Environmentally Conscious Manufacturing Research Articles

Impact of Digital Transformation and Green Manufacturing Practices on Firm Performance with Mediating Role of Green Product Innovation: An Empirical Investigation with PLS-SEM Modeling

Purpose: The objective of this research is to determine the impact of green manufacturing practices and digital transformation on firm performance, with a particular focus on the mediating role of green product innovation. Design/Methodology/Approach: The study conducted a survey of 212 employees from various businesses using a questionnaire-based method. The data is analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) to examine the connections between digital transformation, green manufacturing practices, and company performance. The study also investigated the intermediary function of green product innovation in these connections and offered valuable insights into how sustainable practices might enhance corporate performance. Findings: This research indicates that green product innovation plays a vital role in connecting these practices to improved company success. The results suggests that organisations that have used digital transformation technologies are more inclined to foster innovation in environmental friendly goods, so enhancing sustainability and subsequently improving performance. Implications/Originality/Value: The present research contributes to the existing understanding of the impact of digital transformation and green manufacturing techniques on enhancing company performance with a specific emphasis on sustainability. The importance of digital transformation and environmentally-conscious manufacturing methods in improving the sustainability of enterprises is emphasised.

Barriers to the Sustainable Implementation of Environmentally Conscious Manufacturing: A Contextual-Based Interpretive Structural Model

The traditional production system is mainly concerned with economic growth. However, with growing pollution and the rapid depletion of natural resources, there is an urgent need to adopt environmentally conscious manufacturing (ECM) to prioritize the environment alongside society and business. Therefore, it is crucial to identify the barriers that prevent the sustainable implementation of ECM to overcome them better. This research uses interpretive structural modeling to identify and comprehend the contextual interrelationships between barriers to ECM. The identified barriers are categorized and modeled based on their interdependence and driving powers. The findings show that management’s lack of understanding of ECM is an essential barrier that leads to a communication gap. Both lead to barriers, such as a less qualified workforce, high taxation, poor policy framing and implementation, poor financial support, and lack of technological upgrades. Thereby, this leads to the poor adoption of remanufacturing, higher costs of sustainable products, and in turn, overconsumption of natural resources. Overcoming these barriers will improve the poor acceptance of ECM, the inadequate legislative framework, and the lack of its implementation. The resulting model provides a deeper understanding of the barriers and enables the better design of coping strategies toward a more sustainable implementation of ECM to its fullest potential.

Barriers to environmentally-conscious manufacturing innovation

Barriers to environmentally-conscious manufacturing innovation

Green and Environment Conscious Manufacturing and Management Techniques

Contemporary industry is beginning to realize the negative impact that they have on the environment in terms of greenhouse gas emissions, destruction of natural habitats, hazardous waste emissions, etc. This new found consciousness has prompted a second look on part of the manufactures at how modern manufacturing practices can be modified so as to be more environmentally friendly. Environmental impact of manufacturing can be minimized in various ways. In this context, management is often called upon to provide active leadership in managing their facilities so as to minimize their environmental impact. Some examples of such activities include green supply chains and design for disassembly. Such activities help to create a closed loop product lifecycle that is required to reduce the amount of raw material used and the amount of waste created by production. Similarly using design for manufacturability principles aid in the minimization of raw material used and waste generated as well. Also, facilities are starting to move away from reactive approaches to environmental issues. They are now using proactive approaches and value seeking approaches where the environmental issues are dealt with before they are created. This paper presents an overview of environment conscious manufacturing practices that seek to minimize the negative environmental impact of manufacturing. Being a literature review, this paper primarily deals with state of the art in current practice pertaining to green manufacturing.

Modeling Enablers of Environmentally Conscious Manufacturing Strategy: An Integrated Method

Environmentally conscious manufacturing (ECM) has become an ever-more important strategy for most manufacturing companies to enhance the sustainability of their business. The successful adoption of environmentally conscious manufacturing strategy (ECMS) requires identifying a variety of crucial enablers and understanding their relationships of ECM strategy. However, most previous studies do not consider the interrelationships between enablers, and lack the mechanism of manipulating the vagueness in the decision-making process, which leads to the inaccurate identification of enablers. Thus, to solve these problems, an integrated method based on DEMATEL (Decision-Making Trial and Evaluation Laboratory) and rough set theory is developed in this paper. The method integrates the strength of DEMATEL in dealing with interactions between factors and the ability of rough set theory to manipulate uncertainty. Finally, the method is applied to analyze the enablers of ECMS in an equipment manufacturing company to reveal the feasibility and effectiveness of the proposed approach. The “corporate social responsibility motivation” is identified as the most critical enabler for the case company in implementing ECMS, and it is influenced by other ECMS enablers including “environmental protection equipment” and “environmental design technology”.

