Lean Green Manufacturing Research Articles

The mediatory role of the environmental performance function within the lean-green manufacturing sustainability complex

PurposeThe objective of the study is to explore the mediatory role of the environmental performance of organisations on their economic and social performances. It demonstrates that implementing environmental management techniques should not only be done to comply with environmental regulations, but also as a means of improving social and economic performance.Design/methodology/approachThe data were gathered from the manufacturing industry of Zimbabwe, and 302 useable responses were received. Data analysis was performed through structural equation modelling (SEM) using SMART PLS 3.FindingsImprovement in environmental performance led to improvements in both social and economic performances. Also, environmental performance contributes the greatest total effect; hence, it deserves attention, not only for compliance but also for economic reasons.Originality/valueOur goal is to quantify the extent to which environmental performance might improve the social and, more importantly, the economic performance of organisations. The study also explores the relative importance and performance of lean manufacturing (LM), green manufacturing (GM), social performance and environmental performance for purposes of prioritisation of organisational improvement initiatives.

WASTE MANAGEMENT USING LEAN-GREEN APPROACH: A CASE STUDY IN A FURNITURE COMPANY

Introduction: Wooden furniture is one of Indonesia's superior products, with a low-efficiency level. However, the wooden furniture industry is often associated with intense environmental degradation and high levels of waste. In anticipating waste, a green manufacturing model proposed is Lean-Green manufacturing. This current study aims to explore the implementation of the Lean-Green model in a furniture company's waste processing system and assess the effectiveness of Lean-Green implementation. Methods: The research methodology was qualitative with the Lean-Green scoring method implemented in the supply chain of Company S. Data were collected through interviews and field observations. Results: Company S had a low score, meaning that the interaction between the Lean and Green approaches in the waste processing of the supply chain was not optimal. The Lean-Green implementation in the wooden furniture industry was effective in evaluating waste processing in the supply chain. The research findings urge the initiatives to improve the understanding and implementation of the Lean-Green concept. Conclusion and suggestion: The evaluation of the Lean-Green implementation helps the company’s manager improve the supply chain with sustainable measures.

Reinforcement Learning-Based Optimization for Sustainable and Lean Production within the Context of Industry 4.0

The manufacturing industry often faces challenges related to customer satisfaction, system degradation, product sustainability, inventory, and operation management. If not addressed, these challenges can be substantially harmful and costly for the sustainability of manufacturing plants. Paradigms, e.g., Industry 4.0 and smart manufacturing, provide effective and innovative solutions, aiming at managing manufacturing operations, and controlling the quality of completed goods offered to the customers. Aiming at that end, this paper endeavors to mitigate the described challenges in a multi-stage degrading manufacturing/remanufacturing system through the implementation of an intelligent machine learning-based decision-making mechanism. To carry out decision-making, reinforcement learning is coupled with lean green manufacturing. The scope of this implementation is the creation of a smart lean and sustainable production environment that has a minimal environmental impact. Considering the latter, this effort is made to reduce material consumption and extend the lifecycle of manufactured products using pull production, predictive maintenance, and circular economy strategies. To validate this, a well-defined experimental analysis meticulously investigates the behavior and performance of the proposed mechanism. Results obtained by this analysis support the presented reinforcement learning/ad hoc control mechanism’s capability and competence achieving both high system sustainability and enhanced material reuse.

Lean, green, and smart manufacturing: An ingenious framework for enhancing the sustainability of operations management on the shop floor in industry 4.0

In the present competitive landscape industry, individuals have emphasized fulfilling the consumer needs in available resources and limited constraints. However, the industry individuals face several problems in achieving operational efficiency. These problems include ergonomics issues, environmental waste, work processes waste, inobservance on the shop floor, and workers’ apathy. The operations management teams use various approaches to improve operational excellence on the shop floor, including lean manufacturing, smart manufacturing, green manufacturing, and artificial neural network. These approaches are used to enhance productivity by eliminating problems in the operations management on the shop floor. The present research aims to develop a framework for improvement in operational excellence and sustainability in operations management on the shop floor in an industry 4.0 environment using lean, green, and smart manufacturing concepts. In the study, a strategic ergonomics assessment and environmental assessment have been used to assess working and operational performance on the shop floor. The adaptability of the developed framework has been investigated by implementing it in mining machinery manufacturing industry. The framework has been developed with insights gained from previous research, industry individuals, and brainstorming analysis on problems faced in operations management on the shop floor in industry 4.0 working environment. The novelty of the present study lies in the fact that no model has been developed for achieving operational excellence on the shop floor in industry 4.0 using the smart, lean green manufacturing concept. The developed framework significantly improved productivity by 85%, improved machinery utilization by 21%, reduced production time by 65%, reduced manufacturing defects by 96%, and production cost by 75%. The present research work strongly believe that the developed model would benefit industry individuals in enhancing sustainability in operational excellence on the shop floor in industry 4.0 environment by establishing a more competent and cleaner working environment with available resources.

