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Article
Publication date: 7 June 2021

Ranjith R. and S. Nalin Vimalkumar

The most difficult tasks in the design and development of products for diverse engineering applications were the selection of suitable materials. Choice of inappropriate process…

92

Abstract

Purpose

The most difficult tasks in the design and development of products for diverse engineering applications were the selection of suitable materials. Choice of inappropriate process variables leads to poor performance, which increases the cost of the product. The selection of the best option of available alternatives is important to improve the performance and productivity of the manufacturing enterprises.

Design/methodology/approach

The paper aims to develop Hybrid Multi-Criteria Decision Making (HMCDM) by integrating two potential optimization techniques Elimination Et Choix Traduisant la REalité and multi-objective optimization on the basis of ratio analysis. The weight of the criteria was calculated using the critic weight method.

Findings

The efficiency and flexibility of the proposed HMCDM technique were illustrated and validated by two examples. In the first case, the best electrode material among the five available alternatives was selected for the electrical discharge machining of AZ91/B4Cp magnesium composites. In the second case, the optimum weight percentage of composites providing the best tribological properties was chosen.

Originality/value

It was noted that the HMCDM methodology was quite simple to comprehend, easy to apply and provided reliable rankings of the material alternatives. The proposed hybrid algorithm is suitable for product optimization as well as design optimization.

Details

World Journal of Engineering, vol. 19 no. 4
Type: Research Article
ISSN: 1708-5284

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Article
Publication date: 12 September 2023

G. Citybabu and S. Yamini

Lean Six Sigma 4.0 has brought about a paradigm shift in customization, automation, value creation and digitalization to achieve excellence in human factors, operations and…

1112

Abstract

Purpose

Lean Six Sigma 4.0 has brought about a paradigm shift in customization, automation, value creation and digitalization to achieve excellence in human factors, operations and sustainable development. Despite its potential, LSS 4.0 is still in its nascent stage, with researchers striving to identify the key and relevant components of LSS in relation to Industry 4.0. The present study aims to address this knowledge gap through a literature review and subsequently provide a conceptual framework for LSS within the context of digital transformation.

Design/methodology/approach

In this study, the authors have conducted a thorough review of reputable articles published between 2011 and 2022, focusing on the integration of Lean Six Sigma (LSS) and Industry 4.0 (I4.0). By using appropriate keywords, the authors identified around 85 relevant articles. The main objective of this integrative literature review was to analyze and extract valuable knowledge from the existing literature on LSS and I4.0. Based on the authors’ findings, a conceptual framework was developed.

Findings

The review revealed the motivators, building blocks, tools and challenges of LSS 4.0. The conceptual framework delves into the key aspects of LSS 4.0, focusing on the dimensions of people, process and technology, as well as their subdimensions. These subdimensions serve as the building blocks for developing LSS 4.0 capabilities. The proposed framework visually represents the conceptualization and the relationships among its components.

Research limitations/implications

Only a few conceptual approaches to LSS are developed that include the concepts, new roles and elements of I4.0. As a result, this research investigates the gap in current LSS models preceding I4.0 and develops a conceptual framework to provide a novel and comprehensive summary of the new concepts and components driving nascent and current LSS practices in the digital era.

Practical implications

This study offers practical guidance for implementing LSS in the context of I4.0, emphasizing digital transformation. The findings highlight motivators, building blocks, tools, challenges and spread of LSS 4.0 practices, and present a conceptual framework of LSS 4.0. These insights can help organizations enhance their LSS capabilities and achieve excellence in human factors, operations and sustainable development.

Originality/value

This study aims to make a significant contribution to the model-building efforts of researchers focusing on LSS 4.0. By offering practical guidance, the points discussed in this study help enhance the implementation efforts of practitioners and organizations in the context of I4.0, with a specific focus on digital transformation. The guidance provided takes into account the perspectives of people, processes and technology, providing valuable insights for successful integration.