In situ investigations on forces and power consumption during flow forming process

Flow forming is used to manufacture high precision seamless components for aerospace and defence industries. The typical applications are rocket missile case, cartridge case, rocket nose cones etc. In flow forming, the deformable workpiece is placed over rigid mandrel and rigid roller(s) deform it under contact zone. There are two approaches used for production i.e. forward and reverse. In forward approach, the roller feed and deformation direction are same. Whereas in reverse approach, the roller feed and deformation directions are opposite. The power consumption during the process is an important aspect to foster energy efficient production environment. Also, forces encountered on the tool (Roller) are also crucial aspect in order to design tooling for different material and geometrical conditions. Based on literature review and industrial survey, it was observed that online force and power measurement are quite difficult in commercial machines. Hence, experimental and numerical studies have been carried out on force(s) and power consumption to promote environment conscious manufacturing. Design of experiment (DOE) approach was used to reduce experimental runs. Taguchi L36 design was used to conduct experiments. Three levels of three operating variables like speed, feed and reduction percentage along with two levels of two roller parameters like attack angle and nose radius were considered during the study. It was observed that speed and feed are the most important factors which are influencing the power consumption. Even, roller attack angle, nose radius and reduction percentage are mainly affecting force(s). Also, the results of experiments and simulations are found in good accordance.

MTConnect를 활용한 수치제어 프로그램의 에너지 예측 모델링

In the metal-cutting industry, energy prediction is important for environmentally-conscious manufacturing because it enables a numerical anticipation of the energy consumption from the input of the process parameters, and therefore it contributes to the increasing of the energy-efficiency of the machine-tool operations. This paper proposes an energy-prediction modeling approach for numerical-control programs based on historical machine-monitoring data that have been collected from machine-tool operations. The proposed approach can create accurate energy-prediction models that forecast the energy that is consumed by the execution of a numerical-control program. Also, it can create machine-specific energy-prediction models that accommodate the variety of shop-floor machining contexts. For this purpose, it uses MTConnect to represent the machine-monitoring data to embody an interoperable data-collection environment regarding the shop floor. This paper also presents a case study to show the feasibility and practicability of the proposed approach.

Towards fuzzy preference relationship based on decision making approach to access the performance of suppliers in environmental conscious manufacturing domain

Environmental consciousness has become a significant aspect at various levels of product design. In the recent years, by and large industries are focusing towards environment conscious products. Quantitative analysis of energy consumption and waste generation from any product is directly related to the supply chain management of the product. Hence, the selection of most suitable supplier from the pool of available suppliers is emerged as an important multi attribute (multi objective, multi criteria, multi factor) decision making (MADM) problem. This research paper addresses the supplier selection problem from the perspective of supply analysis, logistic analysis, process analysis, use analysis and, recycle analysis for calculating environmental impact of a product. Based on the associated environmental importance of a product a procedure based on fuzzy framework is used for ranking and selecting the best suitable supplier from its environmental perspective. A multi preference fuzzy relationship model is introduced to incorporate the uncertainty in the decision making by the decision maker. Finally, a solution procedure based on OWA (Ordered Weighted Averaging) aggregation operator is developed. The proposed methodology has been discussed along with an illustrative examples.

Application of ARIMA for forecasting energy consumption and GHG emission: A case study of an Indian pig iron manufacturing organization

Environmentally conscious manufacturing (ECM) has become an important strategy and proactive approach for the iron and steel sector of India to produce environment friendly and to reduce manufacturing cost. There are several environmentally conscious manufacturing indicators to evaluate ECM programs. Among those indicators, energy consumption and greenhouse (GHG) emission may be considered critical environmentally conscious manufacturing indicators (CECMI) for Indian iron and steel sector. This paper focuses on forecasting energy consumption and GHG emission for a pig iron manufacturing organization of India because the managers are interested to know the current and future trends of these indicators for better environmental policy. For forecasting purpose, autoregressive integrated moving average (ARIMA) is applied to reveal that ARIMA (1,0,0) × (0,1,1) is the best fitted model for energy consumption. Regarding GHG emission, ARIMA (0,1,4) × (0,1,1) is the best fitted model. In both cases, the forecasts resemble those of the seasonal random trend model, however they appear smoother because the seasonal pattern and the trend are efficiently averaged for energy consumption and as well as GHG emission. Selection of the correct ARIMA models for these indicators will help in accurate forecasting in order to achieve better environmental management practice.

