Search results

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.

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.

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.

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 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 I4.0 and TPM, which will assist them in more effectively implementing an integrated system of I4.0 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 I4.0 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.

Due to the absence of industry and region-specific implementation guides, change efforts, in particular continuous improvement implementations, continue to report high failure rates. The purpose of this paper is, therefore, to present a finalised implementation framework specifically tailored for manufacturing companies.

A conceptual framework derived from the existing literature is validated, through a Delphi study, by an expert panel to review its content and suitability for a practical application.

This paper proposes a finalised framework tailored to the practical needs of users. The results of the Delphi approach offer a phased implementation framework that provides an overview of the implementation process of continuous improvement initiatives and the key activities involved. The framework is suitable for use by both business leaders and continuous improvement practitioners with varying degrees of previous implementation experience.

The research was carried out in the UK and is specifically focused on the manufacturing industry. It is therefore not clear the applicability of the framework presented to other regions and industries. The framework, although validated through several phases of research, still requires practical application and testing.

Business leaders and continuous improvement practitioners will benefit from having the necessary content presented in a manner that will promote its practical application. It has also been demonstrated that the framework is robust in its content, incorporating the literature findings as well as the experience of an expert panel encompassing 20 people.

This study aims to examine current research on the relationship between Operational Excellence and Healthcare 4.0 (H4.0) for healthcare organizations.

The authors have performed a systematic literature review of 102 documents published between 2011 and 2022 from the Scopus database to identify the research trends on Operational Excellence and H4.0. Through a descriptive bibliometric analysis, this study has highlighted the year-wise trend in publication, top authors, prominent sources of publications, the country-wise spread of research activities and subject area analysis. Furthermore, through content analysis, this study has identified four clusters and proposed directions for future research of each identified cluster.

Results reflect overall growth in this area, with a few parts of the world being underrepresented in research related to Operational Excellence and H4.0. The content analysis focused on describing challenges pertaining to healthcare industries and the role of Operational Excellence tools and H4.0 technologies in dealing with various healthcare delivery aspects. The authors concluded their analysis by proposing a theoretical framework and providing theoretical and managerial implications of the study.

To the best of the authors’ knowledge, the paper is one of the first to analyze the existing literature on the healthcare sector at the interface of Operational Excellence and H4.0 technologies. The conceptual framework and cluster-wise future research prepositions are some of the unique offerings of the study.

In recent times, reverse logistics (RL) is gaining significant traction in various automobile industries to recapture returned vehicles’ value. A good RL program can lower manufacturing costs, establish a green supply chain, enhance customer satisfaction and provide a competitive advantage. However, reducing disruptions and increasing operational efficiency in the automobile RL requires implementing innovative technology to improve information flow and security. Thus, this manuscript aims to examine the hurdles in automobile RL activities and how they can be effectively tackled by blockchain technology (BCT). Merging BCT and RL provides the entire automobile industry a chance to generate value for its consumers through effective vehicle return policies, manufacturing cost reduction, maintenance records tracking, administration of vehicle information and a clear payment record of insurance contracts.

This research is presented in three stages to accomplish the task. First, previous literature and experts' opinions are examined to highlight certain factors that are an aggravation to BCT implementation. Next, this study proposed an interval-valued intuitionistic fuzzy set (IVIFS) – decision-making trial and evaluation laboratory (DEMATEL) with Choquet integral framework for computing and analyzing the comparative results of factor interrelationships. Finally, the causal outline diagrams are plotted to determine the influence of factors on one another for BCT implementation in automobile RL.

This study has categorized the barriers to BCT implementation into five major factors – operational and strategical, technical, knowledge and behavioral, financial and infrastructural, and government rules and regulations. The results revealed that disreputable technology, low-bearing capacity of IT systems and operational inefficiency are the most significant factors to be dealt with by automobile industry professionals for finer and enhanced RL processes utilizing BCT. The most noticeable advantage of BCT is its enormous amount of data, permitting automobile RL to develop client experience through real-time data insights.

This study reveals several factors that are hindering the implementation of BCT in RL activities of the automobile industry. The results can assist experts and policymakers improve their existing decision-making systems while making an effort to implement BCT into the automobile industry's RL activities.

Although there are several studies on the benefits of BCT in RL and the adoption of BCT in the automobile industry, individually, none have explicated the use of BCT in automobile RL. This is also the first kind of study that has used IVIFS-DEMATEL with the Choquet integral framework for computing and analyzing the comparative results of factor interrelationships hindering BCT implementation in automobile RL activities.

Recently, the concept of the circular economy (CE) has witnessed significant momentum in academic and professional circles. However, there is a dearth of research that studies the enabling factors of the CE in the era of digital transformation. The existing research aimed to identify the impact of Industry 4.0 readiness on the CE in manufacturing firms operating in Jordan, as well as to identify the mediating role of the industrial Internet of things and big data analytics.

For this work objectives, 380 questionnaires were analyzed. Convergent validity and discriminant validity tests were performed through partial least squares-structural equation modelling (PLS-SEM) in the Smart-PLS programme. Data reliability was confirmed. A bootstrapping technique was used to analyze the data and then hypothesis testing was performed.

The results indicate that Industry 4.0 readiness, industrial Internet of things (IIoT) and big data analytics positively enable CE, also the IIoT and big data analytics positively mediate the nexus between Industry 4.0 readiness and CE.

This study promotes the idea of focusing on Industry 4.0 readiness to enhance CE in the Jordanian manufacturing sector and knowing the effect of IIoT and big data analytics in this relationship.

This research developed a theoretical model to understand how Industry 4.0 readiness might enhance the CE in manufacturing firms by invoking the IIoT and big data analytics as mediating constructs in the relationship between Industry 4.0 readiness and CE. This paper offers new theoretical and practical contributions that add value to industry 4.0 and CE literature by testing these constructs' mediation models in the manufacturing sector.

This study aims to review the role of green training and green work life balance (GWLB) on sustainable organizational performance (SOP) with a moderating variable “Emotional Intelligence” (EI).

For the development of the construct of the present study, a Scopus database was selected and research papers published in indexed journals were considered. Relevant keywords were selected and literature was searched on green training, EI, SOP, GWLB. The literature was reviewed to find out the linkage and possibility of development of integrated model. The main focus was on highlighting the relevance of green training on GWLB and its influence on SOP.

SOP can be achieved with the intervention of EI and GWLB; further green training is one of the influential practices of human resource development (HRD) which helps to develop the green behavior.

It can give new insight to the organization for application of green human resource practices for SOP. Development and designing the cohesive environmental work culture and willingness to protect environment through green training can be implemented by HRD. Perhaps, the application of green training encourages GWLB.

Quantitative research and cross sectional study is required to find out the intervening role of EI and work–life balance between green training and SOP across a broader range of sectors.

This research extends the literature review and developed a new integrated model which shows the link between green training and SOP.