Details

Benchmarking: An International Journal, vol. 31 no. 9
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 8 August 2016

Bharathiraja Balasubramanian, Praveen Kumar Ramanujam, Ranjith Ravi Kumar, Chakravarthy Muninathan and Yogendran Dhinakaran

The purpose of this paper is to speak about the production of biodiesel from waste cooking oil which serves as an alternate fuel in the absence of conventional fuels such as…

422

Abstract

Purpose

The purpose of this paper is to speak about the production of biodiesel from waste cooking oil which serves as an alternate fuel in the absence of conventional fuels such as diesel and petrol. Though much research work was carried out using non-edible crops such as Jatropha and Pongamia, cooking oil utilized in bulk quantity is discarded as a waste. This is reused again as it contains more of esters that when combined with an alcohol in presence of an enzyme as a catalyst yields triglycerides (biodiesel).

Design/methodology/approach

The lipase producing strain Rhizopus oryzae and pure enzyme lipase is immobilized and treated with waste cooking oil for the production of FAME. Reaction parameters such as temperature, time, oil to acyl acceptor ratio and enzyme concentration were considered for purified lipase and in the case of Rhizopus oryzae, pH, olive oil concentration and rpm were considered for optimization studies. The response generated through each run were evaluated and analyzed through the central composited design of response surface methodology and thus the optimized reaction conditions were determined.

Findings

A high conversion (94.01 percent) was obtained for methanol when compared to methyl acetate (91.11 percent) and ethyl acetate (90.06 percent) through lipase catalyzed reaction at oil to solvent ratio of 1:3, enzyme concentration of 10 percent at 30°C after 24 h. Similarly, for methanol a high conversion (83.76 percent) was obtained at an optimum pH of 5.5, olive oil concentration 25 g/L and 150 rpm using Rhizopus oryzae when compared to methyl acetate (81.09 percent) and ethyl acetate (80.49 percent).

Originality/value

This research work implies that the acyl acceptors methyl acetate and ethyl acetate which are novel solvents for biodiesel production can also be used to obtain high yields as compared with methanol under optimized conditions.

Details

Management of Environmental Quality: An International Journal, vol. 27 no. 5
Type: Research Article
ISSN: 1477-7835

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Article
Publication date: 28 November 2024

G. Citybabu and S. Yamini

Lean Six Sigma (LSS) is often perceived as a foundation for implementing Industry 4.0 (I4.0) within an organization, with the two strengthening each other in different ways. The…

45

Abstract

Purpose

Lean Six Sigma (LSS) is often perceived as a foundation for implementing Industry 4.0 (I4.0) within an organization, with the two strengthening each other in different ways. The purpose of this article is to examine the evolution, trends and motivation for merging LSS and I4.0 and to gain insights into LSS 4.0 in both manufacturing and service sectors. This article also explores the effective methods for integrating and implementing LSS 4.0 in both manufacturing and service sectors, along with conducting a Strengths, Weaknesses, Opportunities and Threats (SWOT) analysis of LSS 4.0.

Design/methodology/approach

By conducting a systematic literature review in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, relevant literature from 2010 to 2023 was reviewed using appropriate keywords and research criteria. The objective was to identify, select and evaluate research articles related to LSS 4.0. Consequently, 159 relevant papers were located in databases, including Elsevier, Taylor and Francis Group, IEEE, Springer, Emerald Insights, Scopus and non-Scopus databases. Additionally, this review aimed to understand the progress of LSS 4.0 from the manufacturing and service sector context and to perform a SWOT analysis of LSS 4.0.

Findings

This review reveals a significant surge in the literature on LSS and I4.0 over the past three years. The research articles were categorized based on various themes, including the publisher, journals, types of articles and geographical factors such as country and continent. Additionally, the review examined the progress of LSS 4.0 in both manufacturing and service sectors. A SWOT analysis was also performed to identify the SWOT of LSS 4.0.