Evaluation of environmentally conscious manufacturing programs using a three-hybrid multi-criteria decision analysis method

Environmental management, being an important component in strategies for achieving sustainable development of processes and products, has emerged as a proactive approach in majority of the manufacturing organizations. From the strategic perspective environmentally conscious manufacturing (ECM) programs lead to better environmental management practice. The objective of the current paper is to present an integrated and holistic framework to evaluate ECM programs. This framework combines three multi-criteria decision analysis (MCDA) methods to consider eight major environmentally conscious manufacturing indicators (ECMI) in order to identify the efficiency of each ECM program. First the interdependence relationship among the ECMIs is established using decision-making trail and evaluation laboratory (DEMATEL). Then a range of weightage (i.e. upper and lower bounds) is created for each ECMI using analytic network process (ANP) to include managerial preferences. Finally, this range of weightage for each indicator is applied to perform restricted multiplier data envelopment analysis (RMDEA). Results show that the technical efficiency of the inefficient ECM programs for integrated RMDEA, on average, is calculated as 53.2% whereas traditional input oriented DEA provides the same score as 72.3%. This clearly indicates that integrated RMDEA is better than the input oriented DEA because same level of output could be produced with lesser resources if the ECM programs perform on the frontier. Hence, the advantage of this methodology is that the managerial preferences are successfully implemented through this newly developed hybrid methodology that will help to reduce less resource consumption and lead to better environmental policy.

Modeling and parameter optimization for cutting energy reduction in MQL milling process

Environmentally conscious manufacturing (ECM), a key concept for modern manufacturing, emphasizes the efficient and optimal use of raw materials and natural resources and minimization of the negative effects on nature and society. This study focused on achieving ECM for milling processes. Toward this end, a model predicting the specific cutting energy was developed and optimized to determine the cutting conditions that minimize the specific cutting energy. A minimum quantity lubrication scheme was employed to minimize the amount of cutting oil used, thereby minimizing the associated process cost. Four process variables or cutting conditions (cutting speed, depth of cut, feed rate, and flow rate) were selected for the specific cutting energy model, and their appropriate ranges were determined through a preliminary experiment. The specific cutting energy model was developed based on an artificial neural network, where the Levenberg-Marquardt back propagation algorithm was implemented and the number of hidden layers was determined through comparison with controlled experimental data. The cutting conditions to minimize the specific cutting energy were determined using a global optimization process-the particle swarm optimization algorithm. In this algorithm, all computations were confined within the experimental range via constraint conditions, and the resulting optimized process variables were experimentally verified.

Process-oriented Life Cycle Assessment framework for environmentally conscious manufacturing

Environmental concern requires manufacturers to extend the domain of their control and responsibility across the product's life cycle. Much of the research has concentrated on assessment of environmental performance through the application of the Life Cycle Assessment (LCA) framework that provides a technical methodology to help identification of environmental impacts of product systems. However, the current LCA framework does not incorporate dynamic and diverse characteristics of manufacturing processes. As a result, the LCA's referential data will largely deviate from the real ones to an extent that the purpose of LCA is not meaningful. In other words, the current and fixed referential data-based method is not suitable to specify the impact categories related to manufacturing processes. From the perspective of decision making related with environmental impact during manufacturing, the current LCA method carried out in the off-line is hard to apply. As a result, performance index, such as greenability, a major performance index for environment conscious manufacturing cannot be implemented in the real practice. This paper presents the development of a framework (called process-oriented LCA) to realize environmental conscious manufacturing incorporating both greenability and productivity. To show the applicability and validity of this framework, experiments and analysis have been conducted and a prototype system has been implemented for a turning machining process.

Effect of various factors for achieving environmental performance in manufacturing industry: a review

During the industrial revolution, environmental issues were not addressed when designing and manufacturing the products. Environmental conscious manufacturing (ECM) is concerned with developing methods for manufacturing products, processes and operations, etc., to satisfy the requirements of environmental standards. Authors present an important review of the development of research; related to environmental performance and provide a review of published work in this area. However, that survey covers the research papers published from 1995 to 2013. This paper investigates the literature by classifying published references into four major categories: design for environment, life cycle analysis, green supply chain management and environmental management system and discusses the various limitations of the systems. It also focuses on environmental management system (EMS) for achieving environmental performance in manufacturing industries.

