• Energy Research

Green Lean Six Sigma has emerged in the Industry 4.0 era as a business strategy contributing to the circular economy by adopting the 3R concept, i.e., reduce, reuse, and recycle. Despite its broadly acknowledged capabilities in the manufacturing industry, practitioners continue to be cautious about its implementation, owing to insufficient knowledge and culture. Hence, there is a need to systematize the existing knowledge regarding this green initiative and also to recognize the key factors enabling its implementation. In the Malaysian manufacturing context, the enabling factors have yet to be identified and evaluated. This current study is the first of its kind to identify and examine these factors and to create a structural model to conceptualize and operationalize this business strategy. The implemented methodological approach includes two steps. Firstly, it performs a systematic review of leading studies on the topic, which are rather scarce in the current context. The second step entails a principal component factor analysis using varimax rotation to finalize the findings. The theoretical and empirical results revealed a structural model with five interconnected key factors, including twenty-seven enablers, that can be used to narrow the existing knowledge gap in the understudied context.

Notwithstanding the research on refining lean tools for the sake of sustainable development is slowly progressing, sustainability-oriented application of value stream mapping has received undivided attention from practitioners and researchers. Going through the literature highlights that there is a lack of research in integrating and systematising the available knowledge on this lean tool, which is regarded as a visual process-based method to make sustainable progress over the time-based and green concepts of wastes to also assess and improve the societal sustainability performance of organisations. Hence, this paper has been aimed at presenting the findings of a systematic literature review on value stream mapping from the triple bottom line point of view. It classifies and codes the main studies in the context as well as provides a research agenda with nine recommendations that may advance this under-studied field. To narrow the gap in the current literature, this article also proposes a sustainability indicator set that would considerably contribute to guiding and strengthening the state-of-the-art research on successful implementation of the application. Besides, the findings indicate that more investigations are needed on employing survey and conceptual methodologies, applying comparative and cross-industry perspectives, developing sustainability indicator sets particularly societal metrics, and considering the stakeholders’ benefits from adopting sustainability-oriented value stream mapping. The research on the convergence of this sustainability-oriented application and new paradigms such as IR 4.0 and/or Circular Economy should be also strengthened.

This paper investigates the barriers that hinder the implementation of lean manufacturing in wood and furniture industries as the adoption of this philosophy in such industries is not promising especially in emerging economies. To this end, a comprehensive review of the literature was performed to identify the barriers and develop a conceptual model. Next, structural equation modeling is employed to examine the model using the collected data from 131 wood and furniture companies. The findings revealed a synergetic effect between three key factors—culture and human attitude, knowledge, and resources—which play a crucial role in implementing lean. The analyses indicated the reasons of companies refused or not ready to implement lean on knowledge and culture and human attitudinal issues, particularly in companies that have limited resources. It is believed that resource issues are an obstacle to lean implementation, but not as important as knowledge and culture and human attitudinal issues. Sufficient knowledge is needed to deploy lean practices as well as changes in culture and human attitude. Investigating the relationships between these three key barriers is a contribution that this study intends to become a forward step for promoting lean manufacturing among under-studied industries. This paper also proposes that through adopting the activities for lean implementation, small and medium enterprises can experience and quantify the positive impacts of lean practices. Government agencies, universities, and professional bodies can support such enterprises in this transition through targeted interventions that address the barriers presented.

The scheduling of open-pit mine production is a large-scale, mixed-integer linear programming problem that is computationally expensive. The purpose of this study is to create a computationally efficient algorithm for solving open-pit production scheduling problems with uncertain geological parameters. To demonstrate the effectiveness of the proposed research, a case study of an Indian iron ore mine is presented. Multiple realizations of the resource models were developed and integrated within the stochastic production scheduling framework to capture uncertainty and incorporate it into the mine plan. In this case study, two hybrid methods were developed to evaluate their performance. Model 1 is a combined branch and cut with the longest path, whereas Model 2 is a sequential parametric maximum flow and branch and cut. The results show that both methods produce similar materials, ore, metal, and risk profiles; however, Model 2 generates slightly more (4 percent) discounted cash flow from this study mine than Model 1. The results also show that Model 2’s computational time is 46.64 percent less than that of Model 1.