Originality/value

This is the first exclusive research work to conduct a SWOT analysis of LSS 4.0. This research article is highly valuable for academicians, researchers, policymakers and practitioners as it helps to identify the SWOT of LSS 4.0. Furthermore, it provides an overview of the progress of LSS 4.0 from both manufacturing and service sector perspectives, and significant case studies are discussed.

Details

The TQM Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 11 March 2024

Sudhanshu Joshi, Manu Sharma, Sunil Luthra, Jose Arturo Garza-Reyes and Ramesh Anbanandam

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

451

Abstract

Purpose

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

Design/methodology/approach

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

Findings

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

Research limitations/implications

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

Originality/value

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

Details

The TQM Journal, vol. 36 no. 6
Type: Research Article
ISSN: 1754-2731

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Article
Publication date: 19 September 2023

Amit Kumar, Som Sekhar Bhattacharyya and Bala Krishnamoorthy

The purpose of this research study was to understand the simultaneous competitive and social gains of machine learning (ML) and artificial intelligence (AI) usage in…

1145

Abstract

Purpose

The purpose of this research study was to understand the simultaneous competitive and social gains of machine learning (ML) and artificial intelligence (AI) usage in organizations. There was a knowledge hiatus regarding the contribution of the deployment of ML and AI technologies and their effects on organizations and society.

Design/methodology/approach

This study was grounded on the dynamic capabilities (DC) and ML and AI automation-augmentation paradox literature. This research study examined these theoretical perspectives using the response of 239 Indian organizational chief technology officers (CTOs). Partial least square-structural equation modeling (PLS-SEM) path modeling was applied for data analysis.

Findings

The results indicated that ML and AI technologies organizational usage positively influenced DC initiatives. The findings depicted that DC fully mediated ML and AI-based technologies' effects on firm performance and social performance.

Research limitations/implications

This study contributed to theoretical discourse regarding the tension between organizational and social outcomes of ML and AI technologies. The study extended the role of DC as a vital strategy in achieving social benefits from ML and AI use. Furthermore, the theoretical tension of the automation-augmentation paradox was explored.

Practical implications

Organizations deploying ML and AI technologies could apply this study's insights to comprehend the organizational routines to pursue simultaneous competitive benefits and social gains. Furthermore, chief technology executives of organizations could devise how ML and AI technologies usage from a DC perspective could help settle the tension of the automation-augmentation paradox.

Social implications

Increased ML and AI technologies usage in organizations enhanced DC. They could lead to positive social benefits such as new job creation, increased compensation to skilled employees and greater gender participation in employment. These insights could be derived based on this research study.

Originality/value

This study was among the first few empirical investigations to provide theoretical and practical insights regarding the organizational and societal benefits of ML and AI usage in organizations because of their DC. This study was also one of the first empirical investigations that addressed the automation-augmentation paradox at the enterprise level.

Details

Journal of Enterprise Information Management, vol. 36 no. 6
Type: Research Article
ISSN: 1741-0398

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Article
Publication date: 23 January 2024

Ranjit Roy Ghatak and Jose Arturo Garza-Reyes

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by…

499

Abstract

Purpose

The research explores the shift to Quality 4.0, examining the move towards a data-focussed transformation within organizational frameworks. This transition is characterized by incorporating Industry 4.0 technological innovations into existing quality management frameworks, signifying a significant evolution in quality control systems. Despite the evident advantages, the practical deployment in the Indian manufacturing sector encounters various obstacles. This research is dedicated to a thorough examination of these impediments. It is structured around a set of pivotal research questions: First, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Second, it aims to elucidate these barriers' interrelations and mutual dependencies. Thirdly, the research prioritizes these barriers in terms of their significance to the adoption process. Finally, it contemplates the ramifications of these priorities for the strategic advancement of manufacturing practices and the development of informed policies. By answering these questions, the research provides a detailed understanding of the challenges faced. It offers actionable insights for practitioners and policymakers implementing Quality 4.0 in the Indian manufacturing sector.