Identification of Key Brittleness Factors for the Lean–Green Manufacturing System in a Manufacturing Company in the Context of Industry 4.0, Based on the DEMATEL-ISM-MICMAC Method

In the context of Industry 4.0, the lean–green manufacturing system has brought many advantages and challenges to industrial participants. Security is one of the main challenges encountered in the new industrial environment, because smart factory applications can easily expose the vulnerability of manufacturing and threaten the operational security of the whole system. It is difficult to address the problem of the brittleness factor in manufacturing systems. Therefore, building on vulnerability theory, this study proposes a vulnerability index system for lean–green manufacturing systems in a manufacturing company in the context of Industry 4.0. The index has four dimensions: human factors, equipment factors, environmental factors, and other factors. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach was used to calculate the degree of influence, the degree of being influenced, and the centrality and causes of the factors. The causal relationships and key influences between the factors were identified. Then, the dependence and hierarchy of each of the key influencing factors were analyzed using the Matrix-Based Cross-Impact Multiplication Applied to Classification (MICMAC) and Interpretative Structural Model (ISM) methods, and a hierarchical structural model of the factors was constructed. Finally, an intelligent manufacturing system that produces a micro-acoustic material and device was used as an example to verify the accuracy of the proposed method. The results show that the method not only identifies the key brittleness factors in a lean–green manufacturing system but can also provide a guarantee for the safe operation of a manufacturing system. This study provides theoretical guidance for the effective management of intelligent manufacturing systems; moreover, it lays a foundation and provides a new methodology for assessing the vulnerability of manufacturing systems.

Research on Driving Factors of Collaborative Integration Implementation of Lean-Green Manufacturing System with Industry 4.0 Based on Fuzzy AHP-DEMATEL-ISM: From the Perspective of Enterprise Stakeholders

The existing research and practices have shown that the coordinated implementation of lean-green manufacturing can have a positive impact on the economic and environmental benefits, which is an effective means to ensure the environmental protection of the production process of manufacturing without damaging their profitability. Within the field of lean-green research, there is still a lack of research to analyze the driving factors for the collaborative implementation of integrated lean and green integration. Although, some scholars and researchers have studied lean and green integration paradigms, their research has mostly focused on lean-green integration practices and their impact on environmental performance and their respective operations. In the context of Industry 4.0, this article investigates the driving forces behind the collaborative integration implementation of a lean-green manufacturing system from the viewpoint of stakeholders. Specifically addressing the issues of correlation and ambiguity in the identification of driving factors, this manuscript proposes an Interpretation Structure Model (ISM) of fuzzy comprehensive Analytic Hierarchy Process (AHP), based on Decision-Making Trial and Evaluation Laboratory (DEMATEL), to determine the importance of the driving factors. Combined with the complex network theory, the evaluation index system is divided into four levels from eight factor categories, including endogenous lean-green driving factors and exogenous driving factors. The fuzzy AHP-DEMATEL-ISM is used to analyze the relationship between indicators and the structure of the indicator system. The complex network which is composed of the indicator system is divided into different levels. The importance of indicators is analyzed from the perspective of the global network, and key factors affecting the driving of lean-green system is analyzed. The integration of the lean-green manufacturing system and organizational synergy are promoted to jointly lead the enterprise toward sustainable development by paying particular attention to the primary impact indicators and aggressively cultivating the key impact indicators.

Decision-Making Model of Mechanical Components in a Lean–Green Manufacturing System Based on Carbon Benefit and Its Application

The key to achieving low-carbon manufacturing is to effectively reduce the carbon emissions of production systems and improve carbon benefits. The use of lean and green tools aids in measuring the added value of products, and increases the efficiency and sustainability of production systems. To address this problem and verify that the synergetic relationship between lean and green innovation increases the efficiency and sustainability in production systems, a new low-carbon manufacturing evaluation indicator—carbon benefit—in lean manufacturing systems was discussed. A low-carbon decision-making model of multiple processes aiming at carbon benefit maximization, as well as the dynamic characteristics of carbon benefit and sustainable process improvements in a lean production system, was established. A case study of a certain satellite dish parts manufacturing line was introduced to analyze and verify the feasibility of the proposed model. After improvement, the processing time of unit parts was reduced from 63 s to 54 s. The workstations were optimized again according to the lean–green manufacturing concept, and the number was reduced by 37.5%. The process was recombined and reduced from 8 to 5 to achieve continuous-flow processing. This reduced the distance by 77 m, and at the same time, the number of operating personnel was reduced, and the after-improvement carbon efficiency increased from 12.98 s/kg CO2e to 36.33 s/kg CO2e in comparison with that before the improvement. The carbon benefit after improvement was 193.92% higher than that before the improvement.