The extended application of value stream mapping has more recently been clarified to fulfill the triple bottom line requirements in the manufacturing systems. Thus, there is a glaring lack of literature on this sustainable-oriented lean tool, among these minute studies, the research attention has mainly been given to the environmental issues, largely neglecting the societal aspects. To complement and support this narrow body of knowledge, this article is aimed at developing a social value stream mapping methodology, which we refer to as Socio-VSM, for visualizing and assessing the societal sustainability performance in the context of manufacturing. In doing so, it identified and incorporated crucial societal metrics into the proposed approach, which was made based on the conventional value stream mapping method. For validation purposes, a case study entailing a hard disc drive substrate manufacturing industry was applied for the documentation and reporting of results derived from the implementation of the proposed methodology and for testing and making conclusions about its effectiveness. It makes the valuable theoretical and practical contributions to narrow the gap on this long-neglected scope.

The manufacturing industry has undergone numerous revolutions over the years, with a unanimous acceptance of the greater benefits of being sustainable. The present industrial wave—Industry 4.0—by using its enabling technologies and principles holds great potential to develop sustainable manufacturing paradigms which require balancing out the three fundamental elements —products, processes, and systems. Yet, numerous stakeholders, including industrial policy and decision makers, remain oblivious of such potential and requirements. Thus, this bibliometric study is aimed at presenting an overview of the broad field of research on the convergence of sustainable manufacturing and Industry 4.0 under the umbrella of “Sustainable Manufacturing 4.0”, which has yet to be developed. It includes the dissemination of original findings on pathways and practices of Industry 4.0 applied to the development of sustainable manufacturing, contributing a bibliometric structure of the literature on the aforementioned convergence to reveal how Industry 4.0 could be used to shift the manufacturing sector to a more sustainable-based state. An initial research agenda for this emerging area has accordingly been presented, which may pave the way for having a futuristic view on Sustainable Manufacturing 5.0 in the next industrial wave, i.e., Industry 5.0.

Big data analytics, described as the fourth paradigm of science breaking through Industry 4.0 technological development, continues to expand globally as organizations strive to attain the utmost value and sustainable competitive edge. Yet, concerning its contribution to developing sustainable products, there is a need for innovative research due to limited knowledge and uncertainty. This research is hence aimed at addressing (a) how research on big data analytics for sustainable products has evolved in recent years, and (b) how and in what terms it can contribute to developing sustainable products. To do so, this study includes a bibliometric review performed to shed light on the phenomenon gaining prominence. Next, the fuzzy technique for order of preference by similarity to ideal solution, along with a survey, is used to analyze the matter in terms of the respective indicator set. The review’s findings revealed that there has been growing global research interest in the topic in the literature since its inception, and by advancing knowledge in the area, progress toward sustainable development goals 7, 8, 9, 12, and 17 can be made. The fuzzy-based analytical findings demonstrated that ‘product end-of-life management efficiency’ has the highest contributory coefficient of 0.787, followed by ‘product quality and durability’ and ‘functional performance’, with coefficients of 0.579 and 0.523, respectively. Such research, which is crucial for sustainable development, offers valuable insights to stakeholders seeking a deeper understanding of big data analytics and its contribution to developing sustainable products.

Although various initiatives have been undertaken by the universities worldwide to ensure that their campus operates sustainably, there are emergent barriers that pose serious challenges to the practitioners and subsequently hinder the successful implementation. The research for this paper was built upon the discussion concerning ‘campus operations’, which is one of the dominant sustainability elements in the university systems. It analyzes the barriers for green campus operations implementation through a methodological approach, which was implemented in two tiers. For identification of the barriers, a comprehensive review of the literature was performed and consulted with academic experts who have been involved in greening campus operations in the university. Next, interpretive structural modeling was used to analyze and develop a model of interactions, mutual influence, and relationship among barriers. The results revealed an eighteen-barrier interpretive structural model with eight levels. The analysis indicated that ‘lack of awareness’, ‘lack of knowledge’, ‘resistance to change’, and ‘inefficient communication’ are the dominant barriers with high driving and low dependence powers. The research findings highlighted the importance of this structural model for universities to facilitate the implementation of campus operations by removing the dominant barriers.