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The purpose of this paper is to present a systematic approach to conduct a diagnosis of the current status of a company’s quality management systems (QMS) and business processes.

The approach proposed is based upon the assessment of the maturity level of a company’s QMS, for which a “maturity diagnostic instrument” is also proposed, a self-assessment exercise using a business excellence model and a first-party quality audit.

The integration of a QMS’ maturity assessment, a self-assessment exercise and a quality audit may provide a more thorough evaluation of various company’s systems and operations. This paper provides organisations, and their managers, with a systematic approach to help them understand better the current performance of their QMSs and business processes.

This paper’s main contribution consists in the proposal of a novel approach for organisation to measure and understand the status of their QMS and business processes. Subsequently, better management decisions to improve a company’s operations can be taken.

The academic literature and research lines exploring the effect of quality improvement methods on environmental performance still remain in early stages. The purpose of this paper is therefore to investigate, through a systematic review of the existing academic literature, the environmental (green) impact of using quality and operations improvement methods such as Lean, Six Sigma and Lean Six Sigma. This includes the impact on energy saving and the usage of natural resources.

This study follows a systematic literature review approach through which it analyses research papers published in top 16 operations and quality management journals. No specific time frame was established, but a set of keywords were used to short-list the articles. A sample of 70 articles was finally short-listed and analysed to provide a discussion on environmental concerns related to Lean, Six Sigma and Lean Six Sigma.

The comprehensive review of short-listed articles indicates that both Lean and Six Sigma can be considered effective methods to support the conservation of resources, combat global warming and saving energy. Various scholars provide evidence of this, and as such, organisations should not only consider these methods to manage quality and improve operational performance but also meet environmental regulations. A set of research questions that demands further investigation has also been proposed based on the findings of this research.

This study is limited to a sample of 70 articles collected from top 16 operations and quality management journals. The search of journals is also limited to a set of key words (“Lean”, “Green”, “Six Sigma”, “environment”, “sustainable” and “sustainability”) used to short-list the sample size.

The study shows that organisations can consider the adoption of Lean, Six Sigma and Lean Six Sigma to meet environmental regulations, save costs and also meet quality management standards. This will contribute in helping organisations to formulate more effective and inclusive strategies which do not only consider the quality and operational dimensions but also the environmental dimension.

Literature exploring the environmental/green impact of quality management methods commonly used in industry is limited. There is also a lack of studies aiming to investigate the green impact of Lean and Six Sigma in top operations and quality management journals. The study focusing on investigating the green impact of Lean, Six Sigma and Lean Six Sigma methods altogether is also a research first of its kind.

The purpose of this research is to establish a conceptual model to understand the impact of Total Productive Maintenance (TPM) and Industry 4.0 (I4.0) on the transition of a Circular Economy (CE). Also, the paper explores the combined impact of TPM, I4.0 and CE on the sustainability performance (SP) of manufacturing firms.

The conceptual model is proposed using the dynamic capability view (DCV) and empirically validated by partial least squares-structural equation modelling (PLS-SEM) using 304 responses from Indian manufacturing firms.

The results suggest that I4.0 positively impacts TPM, CE and SP, also showing TPM's positive impact on CE and SP. In addition, CE has a positive influence on the SP of manufacturing firms. Furthermore, CE partially mediates the relationship between I4.0 and SP with TPM and SP. The study also identifies TPM, I4.0 and CE as a new bundle of dynamic capabilities to deliver SP in manufacturing firms.

The present research adds to the knowledge and literature on DCV by identifying the importance of CE in the settings of I4.0 and TPM, especially in the context of sustainability. Also, the current study offers a new set of dynamic capabilities and provides some significant future recommendations for researchers and practitioners.

Eco-innovation is a relatively recent construct in the literature, which nowadays more and more researchers and academics consider as one of the strategies that generate a higher level of sustainable and business performance. However, little is known about the influence of eco-innovation practices on sustainable performance and business performance, particularly in the automotive and auto parts industry. Therefore, this paper aims to fill this knowledge gap and explore the aforementioned interdependence.

The influence of eco-innovation practices on sustainable performance and business performance is investigated through a research framework consisting of 5 constructs, 25 items and 6 hypotheses derived from an extensive review of the literature. A self-administered questionnaire was distributed to 460 companies in the automotive and auto parts industry in Mexico. The data were analyzed through a confirmatory factor analysis, descriptive statistics and structural equation modeling.

The results obtained indicated that eco-innovation practices have a positive influence on both sustainable performance and business performance in the automotive and auto parts industry.

This paper provides further insightful evidence of the influence of eco-innovation practices on sustainable performance and business performance, particularly in the automotive and auto parts industry.

The role of data analytics is significantly important in manufacturing industries as it holds the key to address sustainability challenges and handle the large amount of data generated from different types of manufacturing operations. The present study, therefore, aims to conduct a systematic and bibliometric-based review in the applications of machine learning (ML) techniques for sustainable manufacturing (SM).

In the present study, the authors use a bibliometric review approach that is focused on the statistical analysis of published scientific documents with an unbiased objective of the current status and future research potential of ML applications in sustainable manufacturing.

The present study highlights how manufacturing industries can benefit from ML techniques when applied to address SM issues. Based on the findings, a ML-SM framework is proposed. The framework will be helpful to researchers, policymakers and practitioners to provide guidelines on the successful management of SM practices.

A comprehensive and bibliometric review of opportunities for ML techniques in SM with a framework is still limited in the available literature. This study addresses the bibliometric analysis of ML applications in SM, which further adds to the originality.

