These papers are classified into seven sub-themes encompassing I4.0 or procurement 4.0 (P4.0), big data, IoT, additive manufacturing, blockchain, e-procurement, and AI. Results: the investigation reveals that I4.0 technologies, particularly e-procurement and blockchain, have garnered substantial attention. Such technologies offer diverse value propositions, encompassing streamlined supplier evaluation, lead time reduction, cost optimization, and enhanced data security. Conclusion: the paper underscores pivotal trends and insights for the evolution of Procurement 4.0, illuminating a path toward more efficient supply chain management.

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“…The paper by Patel et al (2020) used the analytic hierarchy process to determine that the utilization of information technology and market sensitivity is the most important facilitator for agility in the Indian manufacturing industry. The paper by Rane and Narvel (2021) identified the challenges of I4.0 in the agility of asset‐intensive industries by using the Ishikawa diagram and Pareto chart. The growth of I4.0 technologies, such as Big Data Analytics, has impacted enterprise resource planning to ensure the agility of the supply chain in the automotive industry in India.…”

Section: Literature Reviewmentioning

confidence: 99%

Role of Industry 4.0 in agile manufacturing to achieve sustainable development

et al. 2022

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The business world is becoming increasingly complex, disrupted, and uncertain. As Industry 4.0 (I4.0) takes shape, to endure this change and focus on growth, industries must learn to embrace change and move quickly; this is particularly so for the automotive industry, which is a major sector of any economy. Agility is needed to embrace this change and promote sustainability across every industry. To face these contingencies, it is essential to identify and understand the strategies that can aid industries in sustaining real‐time scenarios. In this paper, we aim to assess the agility indicators that bring resilience to the inclusion of I4.0 and sustainability in the automotive sector. The unexpected changes in the environment related to sustainability and technological disruptions of I4.0 require the identification of sustainable agile mitigation strategies to manage such situations. The fuzzy Delphi methodology assesses agility indicators based on a questionnaire for prioritization. Further, the fuzzy technique for order performance by similarity to ideal solution (TOPSIS) is utilized to prioritize these agility indicators with the agility strategies that manufacturing industries can deploy to enhance the sustainability of their operations. The fuzzy extension to the methodologies helps in incorporating vagueness and ambiguity in the decision‐making process. A fuzzy approach to prioritizing agile strategies as the industries are changing is helpful. The decision makers have only a few clear ideas about how best to integrate them. Among the agile strategies, “resilience,” “technological capabilities,” and “customer‐centric innovation” are the top strategies. By executing the strategies suggested in the study and understanding the agility indicators, practitioners can ensure resilience in the work systems and minimize the impact of the disruptions caused by the industrial revolution. Thus, this research has been underpinned by the organizational change theory and discusses all mitigation strategies concerning the rapid changes organizations are facing with the fourth industrial revolution.

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Data-driven decision making with Blockchain-IoT integrated architecture: a project resource management agility perspective of industry 4.0

Cited by 28 publications

References 40 publications

Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review

Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review

Transformative Procurement Trends: Integrating Industry 4.0 Technologies for Enhanced Procurement Processes

Role of Industry 4.0 in agile manufacturing to achieve sustainable development

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