Lean-green performance management in Indian SMEs: a novel perspective using the best-worst method approach

PurposeIn a globalized environment, small and medium enterprises (SMEs) are facing formidable challenges. Not only do they have to keep up their profitability, but there is also a pressure from various stakeholders to add to their environmental and quality performance .The solution obviously lies in continuously adopting and improving upon lean-green practices in their operations. This work aims at identifying, classifying and building up a duly tested robust ranked-order model of such “enablers”, related to lean-green practices, that puts them (the enablers) in an order of being the most significant to being the least significant further to be accorded the same or similar weight in strategy formulation and implementation stage by Indian SMEs for enhancing their overall organizational performance.Design/methodology/approachThe study identifies 20 enablers (12 lean and 08 green manufacturing enablers) through extensive literature review and experts' opinion survey and classifies them into three main categories. The ranking and significance of each of the main and subcategory enablers is evaluated according to its weight which is determined by the best-worst method (BWM) approach, one of the novel multi-criteria decision-making (MCDM) methods. Further, the results have been drawn after running accuracy check of the rankings (based upon optimal weights) and testing the robustness of the ranked-order model through sensitivity analysis.FindingsThe results of this study reveal that out of the three main category enablers, “operational performance enablers (E1)” and “quality performance enablers (E3)” are the most and the least significant enablers, while in the group of 20 subcategory enablers, “Kaizen (E17)” and “environment emission control (E28)” are the most and the least significant subcategory enablers, respectively.Practical implicationsThe prioritization model or ranked-order model of the lean-green manufacturing enablers proposed through this study may serve as a standard model to managers to help them decide and allocate their efforts and resources accordingly in managing their operations. This will also help them adopt high-ranking lean-green manufacturing enablers in their firms and benchmark and standardize their existing practices accordingly, leading to greater competitive advantage.Originality/valueThe study identifies various green-lean manufacturing enablers in SMEs, classifies them into three main categories and ranks them using BWM approach. The findings of this study should be extremely relevant to managers, manufacturing engineers and practitioners in Indian SMEs from the perspective of developing deeper appreciation of these enablers as per their relative ranked importance to further formulating an effective and efficient strategy for their implementation resulting in optimal results.

Lean-Green Manufacturing Practices and Their Link with Sustainability: A Critical Review

The current rapidly changing and highly competitive market has put companies under a great pressure towards adopting sustainable practices, in terms of keeping a healthy balance among economic, environmental and social performances. In this context, the lean-green manufacturing approach, which combines lean practices focused on customers’ demand, and green practices focused on reducing the business’ environmental impact, has gained popularity. Nevertheless, the lean-green manufacturing is still a relatively new practice, lacking a clear and structured research definition, and of significant evidence of successful cases in the practice. In this paper, a literature review is conducted to identify the actual possibility of combining lean and green practices, the current trends for implementing such combination and the potential sustainability improvements such implementation can lead. It is the authors’ intention that the findings analysed in this paper can contribute to the state-of-the-art of lean-green manufacturing and provide practitioners with a useful tool towards developing effective strategies for its deployment.

Modelling and analysis of barriers affecting the implementation of lean green agile manufacturing system (LGAMS)