Design/methodology/approach

Employing Interpretive Structural Modelling and Matrix Impact of Cross Multiplication Applied to Classification, the authors probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorized according to their driving power and dependence, providing a richer understanding of the dynamic obstacles within the Technology–Organization–Environment (TOE) framework.

Findings

The study results highlight the lack of Quality 4.0 standards and Big Data Analytics (BDA) tools as fundamental obstacles to integrating Quality 4.0 within the Indian manufacturing sector. Additionally, the study results contravene dominant academic narratives, suggesting that the cumulative impact of organizational barriers is marginal, contrary to theoretical postulations emphasizing their central significance in Quality 4.0 assimilation.

Practical implications

This research provides concrete strategies, such as developing a collaborative platform for sharing best practices in Quality 4.0 standards, which fosters a synergistic relationship between organizations and policymakers, for instance, by creating a joint task force, comprised of industry leaders and regulatory bodies, dedicated to formulating and disseminating comprehensive guidelines for Quality 4.0 adoption. This initiative could lead to establishing industry-wide standards, benefiting from the pooled expertise of diverse stakeholders. Additionally, the study underscores the necessity for robust, standardized Big Data Analytics tools specifically designed to meet the Quality 4.0 criteria, which can be developed through public-private partnerships. These tools would facilitate the seamless integration of Quality 4.0 processes, demonstrating a direct route for overcoming the barriers of inadequate standards.

Originality/value

This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE framework, detailing how these barriers interact with and influence each other, particularly highlighting the previously overlooked environmental factors. The analysis reveals a critical interdependence between “lack of standards for Quality 4.0” and “lack of standardized BDA tools and solutions,” providing nuanced insights into their conjoined effect on stalling progress in this field. Moreover, the study contributes to the theoretical body of knowledge by mapping out these novel impediments, offering a more comprehensive understanding of the challenges faced in adopting Quality 4.0.

Details

International Journal of Quality & Reliability Management, vol. 41 no. 6
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 6 July 2023

G. Citybabu and S. Yamini

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of…

767

Abstract

Purpose

The purpose of this paper is to investigate the research landscape of LSS 4.0 papers published in two well-known repositories, Scopus and Web of Science (WoS), in terms of publication trends, article distribution by author, journal, affiliations and country, and article clustering based on keywords, authors and countries. In addition, a literature review was carried out to build a conceptual framework of integrated Lean Six Sigma and Industry 4.0 (LSS 4.0) that encompasses operational, sustainability and human factors or ergonomics aspects.

Design/methodology/approach

The literature review of integrated Lean Six Sigma and I4.0 publications published in Scopus and WoS databases in the current decade was conducted for the present study. This study categorizes LSS, I4.0 and related research articles based on publication patterns, journals, authors and affiliations, country and continental-wise distribution and clustering the articles based on keywords and authors from the Scopus and WoS databases from 2011 to 2022 using the search strings “Lean”, “Six Sigma”, “Lean Six Sigma” and “Industry 4.0” in the Title, Abstract and Keywords using Biblioshiny, VOS viewer and Microsoft Excel.

Findings

In the recent three years, from 2020 to 2022, LSS 4.0 has been substantially increasing and is seen as an emerging and trending area. This research identifies the most influential authors, most relevant affiliations, most prolific countries and most productive journals and clusters based on keywords, authors and countries. Further, a conceptual framework was developed that includes the impact of operational, sustainability and ergonomic or human factors in LSS 4.0.

Research limitations/implications

This article assists in comprehending the trends and patterns of LSS 4.0. Further, the conceptual framework helps professionals and researchers understand the significance and impact of integrating LSS and Industry 4.0 in the aspects of human factors/ergonomic, sustainability and operations. Also, the research induce professionals to incorporate all these factors while designing and implementing LSS 4.0 in their organization.

