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This study aims to explore the integration of Industry 4.0 technologies with lean six sigma practices in the manufacturing sector for enhanced process improvement.

This study used a fuzzy decision-making trial and evaluation laboratory approach to identify critical Industry 4.0 technologies that can be harmonized with Lean Six Sigma methodologies for achieving improved processes in manufacturing.

The research reveals that key technologies such as modeling and simulation, artificial intelligence (AI) and machine learning, big data analytics, automation and industrial robots and smart sensors are paramount for achieving operational excellence when integrated with Lean Six Sigma.

The study is limited to the identification of pivotal Industry 4.0 technologies for Lean Six Sigma integration in manufacturing. Further studies can explore the implementation challenges and the quantifiable benefits of such integrations.

Integrating Industry 4.0 technologies with Lean Six Sigma enhances manufacturing efficiency. This approach leverages AI for predictive analysis, uses smart sensors for energy efficiency and adaptable robots for flexible production. It is vital for competitive advantage, significantly improving decision-making, reducing costs and streamlining operations in the manufacturing sector.

The integration of Industry 4.0 technologies with Lean Six Sigma in manufacturing has significant social implications. It promotes job creation in high-tech sectors, necessitating advanced skill development and continuous learning among the workforce. This shift fosters an innovative, knowledge-based economy, potentially reducing the skills gap. Additionally, it enhances workplace safety through automation, reduces hazardous tasks for workers and contributes to environmental sustainability by optimizing resource use and reducing waste in manufacturing processes.

This study offers a novel perspective on synergizing advanced Industry 4.0 technologies with established Lean Six Sigma practices for enhanced process improvement in manufacturing. The findings can guide industries in prioritizing their technological adoptions for continuous improvement.

This study aims to explore the interrelationships among human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity.

This study used a cross-sectional survey approach, and quantitative data were collected from 324 Indian auto-component manufacturing firms. Confirmatory factor analysis was used, followed by structural equation modelling techniques for the conceptual model, which incorporated a complete set of 11 hypotheses.

The results confirmed that human-related lean practices trigger lean production shop floors and improve process quality. Furthermore, the study revealed the positive impact of a lean production shop floor on process quality and inventory management and the positive impact of process quality on both operational and business productivity. Finally, inventory management is of the utmost importance in achieving better operational and business productivity, and operational productivity positively leads to business productivity.

The findings of this study can benefit auto-component manufacturing firms by elucidating the complex relationships between human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity. Better knowledge of these relationships will enable firms to enhance efficiency levels, reduce costs and resource wastage and improve their overall performance. This study provides a good understanding of the interplay between lean and quality factors and their influence on inventory management and business performance.

In this study, the authors assess the current state of lean product development and the lean production shop floor, along with the impact of the former on process quality and the latter on product quality and customer complaint reduction. The interplay between process and product quality and customer complaint reduction is assessed, along with their impacts on business performance.

Data were collected from 377 managers working at auto-component manufacturing firms in India. Confirmatory factor analysis was used for scale validation, and structural equation modelling was employed to test the research hypotheses.

The results of the statistical analyses reveal the positive influence of a lean production shop floor on process quality and lean product development on product quality and customer complaint reduction, and thereby on business performance.

The findings of this research provide insights into the interplay between lean and quality factors and their influence on customer complaint reduction and business performance. Practitioners can use the proposed model to strategically design unique products and improve the efficiency and effectiveness of the production shop floor, which can help enhance the product and process quality. This can reduce customer dissatisfaction and improve the business performance.

Few studies have simultaneously investigated the influence of lean product development and lean production shop floors in the Indian manufacturing context. To the best of our knowledge, this study is one of the first attempts to include customer complaint reduction as a construct in a lean model. It helps identify and prioritise the enablers of business performance and provides valuable insights for practitioners to strengthen lean implementation to attain a competitive edge.

The purpose of this study is to learn how the incorporation and use of leanness, agility and innovation in Indian manufacturing micro, small and medium enterprises (MSMEs) affect their bottom lines and how much these factors contribute to the MSMEs’ ability to meet their long-term sustainability goals.

The suggested model was subjected to data validation and additional empirical validation using a sample of 411 Indian manufacturing MSMEs. The analysis of construct measures is conducted through the utilization of confirmatory factor analysis, a statistical technique that is grounded in the theoretical framework of structural equation modeling (SEM). In addition, path model analysis was applied for the purpose to validate the assumptions that were included in the structural models.

Consistent with the proposed model, the findings of this study demonstrate that leanness, agility and innovation have a substantial favorable impact on the sustainability of a company’s performance. These findings may be helpful in gaining professionals, academics and policymakers to acknowledge the significance of leanness, agility and innovation in enhancing the long-term sustainability of MSMEs and enhancing the overall performance of a particular company. This research excluded the service industries-based research papers.

Many research in the field of manufacturing industries that have adopted leanness, agility, innovativeness and sustainability as individual approaches or as a collective methodology of two or more were considered in the current study. This research excluded the service industries-based research papers.

This literature review has recognized and analyzed various dimensions and roles of leanness, agility, innovativeness and sustainability that are prevalent in manufacturing industries that include the positive and negative effects on the performance of the industries. The research enlightens the path and shows future directions for research to develop efficient, effective and sustainable manufacturing industries.

By promoting the concept of focusing on the “human factor”, namely, stakeholder perspectives, the MSME sector is propagating a strategy that moves away from an excessive focus on technology and toward a more humane one. Through the application of the three key concepts of leanness, agility and innovation, this work aims to create a framework for measuring the sustainability performance of micro-, small- and medium-sized enterprises (MSMEs), with the ultimate goal of assisting the country in achieving the Sustainable Development Goals in the fields of industry, innovation and infrastructure by supporting environmentally friendly and resource-conserving businesses that give back to society and the natural environment.