Purpose Many types of research have already investigated the lean, green or agile manufacturing systems in a discrete manner or as combinations of two of them. In today’s competitive scenario, if industry wants to perpetuate its name in the market, then it has to supervene proper thinking and smart approach. Therefore, the combination of lean, green and agile manufacturing systems can provide better and beneficial results. The purpose of this paper is to discern the barriers to the combined lean green agile manufacturing system (LGAMS), understand their interdependence and develop a framework to enhance LGAMS by using total interpretive structural modeling (TISM) and MICMAC (Matriced’ Impacts Croise’s Multiplication Appliquée a UN Classement) Analysis. Design/methodology/approach This paper uses TISM methodology and MICMAC analysis to deduce the interrelationships between the barriers and rank them accordingly. A total of 13 barriers have been identified through extensive literature review and discussion with experts. Findings An integrated LGAMS has been presented that balances the lean, green and agile paradigms and can help supply chains become more efficient, streamlined and sustainable. Barriers are identified while referring to all three strategies to showcase the clear relevance. TISM models the barriers in different levels showcasing direct and important transitive relations. Further, MICMAC analysis distributes the barriers in four clusters in accordance with their driving and dependence power. Research limitations/implications The inferences have been drawn from a model developed on the basis of inputs from a small fraction of the industry and academia and may show variations when considering the whole industry. Practical implications The outcome of this research can contribute to bringing the change to the manufacturing systems used in most developing nations. Also, top managers considering adoption of LGAMS can be cautious of the most influential barriers. Originality/value A TISM-based model of the barriers to an integrated LGAMS has been proposed with evaluation of the influence of the barriers.

Sustainable Lot Size in a Multistage Lean-Green Manufacturing Process under Uncertainty

Optimal lot sizing is the primary tool applied by lean practitioners to reduce inconsistency in the manufacturing system to cut down inventories, which are often considered as a type of waste in the lean culture. Managers attempt to consider environmental impacts of the manufacturing system and find ways to reduce these effects while making efforts to achieve environmental protection. From a sustainability standpoint, carbon emissions are the major source of environmental contamination and degradation. In this context, this research provides an economic production quantity model with uncertain demand and process information in a multistage manufacturing process. This imperfect manufacturing process produces defective products at an uncertain rate, and is reworked to convert them into perfect quality products and reduce wastages. To control this uncertainty in the manufacturing process, the decomposition principle and the signed distance method of fuzzy theory are applied. The manufacturing process is analyzed with regard to environmental concerns, and a sustainable lot size is obtained through an interactive Weighted Fuzzy Goal Programming (WFGP) approach for the simultaneous achievement of economic and environmental sustainability. An experimental study is performed to verify the practical implication of the model, and results are evaluated through a sensitivity analysis. Important managerial insights and graphical illustrations are provided to elaborate the model.

Lean-green manufacturing: the enabling role of information technology resource

PurposeThe purpose of this paper is to contribute to the existing knowledge about the relationships between information technology (IT), lean manufacturing (LM), organizational environmental issues and business performance.Design/methodology/approachA questionnaire-based survey was conducted to collect data from 122 elite manufacturers, and the hypothesized relationships were tested using partial least squares structural equation modeling.FindingsIT competence in LM acts as a lower-order organizational capability, and its business value should be recognized through the intermediate roles of LM effectiveness and environmental management capability. Findings recommend that the net benefits of LM are mainly materialized through waste and pollution reduction and simplified implementation of proactive environmental practices.Research limitations/implicationsAmong other limitations, relying on a rather small sample size and cross-sectional data of this research, and lack of generalizability of findings, tends to have certain limitations. An interesting direction for future research would be to extend this research by assessing interaction of other types of IT resources with LM and organizational environmental issues.Practical implicationsBoth LM and proactive environmental management are information-intensive. Investment in both technological and human aspects of IT resource aimed at increasing the effectiveness of LM activities and proactive environmental practices is imperative for contemporary manufacturers.Originality/valueThis study introduces the IT capability of IT competence in LM and two organizational capabilities of LM effectiveness and environmental management capability. By doing so, the study highlights the significant role of organizational environmental issues in devising firms’ IT and advanced manufacturing technology investment strategies in LM context.

Assessment of drivers to implement integrated lean green manufacturing system in Indian SMEs through IF-TOPSIS approach

Due to globalisation and strict environmental regulation by government agencies, small and medium enterprises (SMEs) are under hideous pressure to improve their operational, financial as well as environmental performance. Taking this fact into consideration, an integrated lean green manufacturing system (LGMS) has been proposed as a solution to improve the overall performance of SMEs. It is important to identify the essential driving factors that influence in adoption of LGMS in SMEs. Therefore, present study examines the rank of drivers by utilising an intuitionistic fuzzy technique for order of preference by similarity to ideal solution (IF-TOPSIS) approach. Finding of the study shows that 'competitiveness', 'legislative and regulatory compliances', 'reduce manufacturing cost', 'market trends' and 'improve working environment' are the top most essential drivers among 23 drivers. This study provides important insights to policy makers in government and industries for proper and effective implementation of LGMS in manufacturing SMEs.