Equipment performance helps the manufacturing sector achieve operational and financial improvements despite process variations. However, the literature lacks a clear index or metric to quantify the monetary advantages of enhanced equipment performance. Thus, the paper presents two innovative monetary performance measures to estimate the financial advantages of enhancing equipment performance by isolating the effect of manufacturing fluctuations such as product mix price, direct and indirect characteristics, and cost changes.

The research provides two measures, ISB (Improvement Saving Benefits) and IEB (Improvement Earning Benefits), to assess equipment performance improvements. The effectiveness of the metrics is validated through a three stages approach, namely (1) experts' binary opinion, (2) sample, and (3) actual cases. The relevant data may be collected through accounting systems, purpose-built software, or electronic spreadsheets.

The findings suggest that both measures provide an effective cost–benefit analysis of equipment performance enhancement. The measure ISB indicates savings from performance increases when equipment capacity is greater than product demand. IEB is utilised when equipment capacity is less than product demand. Both measurements may replace the unitary cost variation, which is subject to manufacturing changes.

Manufacturing businesses may utilise the ISB and IEB metrics to conduct a systematic analysis of equipment performance and to appreciate the financial savings perspective in order to emphasise profitability in the short and long term.

The study introduces two novel financial equipment performance improvement indicators that distinguish the effects of manufacturing variations. Manufacturing variations cause cost advantages from operational improvements to be misrepresented. There is currently no approach for manufacturing organisations to calculate the financial advantages of enhancing equipment performance while isolating production irregularities.

Total Productive Maintenance (TPM) could act as a practical approach to offer sustainability deliverables in manufacturing firms aligning with the natural resource-based view (NRBV) theory's strategic capabilities: pollution prevention, product stewardship and sustainable development. Also, the emergence of Blockchain Technology (BCT) and Circular Economy (CE) are proven to deliver sustainable outcomes in the past literature. Therefore, the present research examines the relationship between BCT and CE and TPM's direct and mediation effect through the lens of NRBV theory.

The current study proposes a conceptual framework to examine the relationship between BCT, CE and TPM and validates the framework through the Partial Least Squares Structural Equation Modeling. Responses from 316 Indian manufacturing firms were collected to conduct the analysis.

The investigation outcomes indicate that BCT positively influences CE and TPM and that TPM has a significant positive impact on CE under the premises of NRBV theory. The results also suggest that TPM partially mediates the relationship between BCT and CE.

This research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities and TPM mediation.

The positive influence of TPM and BCT on CE could initiate the amalgamation of BCT-TPM, improving the longevity of production equipment and products and speeding up the implementation of CE practices.

This research fills a gap in the literature by investigating the effect of BCT and TPM on CE within the framework of the NRBV theory. It explores the link between BCT, TPM and CE under the NRBV theory's strategic capabilities along with TPM mediation.

The purpose of this paper is to assess the quality practices of European pharmaceutical manufacturers to determine the level of readiness of this industrial sector to implement and/or sustain lean manufacturing (LM).

An assessment framework developed by Al-Najem et al. (2013) was adapted to evaluate how ready European pharmaceutical manufacturers are to implement and/or sustain LM. Therefore, the lean readiness (LR) level of these organisations was assessed through six quality practices related to LM. These included: processes, planning and control, human resources, top management and leadership, customer relations, and supplier relations. One research question and three hypotheses were formulated and tested using a combination of descriptive statistics and non-parametric Mann-Whitney tests. Data were collected through a survey questionnaire distributed to 310 European pharmaceutical manufacturers and responded by 37 of these organisations.

Overall, the results of this study indicate an inadequate level of LR for the participating firms. Simultaneously, it was concluded that factors such as company size, type of relationships with suppliers and ISO 9000 certification do not have an effect on the quality practices, and hence LR level, of European pharmaceutical manufacturing organisations.

This study provides crucial information regarding the LR level of European pharmaceutical manufacturers, which can now be aware of the areas in their practices that require further improvement towards a successful lean journey. Simultaneously, organisations in the pharmaceutical sector that intend to implement LM can consider the results of this study and evaluate their readiness level. Managers can, therefore, refer to this research and use it as a platform to take better decisions regarding what quality aspects of their operations need to be enhanced to successfully deploy or sustain a lean strategy.

This research is one of the very few studies that have focussed on evaluating whether the European pharmaceutical manufacturing industry is ready to successfully implement or sustain LM. Therefore, this research expands the limited existent body of knowledge of LM in this industry.

Key success factors (KSFs) of total productive maintenance (TPM) have historically played a vital role in attaining economic and ecological sustainability but have overlooked social sustainability. Hence, this study analyses and ranks the most significant TPM KSFs for attaining social sustainability in manufacturing small and medium enterprises (SMEs).

The research employs a deductive methodology to identify the relevant TPM KSFs and social sustainability indicators and then uses Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to rank the TPM KSFs in order to achieve social sustainability, followed by a sensitivity analysis to assess the methodological robustness.

The findings indicate that the top five TPM KSFs influencing social sustainability are employee health and safety, organizational culture, top management commitment, employee engagement and effective communication and effective workplace management. In addition, the results indicate that effective equipment utilization is the least significant TPM key factor affecting social sustainability.

SME manufacturing managers do not need to worry about all of the TPM KSFs if they only concentrate on the ones that will have the most impact. If managers use the top 5 TPM KSFs as a starting point, they may create customized TPM training programs for their companies. As a result, this will facilitate the efforts of their personnel toward social sustainability.

In the existing literature, little emphasis has been paid to social sustainability and how SMEs may implement these practices. This research adds to the current theory of TPM and social sustainability and sheds light on how SMEs might use TPM to advance toward more socially sustainable operations.