Resiliency of Smart Manufacturing Enterprises via Information Integration

Sheth, Ananya; Kusiak, Andrew

doi:10.1016/j.jii.2022.100370

Cited by 13 publications

(5 citation statements)

References 41 publications

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“…It is a computing system capable of executing tasks that demand human intelligence (Saha et al, 2022; Sheth & Kusiak, 2022). Predictive analytics allows companies to step ahead of demand, (Govindan et al, 2022; Spieske & Birkel, 2021) and therefore align its capacities to avoid delays, excess production, and inefficient loadings (Raut et al, 2021).…”

Section: Resultsmentioning

confidence: 99%

Uncovering Industry 4.0 technology attributes in sustainable supply chain 4.0: A systematic literature review

2023

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Industry 4.0 technologies are transforming supply chain management from a linear model to what is known as supply chain 4.0, where operations are integrated, and flows stream in multiple directions. The study aims to explore the attributes of Industry 4.0 technologies and their impact to drive sustainability values. The findings were generated after a systematic literature review of 71 articles on various sustainability dimensions and multiple Industry 4.0 technologies. The study provides a review of the most studied technologies in the sustainable supply chain context and categorizes their attributes as well as their relevance to sustainability. The results show that advances in technologies such as Blockchain and Internet of Things have increased the potential for supply chains to reach sustainability values.The study expands the existing literature and encourages businesses and the scientific community to investigate the power of Industry 4.0 technologies for sustainability.It presents limitations and directions for future research.

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Section: Resultsmentioning

confidence: 99%

Uncovering Industry 4.0 technology attributes in sustainable supply chain 4.0: A systematic literature review

2023

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“…The MFGRES framework identifies manufacturing (re-)configuration capabilities, agility, communication and a supporting MFGRM culture as key enablers for differentiating MFGRES antecedents. Numerous academics, with some variation, have supported this central idea (Dwaikat et al ., 2022; Hosseini et al ., 2016; Longo et al ., 2022; Sheth and Kusiak, 2022). We find that the majority of the articles in our sample identify techniques to improve agility (∼67%) and (re-)configuration capacities (∼43%).…”

Section: Methodsmentioning

confidence: 99%

Are metaverse applications in quality 4.0 enablers of manufacturing resiliency? An exploratory review under disruption impressions and future research

El Jaouhari,

Arif,

Samadhiya

et al. 2023

TQM

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PurposeThe purpose of this paper is to investigate, from a thorough review of the literature, the role of metaverse-based quality 4.0 (MV-based Q4.0) in achieving manufacturing resilience (MFGRES). Based on a categorization of MV-based Q4.0 enabler technologies and MFGRES antecedents, the paper provides a conceptual framework depicting the relationship between both areas while exploring existing knowledge in current literature.Design/methodology/approachThe paper is structured as a comprehensive systematic literature review (SLR) at the intersection of MV-based Q4.0 and MFGRES fields. From the Scopus database up to 2023, a final sample of 182 papers is selected based on the inclusion/exclusion criteria that shape the knowledge base of the research.FindingsIn light of the classification of reviewed papers, the findings show that artificial intelligence is especially well-suited to enhancing MFGRES. Transparency and flexibility are the resilience enablers that gain most from the implementation of MV-based Q4.0. Through analysis and synthesis of the literature, the study reveals the lack of an integrated approach combining both MV-based Q4.0 and MFGRES. This is particularly clear during disruptions.Practical implicationsThis study has a significant impact on managers and businesses. It also advances knowledge of the importance of MV-based Q4.0 in achieving MFGRES and gaining its full rewards.Originality/valueThis paper makes significant recommendations for academics, particularly those who are interested in the metaverse concept within MFGRES. The study also helps managers by illuminating a key area to concentrate on for the improvement of MFGRES within their organizations. In light of this, future research directions are suggested.

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“…It discusses the different aspects of smart services-based manufacturing (Koldewey et al. , 2020; Sheth and Kusiak, 2022), innovation in supply chain management (Mak, 2022; Hahn, 2020), logistics (Rahman et al. , 2022; Asthana and Dwivedi, 2020) digitization of the manufacturing sector (Kohtamaki et al.…”

Section: Analysis Of Contentmentioning

confidence: 99%

“…Based upon the results of LDA and co-occurrence analysis of keywords, the cluster focuses on operational (Mak, 2022) and smart manufacturing communities. It discusses the different aspects of smart services-based manufacturing (Koldewey et al, 2020;Sheth and Kusiak, 2022), innovation in supply chain management (Mak, 2022;Hahn, 2020), logistics (Rahman et al, 2022;Asthana and Dwivedi, 2020) digitization of the manufacturing sector (Kohtamaki et al, 2020;Dragicevic et al, 2019). Technologies used include blockchain (De Giovanni, 2020), cloud manufacturing and datadriven decision-making for the manufacturing sectors (Sarbu, 2022).…”

Section: Cluster 1 (Manufacturing-based Scs)mentioning

confidence: 99%

A contemplative overview of smart communities: a hybrid analytical approach

Sakshi,

Srivastava,

Mangla

et al. 2023

JEIM

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PurposeThis study aims to uncover and develop explicit knowledge of existing smart communities (SCs) to guide services and business solutions for enterprises and serve community users in a well-thought-out manner. These sagacious frameworks will assist in analyzing trends and reaching out to pre-existing setups with different degrees of expertise.Design/methodology/approachA systematic overview is provided in this paper to unify insights and competencies toward building SCs; a hybrid analytical approach is used consisting of machine learning and bibliometric analysis. Scopus and Web of Science (WoS) are the primary databases for this purpose.FindingsSCs implement cutting-edge technologies to enhance mobility, elevating information and communication technology (ICT) skills and data awareness while improving business processes and efficiency. This system of SC is an evolution of the conventional method. It provides a foundation for intelligent community services based on individual users and technologies such as the Internet of Things (IoT), artificial intelligence, cloud computing and big data. Manufacturing-based, service-based, retail-based, resource management and infrastructure-based SCs exist in the literature.Originality/valueThe paper summarizes a conceptual framework of SCs based on existing works around SCs. To the best of the authors’ knowledge, this is the first systematic literature review that uses a hybrid approach of topic modeling and bibliometric analysis to understand SCs better.

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Resiliency of Smart Manufacturing Enterprises via Information Integration

Cited by 13 publications

References 41 publications

Uncovering Industry 4.0 technology attributes in sustainable supply chain 4.0: A systematic literature review

Uncovering Industry 4.0 technology attributes in sustainable supply chain 4.0: A systematic literature review

Are metaverse applications in quality 4.0 enablers of manufacturing resiliency? An exploratory review under disruption impressions and future research

A contemplative overview of smart communities: a hybrid analytical approach

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