Investigating the Barriers to Quality 4.0 Adoption in the Indian Manufacturing Sector: Insights and Implications for Industry and Policymaking

Purpose: The research explores the shift to Quality 4.0, examining the move towards a data-focused 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: Firstly, it seeks to identify the key barriers that impede the adoption of Quality 4.0. Secondly, 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 (ISM) and Matrix Impact of Cross Multiplication Applied to Classification (MICMAC), we probe the interdependencies amongst fourteen identified barriers inhibiting Quality 4.0 adoption. These barriers were categorised 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 organisational barriers is marginal, contrary to theoretical postulations emphasising their central significance in Quality 4.0 assimilation. Originality: This research delineates specific obstacles to Quality 4.0 adoption by applying the TOE (Technology-Organization-Environment) 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 standardised Big Data Analytics (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. 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

A Six-Sigma DMAIC Approach to Improve the Sales Process of a Technology Start-Up

Despite the adoption of Six-Sigma in different service sectors, its application in the Sales function of a Technology-based Start-up has not been explored. This paper deploys an action research-based study methodology and conducts a thorough analysis of a Technology Start-up company in Indonesia, using Six-Sigma principles and the Define-Measure-Analyse-Improve-Control (DMAIC) approach. Statistical validation of the causes of problems helped to formulate a strategy that may have otherwise not been possible. The results of the study and proposed solutions confirm the potential benefits of adopting Six-Sigma in the Sales function of technology start-ups to reduce, particularly, customer waiting time. The novelty of this research lies in the fact that it applies Six-Sigma in a transactional process such as sales, which earlier studies have not explored in depth. This paper can be employed as a reference for organisations to undertake and guide specific process improvement projects similar to the one presented

The circular economy impact on small to medium enterprises

In recent years, the literature surrounding the circular economy has grown. While the notion of reducing, recycling and reusing have become adopted practices in many organisations under the umbrella of sustainability, having a circular economy is arguably the next generation step, in terms of sustainability. A systematic literature review on the circular economy identified a gap in the research, regarding the impact at the micro level to be placed on small to medium enterprises. The research concludes that a paradigm shift in circular thinking at the micro level is required, and that further research is needed to identify new skills, resources, approaches, and business models to enable subject matter experts (SMEs) to adopt a circular practice.N/

Optimisation of a distribution system in the retail industry: An Australian retail industry

This paper develops a mathematical model based on inventory routing problem that aims to minimise transportation cost, inventory carrying cost and optimises delivery schedules in a retail Australian industry. A supply chain is considered which comprises of a single distribution centre, having homogenous fleet of vehicles, supplying a single product to multiple retailers having deterministic demand. The mathematical model takes into account varying level of road congestion.N/

Integrating Industry 4.0 and Total Productive Maintenance for Global Sustainability

The integration of Total Productive Maintenance (TPM) and industry 4.0 (I4.0) is an emerging model, and the global pressure of various stakeholders raises scepticism of any emerging model towards providing sustainability. Therefore, this research aims to identify and rank the potential significant drivers of an integrated model of I4.0 and TPM to guide manufacturing enterprises towards sustainability. This research follows a four-phase methodology including literature review and expert opinion to select the sustainability indicators and I4.0 integrated TPM key drivers, followed by employing the Analytic hierarchy process (AHP) approach for weight determination of sustainability indicators. The research then deploys the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to prioritise the I4.0 integrated TPM key drivers based on their effect on various sustainability indicators. Finally, a sensitivity analysis is conducted to check the robustness of the TOPSIS. The findings establish the top five most influential key drivers of an I4.0 integrated TPM system, which include Top management support, Formal I4.0 adoption program, Mid-management involvement and support, Solid TPM baseline knowledge, and High engagement of the production team. These top drives can lead manufacturing firms towards sustainability. The digitalisation of shop floor practices, such as TPM could be adapted by shop floor managers and policymakers of manufacturing companies to deliver sustainability-oriented outcomes. In addition, this research may aid decision-makers in the manufacturing sector in identifying the most important drivers of Industry 4.0 and TPM, which will assist them in more effectively implementing an integrated system of Industry 4.0 and TPM to practice sustainability. The scope of TPM applicability is wide, and the current research is limited to manufacturing companies. Therefore, there is a huge scope for developing and testing the integrated system of Industry 4.0 and TPM in other industrial settings, such as the textile, food and aerospace industries. This research makes a first-of-its-kind effort to examine how an I4.0 integrated TPM model affects manufacturing companies' sustainability and how such effects might be maximised

Supply Chain Resilience Strategies and their Impact on Sustainability: An Investigation from the Automobile Sector

This study proposes a framework comprising supply chain (SC) resilience strategies to handle low-frequency high impact (LFHI) disruptive events. It also evaluates the impact of SC resilience strategies’ implementation on the triple bottom line of SC sustainability. A hybrid three-phased method is proposed to meet the research objectives of the study. In the first phase, the study employs the Delphi technique to select SC resilience strategies and SC sustainability dimensions. In the second phase, the Best–Worst Method (BWM) is employed to assess the relative weights of resilience strategies. Finally, in the third stage, summative Likert scoring is used to understand the impact of SC resilience strategies on the SC sustainability triple bottom line (3BL).The outcomes reveal that firms give due importance to inter-organizational relationships and supplier nearness for supply continuity. In the sustainability context, the obtained scores proved that resilience strategies have the maximum impact on economic sustainability, followed by environmental sustainability. This is the first study that examines aspects of SC resilience strategies and quantifies their impact on the triple bottom line of SC sustainability. This study is specific to the automobile sector; sectoral diversity may expose similarities and dissimilarities in the approach. The outcome establishes that supplier–manufacturer relationships need to be strengthened further to tackle any future uncertainties. Besides, supplier location decisions may also be revisited. The strategies proposed will aid SC managers to make informed decisions to prepare for uncertain events. In the face of uncertain events, often SC’s trade-off sustainability in pursuit of resilience. It manifests that resilience is a prerequisite for SC sustainability. While planning SCs, organizations often choose either sustainability or resilience. Thus, this study acknowledges the need to develop effective SC resilience strategies that are in harmony with the sustainability agenda