Assessment of drivers to implement integrated lean green manufacturing system in Indian SMEs through IF-TOPSIS approach

Due to globalisation and strict environmental regulation by government agencies, small and medium enterprises (SMEs) are under hideous pressure to improve their operational, financial as well as environmental performance. Taking this fact into consideration, an integrated lean green manufacturing system (LGMS) has been proposed as a solution to improve the overall performance of SMEs. It is important to identify the essential driving factors that influence in adoption of LGMS in SMEs. Therefore, present study examines the rank of drivers by utilising an intuitionistic fuzzy technique for order of preference by similarity to ideal solution (IF-TOPSIS) approach. Finding of the study shows that 'competitiveness', 'legislative and regulatory compliances', 'reduce manufacturing cost', 'market trends' and 'improve working environment' are the top most essential drivers among 23 drivers. This study provides important insights to policy makers in government and industries for proper and effective implementation of LGMS in manufacturing SMEs.

Review of lean-green manufacturing practices in SMEs for sustainable framework

Review of lean-green manufacturing practices in SMEs for sustainable framework

Review of lean-green manufacturing practices in SMEs for sustainable framework

Lean manufacturing aims at maximising the resource utilisation through minimisation of waste and respond to the fluctuating and competitive business environment, whereas GM concept addresses a various manufacturing matters, say recycling, waste management, environmental protection and so on. Lean manufacturing and its integration with green manufacturing practices benefits both industries and society. This review paper identifies prime elements of lean and green manufacturing and throws light on current scenario in small and medium enterprises. The paper begins with brief introduction about lean and green manufacturing concept. In Section 2, literature review presents the elements of lean and green manufacturing practices. Section 3 comprises two parts: 1) highlights principle of sustainability-oriented framework; 2) significant features of MDCM models. Section 4 focuses on current scenario of Indian SMEs in context of sustainable lean-green manufacturing practices and its comparison with SMEs in other countries. Section 5 presents conclusion of and future scope of the paper.

Ranking of drivers for integrated lean-green manufacturing for Indian manufacturing SMEs

The growth of manufacturing small and medium size enterprises (SMEs) is vital as they have a significant amount of share in total manufacturing output. In this era of globalization, SMEs are compelled to ensure sustainable profitability through cost savings, while being environmentally conscious at the same time. It has been reported in the prior investigations that lean and green practices can achieve excellent results if they are implemented simultaneously. Hence, SMEs need to adopt integrated lean and green manufacturing as this can address economic and environmental concerns together. The drivers for implementation of integrated lean and green manufacturing in SMEs have not been thoroughly explored in the past studies. This sets the motivation for the present research. Thus, in this paper drivers for integrated lean and green manufacturing are identified from the combined support of existing literature and experts' opinions in the relevant field. The drivers are ranked using multi-criteria decision making methods such as technique for order of preference by similarity to ideal solution (TOPSIS) and simple additive weighting (SAW) in fuzzy environment using environmental, social and economic perspectives, however, consolidated ranking is obtained by borda method. The results reveal that top management commitment, technology up-gradation, current legislation, green brand image and future legislation are five most important drivers for the implementation of integrated lean and green manufacturing in Indian manufacturing SMEs. The research counters the uncertainties in importance of criteria weights using sensitivity analysis which determines the influence of criteria weights on the prioritization. Finally, the paper concludes with some managerial implications which will help the policy makers in government and industry to focus on few important drivers to facilitate the integrated lean and green manufacturing implementation in SMEs with limited resources.

Two-way assessment of barriers to Lean–Green Manufacturing System: insights from India

Manufacturing systems across the globe are under pressure to improve the competitiveness and environmental performance. However, neither of lean manufacturing (LM) nor green manufacturing (GM) concepts distinctly provides a comprehensive workable solution to the challenges of the competitiveness and environmental performance. There is a need to make a bridge between LM and GM. So, a hybrid system of Lean–Green Manufacturing System (LGMS) is proposed which can handle the challenges of the manufacturing systems completely. However, adoption of such manufacturing systems in the existing industrial framework poses many issues which hinder the implementation of such system, although it leads to holistic improvement of manufacturing system performance. These issues are termed as ‘barriers’. In this research, a comprehensive and thorough study of the LM, GM and LGMS has been done to identify the barriers. These barriers are suitably analyzed to bring out some insights which can help them mitigate. This will enable the voluntary transition towards LGMS more realistically. Barriers will be analyzed and validated with the help of two-way assessment approach. This research will contribute to the scientific literature by providing a validated list of barriers and few high impact barriers which will provide the ground for policy makers in industry and government to frame policies which are more implementable.