The objective of this research is to assess the importance and effectiveness of integrating various approaches such as leanness, agility, innovativeness and sustainability within the framework of manufacturing micro, small, and medium enterprises (MSMEs). The authors hope that by going further into these concepts, they will be able to broaden their understanding and get a more comprehensive insight into the role that these concepts play and how they might be successfully used within this environment.

Today, manufacturing companies are facing a fierce competition and are under great pressure to cut costs for survival in the market. So emphasis is given to enhance quality, minimize waste, customer delight and increasing productivity through reduction in wastage of resources. But, most companies hesitate to implement all measures simultaneously to acquire lean manufacturing because of some practical/ capital constraints. Therefore, the purpose of this paper is to develop a phase-wise approach to implement lean manufacturing.

The paper opted for an exploratory study using the qualitative flexible system methodology framework proposed by Sushil (1994) and options field methodology proposed by Warfield (1982, 1990) including rigorous group discussion comprising the employees representing middle and senior management with productivity improvement backgrounds. The response of experts was recorded using a specially designed instrument in the light of the parameters suggested in group discussion. The measures/ actions were arranged in the decreasing order of their cumulative score.

The paper provides a phase-wise approach to implement lean manufacturing. Mixed approach is preferred over the other three approaches to implement lean manufacturing. Thirty measures/actions contributing to mixed approach are identified to implement lean manufacturing in three phases. A three-phase approach is developed: 10, 14 and six measures in the first, second and third phases, respectively, are identified to implement lean manufacturing after considering the practical constraints faced by the companies.

All the measures/actions suggested to implement lean manufacturing are focused on the engineering manufacturing industry. Thus, the research results may lack generalizability and are limited to engineering manufacturing industry. The model developed in this research is based upon experts’ opinions. The experts’ opinion may be biased. The results of the model may vary in the real-world setting.

The present paper provides guidelines to practitioners for implementing lean manufacturing in phases. Hopefully, this study will motivate the firm’s management for implementing lean manufacturing and limiting the effect of practical constraints and scarcity of resources.

This paper fulfills and identifies the need to develop an approach to implement lean manufacturing phase wise because of practical constraints.

Dietary diversity (DD) is a proxy indicator of nutrient adequacy and has been propagated as a health beneficial component of dietary behavior. This study aims to understand DD and its association with lipid indices among Indian Kho-Kho players.

In all, 50 Indian Kho-Kho players aged between 16 years and 31 years belonging to different regions of India were recruited. Dietary diversity score (DDS; food groups/day) and food variety score (FVS; number of food items/day) were considered to assess the DD. The United Nations Food and Agricultural Organization food frequency questionnaire was used as a tool. Serum total cholesterol (TC), triglycerides (TG), LDL, VLDL and HDL were measured.

The DDS and FVS showed that athletes were consuming approximately 7 of 9 food groups (Mean ± SD: 6.5 ± 1.3) and 27 varieties of foods (Mean ± SD:27.0 ± 8.6) from 9 food groups per day. This study could not find significant differences for DDS and FVS among athletes belonging to different regions. FVSs of organ meat, eggs and spices and condiments were significantly positively associated with TG (p < 0.036, p < 0.020 and p < 0.001) and VLDL (p < 0.054, p < 0.021 and p < 0.001). LDL was inversely significantly associated with FVS of cereals, white root and tubers (p < 0.032).

DDS and FVS were not associated with lipid indices among Kho-Kho players. However, individual FVS of organ meat, eggs and spices and condiments may increase TG and VLDL. Optimum consumption of cereals and root tubers may help to maintain LDL levels among Kho-Kho players.

It was found that daily consumption of organ meat and eggs may increase TG and VLDL, and optimum consumption of cereals and white roots and tubers may help to maintain LDL. High energy and fat foods may act as mediators along with spices and condiments in increasing TG and VLDL.

Presents two models. Model I deals with some characteristics of a single unit system with a sensing device and two types of repairmen. The unit is attached to a sensing device which completely monitors the operating or non‐operating status of the unit. The regular repairman is always available with the system and inspects the operation of the sensing device. If the device is not working, then an expert repairman is called to the system and the operational status of the unit is now monitored by the expert repairman. It is assumed that the failure of the unit, repair of the regular, expert and the status of the sensing device are stochastically independent random variables each having an arbitrary distribution. Several important results have been derived including profit with some applications. In model II, a two‐unit cold standby system with pre‐inspection is considered. In this model, first the regular repairman inspects every unit that fails to ascertain whether he is able to repair it or not. If he can repair it, he proceeds; otherwise an expert repairman is called. An analytical approach to find the optimum interchanging time of units by giving rest to the operative unit is obtained.

The purpose of this paper is to examine the five-factor structure of patients’ satisfaction constructs toward private healthcare service providers.

This research is a cross-sectional study. A questionnaire-based survey was conducted with previous and current Bangladeshi patients. Exploratory factor analysis was employed to extract the underlying constructs.

Five underlying dimensions that play a significant role in structuring the satisfaction perceived by Bangladeshi private healthcare patients are identified in this study.

The main contribution of this study is identifying the dimensions of satisfaction perceived by Bangladeshi patients regarding private healthcare service providers.

Healthcare managers adopt the five identified underlying construct items in their business practices to improve their respective healthcare efficiency while ensuring overall customer satisfaction.