Green Lean Six Sigma Sustainability Oriented Project Selection and Implementation Framework for Manufacturing Industry

Green Lean Six Sigma (GLS) project selection has been done based on the six sustainability-oriented criteria formed from seventeen sub-criteria (found from the literature and developed by authors).The weights of the criteria have been determined through the entropy method. The projects have been ranked based on the criteria through the advanced decision-making approach: Grey relation analysis (GRA). The results of the study were validated using best worst method (BWM) and sensitivity analysis. Purpose: The present study deals with the selection of the sustainability-oriented GLS project for the manufacturing industry in the complex decision-making environment. Moreover, the study also proposes a GLS implementation framework for improved organizational performance. It has been found that the productivity-related criterion is the most significant among other criteria with entropy weight of 0.2721. GRA has been used in this research work to rank the potential GLS projects in a manufacturing industry based on six sustainability criteria, to select a project that exhibits the maximum potential for sustainable improvement. The machine shop has been found as the most significant GLS project with grey relation grade of 0.4742. Originality: With increased globalized competition in recent times, new projects are being considered as the foundation stone for organizational success. The decision making becomes quite complex to select an effective project due to the intriguing nature of various criteria, subcriteria, and different aspects of sustainability. The present study is the first of its kind that provides ways for the selection of sustainability-oriented GLS projects.The present study facilitates practitioners and industrial managers to implement an inclusive GLS approach for improved sustainability dynamics through effective GLS project selection and implementation framework

A review of lean and agile management in humanitarian supply chains: analysing the pre-disaster and post-disaster phases and future directions

Disasters have quadrupled over the last two decades leading to unprecedented loss of life. The objective of disaster-focussed humanitarian supply chains (HSCs) is to ensure saving maximum lives with limited resources; despite severe uncertainties. Therefore, significant research has investigated lean and agile in HSCs; to effectively source and speedily deploy resources, with minimum wastage; in each disaster life-cycle phase. However, the literature and research findings are currently highly disjointed regarding how lean and agile principles may be aligned with different HSC activities in the disaster management lifecycle; and do not provide a collective understanding for practitioners and researchers. This paper reviews and organises the literature on HSCs in relation to lean and agile paradigms, focussing on the pre-disaster (mitigation and preparedness) and post-disaster (response and recovery) phases. Findings reveal, all phases benefit from both lean and agile, with agile benefitting the response phase most. The phases are inter-dependent and identifying optimum decoupling points for lean and agile principles are crucial. Majority research has focussed on individual or a couple of phases. Therefore, authors recommend research on integrating the functions of the different phases by employing lean and agile principles, to generate rapid response, economies of scale and cost minimisation

Slowing the fast fashion industry: an all-round perspective

The fashion sector contributes significantly to global environmental pollution. Clothing manufacturing and transportation produce a large amount of greenhouse gas emissions. Recent research has shown that nowadays, the number of consumers that are more willing to pay higher prices for clothes with high sustainability content is growing. This paper provides a broad framework of current trends in the fashion, textile, and garment industry, highlighting circular and slow fashion values that companies and policymakers should address in the coming years to maintain their competitiveness in the market and promote sustainable development. The EU Strategy for Sustainable and Circular Textiles is expected to help fashion enterprises achieve more circular, sustainable, and resilient value chains. Notably, encouraging natural and recycled textiles, design for reuse and recycling, second-hand retail and repair, and product-as-a-service models, particularly for items with high turnover rates, have been highlighted as critical factors for reducing the fashion industry's environmental implications

Theorizing the Principles of Sustainable Production in the context of Circular Economy and Industry 4.0.

The concept of Sustainable Production is evolving with changes triggered by the emergence of new economic and industrial models such as Circular Economy and Industry 4.0. However, most studies that currently link these concepts are based on the principles of Sustainable Production defined 20 years ago. Therefore, the primary aim of this study is to redefine the principles that should govern Sustainable Production operations in the transition towards a Circular Economy and smart industry models. To this end, an initial proposal of 11 principles was shared with 11 world-class experts (academics and practitioners) and a consensus proposal was sought through a Delphi Panel. Ten principles emerged from this study, which were evaluated by experts according to criteria of significance, parsimony, semantic consistency and empirical adequacy. Additionally, to study the relationships between the ten principles, the Interpretative Structural Model (ISM) technique was applied. The ISM technique identified which principles are independent of or dependent on each other and established relationships between the principles. The findings suggest that Principle 5 ("Prioritize employees' well-being"), Principle 6 ("Enhance management commitment to sustainability"), Principle 9 ("Measure and optimize sustainable processes") and Principle 10 ("Boost the use of sustainable technologies") help to establish an ideal context to enhance the development of the rest of the principles that characterize Sustainable Production. The presentation of the ten principles opens new possibilities for researchers while helping managers to better understand sustainability in terms of production and, therefore contribute to achieving SDG 12