eTransition models of collaborating design and manufacturing enterprises

Ránky, Paul G.; Lonkar, M.; ChamyVelumani, Satish

doi:10.1080/0951192031000089165

Cited by 8 publications

(4 citation statements)

References 5 publications

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“…We choose three clusters based on the side and Weighted Mean Silhouette value, that is, "sustainable manufacturing concept evolution (#0)," "larger integrated circuit (#1)," and design (#3). Cluster 0 has 76 members, and the most active citation is Culot et al [19], cluster 1 has 58 members, with the most active citation being Ranky et al [20], and cluster 3 has 47 members, and the most active citation is Fountain [21]. ese three papers with a high level of citing times are analyzed in Table 2, which shows a research trend over time.…”

Section: Visualization Of the Scientific Literature From Differentmentioning

confidence: 99%

“…Year Main points Fountain [21] 2020 Novel leadership in digital information processing Ranky et al [20] 2003 Managing manufacturing lines and providing electronic support systems for operators Culot et al [19] 2000 Operationalization of industry 4.0 across multiple disciplines technology drives production innovation is carried on to the next stage.…”

Section: Articlementioning

confidence: 99%

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The Sustainable Digitalization in the Manufacturing Industry: A Bibliometric Analysis and Research Trend

Shang

Zhang

2022

Mobile Information Systems

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Digital technologies are shown to perform a vital role in developing a resource-efficient industrial base. The effective adoption of digital technologies can help reduce costs and improve the sustainability and flexibility of manufacturing industries. However, how digital technologies favor the transition towards manufacturing systems has not been analyzed in detail yet, so more conceptual and empirical investigation is required in this field. This study investigates the digital transformation trend in the manufacturing industry by combining the bibliometric method with life cycle mode and literature mining. An integrated data analysis system (IDAS) is developed, which includes data collection, data analysis, and visualization processes. As a result, dual-map overlay, keywords clusters, Timeline, and Time zone views are visualized to identify the research trend with the three main aspects: design, larger integrated circuit, and sustainable manufacturing concept evolution. Besides, to recognize potentials for future development of the domain, life cycle model-based technological trajectory is identified, constructing an information society, the combination of tools, and the performance improvement of the whole digital transformation. Moreover, in response to sustainable development, a system considering business strategies and cultural delivery, technological integration, and partner participation and evaluation is developed, which could cope with complex manufacturing processes due to different industrial tasks in different regions.

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Section: Visualization Of the Scientific Literature From Differentmentioning

confidence: 99%

Section: Articlementioning

confidence: 99%

The Sustainable Digitalization in the Manufacturing Industry: A Bibliometric Analysis and Research Trend

Shang

Zhang

2022

Mobile Information Systems

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“…Concepts Papers suggesting ways of thinking things, such as new metamodels or taxonomies (this was titled "models" in [117], which is misleading in the context of this study), such as [115,126,146].…”

Section: Contribution Type Facetmentioning

confidence: 99%

Modeling languages in Industry 4.0: an extended systematic mapping study

et al. 2019

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Industry 4.0 integrates Cyber-Physical Systems with the Internet of Things to optimize the complete value-added chain. Successfully applying Industry 4.0 requires the cooperation of various stakeholders from different domains. Domain-specific modeling languages promise to facilitate their involvement through leveraging (domain-specific) models to primary development artifacts. Objective: We aim to assess the use of modeling in Industry 4.0 through the lens of modeling languages in a broad sense. Method: Based on an extensive literature review, we updated our systematic mapping study on modeling languages and modeling techniques used in Industry 4.0 [159] to include publications until February 2018. Overall, the updated study considers 3344 candidate publications that were systematically investigated until 408 relevant publications were identified. Based on these, we developed an updated map of the research landscape on modeling languages and techniques for Industry 4.0. Results: Research on modeling languages in Industry 4.0 focuses on contributing methods to solve the challenges of digital representation and integration. To this end, languages from systems engineering and knowledge representation are applied most often but rarely combined. There also is a gap between the communities researching and applying modeling languages for In

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“…It is based on our generic process failure risk analysis method, which could be applied to literally any process, that involves risk (Bot 1999, Binder 2002, Dornan 2002, Dunkerley et al 2002, Gobble and Brombacher 1999, Held 1998, Ranky 1996, 2003c.…”

Section: Introductionmentioning

confidence: 99%

An analytical approach, a software tool (DFRA) and application examples for assessing process-related failure risk

Ránky¹,

ChamyVelumani²

2003

International Journal of Computer Integrated Manufacturing

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Our process-related failure risk analysis method belongs to the family of failure mode and effect analysis methods. It represents a systematic, rule-based, quantitative and open-source computational method, developed by Ranky for disassembly and for other processes, to identify and minimize potential failure risks, and/or failures of processes in general, including disassembled sub-assemblies, objects and components, and their effects on the customer. One of the tools developed based on the generic methodology, DFRA (Disassembly Failure Risk Analysis), is a Team Oriented Problem Solving (TOPS) method, aimed at minimizing dissatisfaction, and financial loss for disassembly process related risks. DFRA is applied during the planning stages of a disassembly process, and then updated on a regular basis to document changes. It addresses negative quality and is primarily concerned with potential events, which can make the disassembly process, or the harvested components fail. Our approach is component-oriented, meaning that as we disassemble the product, the DFRA team focuses on each subassembly and then each component. This paper describes the methodology, offers an insight into the rule-base, and gives some application examples for assessing process-related failure risk using our DFRA spreadsheet-based software tool; a crucial piece of the eTransition jigsaw puzzle.

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eTransition models of collaborating design and manufacturing enterprises

Cited by 8 publications

References 5 publications

The Sustainable Digitalization in the Manufacturing Industry: A Bibliometric Analysis and Research Trend

The Sustainable Digitalization in the Manufacturing Industry: A Bibliometric Analysis and Research Trend

Modeling languages in Industry 4.0: an extended systematic mapping study

An analytical approach, a software tool (DFRA) and application examples for assessing process-related failure risk

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