Originality/value

This conceptual framework and bibliometric analysis would aid in identifying potential areas of research and providing future directions in the domain of LSS 4.0. It will be beneficial for academicians, professionals and researchers who are planning to apply and integrate techniques of LSS and technologies of I4.0 in their organizations and research.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 5
Type: Research Article
ISSN: 1741-0401

Keywords

Available. Open Access. Open Access
Article
Publication date: 12 October 2023

Jiju Antony, Arshia Kaul, Shreeranga Bhat, Michael Sony, Vasundhara Kaul, Maryam Zulfiqar and Olivia McDermott

This study aims to investigate the adoption of Quality 4.0 (Q4.0) and assess the critical failure factors (CFFs) for its implementation and how its failure is measured.

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Abstract

Purpose

This study aims to investigate the adoption of Quality 4.0 (Q4.0) and assess the critical failure factors (CFFs) for its implementation and how its failure is measured.

Design/methodology/approach

A qualitative study based on in-depth interviews with quality managers and executives was conducted to establish the CFFs for Q4.0.

Findings

The significant CFFs highlighted were resistance to change and a lack of understanding of the concept of Q4.0. There was also a complete lack of access to or availability of training around Q4.0.

Research limitations/implications

The study enhances the body of literature on Q4.0 and is one of the first research studies to provide insight into the CFFs of Q4.0.

Practical implications

Based on the discussions with experts in the area of quality in various large and small organizations, one can understand the types of Q4.0 initiatives and the CFFs of Q4.0. By identifying the CFFs, one can establish the steps for improvements for organizations worldwide if they want to implement Q4.0 in the future on the competitive global stage.

Originality/value

The concept of Q4.0 is at the very nascent stage, and thus, the CFFs have not been found in the extant literature. As a result, the article aids businesses in understanding possible problems that might derail their Q4.0 activities.

Details

International Journal of Quality & Reliability Management, vol. 41 no. 4
Type: Research Article
ISSN: 0265-671X

Keywords

Available. Open Access. Open Access
Article
Publication date: 2 January 2025

Federico Barravecchia, Luca Mastrogiacomo and Fiorenzo Franceschini

The aim of this study is to enhance the product quality management by proposing a framework for the classification of anomalies in digital voice of customer (VoC), i.e. user…

92

Abstract

Purpose

The aim of this study is to enhance the product quality management by proposing a framework for the classification of anomalies in digital voice of customer (VoC), i.e. user feedback on product/service usage gathered from online sources such as online reviews. By categorizing significant deviations in the content of digital VoC, the research seeks to provide actionable insights for quality improvement.

Design/methodology/approach

The study proposes the application of topic modeling algorithms, in particular the structural topic model, to large datasets of digital VoC, enabling the identification and classification of customer feedback into distinct topics. This approach helps to systematically analyze deviations from expected feedback patterns, providing early detection of potential quality issues or shifts in customer preferences. By focusing on anomalies in digital VoC, the study offers a dynamic framework for improving product quality and enhancing customer satisfaction.

Findings

The research categorizes anomalies into spike, level, trend and seasonal types, each with distinct characteristics and implications for quality management. Case studies illustrate how these anomalies can signal critical shifts in customer sentiment and behavior, highlighting the importance of targeted responses to maintain or enhance product quality.

Research limitations/implications

Despite its contributions, the study has some limitations. The reliance on historical data may not hold in rapidly changing markets. Additionally, text mining techniques may miss implicit customer sentiment.

Practical implications

The findings suggest that companies can enhance their quality tracking tools by digital VoC anomaly detection into their standard practices, potentially leading to more responsive and effective quality management systems.

Originality/value

This paper introduces a novel framework for interpreting digital VoC anomalies within the Quality 4.0 context. By integrating text mining techniques with traditional quality tracking, it offers a novel approach for leveraging customer feedback to drive continuous improvement.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

Keywords

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