Development of a structural model of environmentally conscious manufacturing drivers

Purpose – Manufacturing firms consume energy and natural resources in highly unsustainable manner and release huge amounts of green house gases leading to many economic, environmental and social problems; from local waste disposal to climate change. Consciousness about these issues has lead to a new manufacturing paradigm of environmentally conscious manufacturing (ECM). There exist many social, legislative, policy, economic, internal, and environmental factors which can motivate and/or force industry to adopt ECM. The purpose of this paper is to identify the drivers for ECM, developing a model of these drivers using statistical analysis and testing the model using structural equation modeling (SEM) technique. Design/methodology/approach – The basic steps of methodology are ECM driver development, survey instrument development, data collection, model proposition, and model validation. The main data analysis approaches are exploratory factor analysis, confirmatory factor analysis, and SEM to develop a model of drivers and validating the same based on the data collected from the manufacturing industry. Findings – The reliable, valid, and tested model has three types of drivers – internal, policy, and economic. It has been found through hypothesis testing that internal drivers for the implementation of ECM are positively related to policy and economic drivers; and policy drivers are positively related to economy drivers. This research is expected to help government and industry in developing policies and strategies for the successful implementation of ECM. Practical implications – The novelty of this study is that it provides the relationship among the drivers which can be leveraged by the managers to focus on the root drivers for smooth and effective implementation of ECM. Originality/value – This paper provides new theoretical insight into the factors motivating the industry to implement ECM systems in the industry with special focus on manufacturing sector of emerging economies.

Special Issue on Design and Manufacturing for Environmental Sustainability

This issue focuses on design and manufacturing theories and methodologies aimed at achieving environmental sustainability. It has been two decades since environmental sustainability and related issues have been discussed as main issues in design and manufacturing. In these 20 years, theories and methodologies have been developed on environmentally conscious design, including the design of disassembly and life cycle assessment, and manufacturing techniques for saving energy and resources and low emission. In spite of these efforts, the seriousness of the environmental issues, e.g., global warming, is getting harder and harder and new issues continuously arise. It has gradually been recognized that essential problems reside within the manufacturing industry structure and the center of the manufacturing industry has shifted from developed countries such as Japan and US to developing countries with accelerating mass production and mass consumption. Based on this recognition, this special issues deals with rather novel topics emerging in the domain of design and manufacturing for environmental sustainability. The first five papers provide a global scope on the relationship between environmental sustainability and manufacturing industry, including global energy consumption patterns, manufacturing industry scenario writing, informative reviews on lean remanufacturing, urban mining, and education on resource scarcity. The second three papers focus on human recognition and behavior – emerging topics in this domain – including socially responsible investment, customer choice, and the routing of electric vehicles. The last five papers propose new methods or technologies of environmentally conscious design and sustainable manufacturing, including ecobusiness design, electric vehicle heating systems, and the sustainability evaluation of manufacturing processes. Some papers, revised and extended in response to the editor’s invitations, were originally presented at EcoDesign 2013: 8th International Symposium on Environmentally Conscious Design and Inverse Manufacturing (Jeju, Korea). The editor sincerely thanks the authors and reviewers for their devoted work in making this special issue possible. We hope that these articles will encourage further research on design and manufacturing for environmental sustainability.

Modeling drivers for successful adoption of environmentally conscious manufacturing

Purpose – This paper aims at developing an interpretive structural model of drivers for environmentally conscious manufacturing (ECM). It will demonstrate how interpretive structural modeling (ISM) supports policy makers in the government and industry in identifying and understanding interdependencies among drivers for ECM. Interdependencies among drivers will be derived and structured into a hierarchy to derive subsystems of interdependent elements with corresponding driving power and dependency. Design/methodology/approach – ISM has been used to identify hierarchy and inter-relationships among drivers for ECM adoption and to classify the drivers according to their driving and dependence power using MICMAC analysis. The drivers for ECM adoption are identified through the review of literature followed by developing a model of drivers using ISM. Findings – The main findings of the paper include the development of an ISM model of drivers for ECM adoption. The developed model divided the identified drivers into five levels of hierarchies showing their inter-relationship and depicting the driving-dependence relationship. These five levels have been classified into four categories – awareness, external, organizational and benefits. Originality/value – The developed ISM model is expected to provide a direction to the policy makers in the government and industry and the top management of the organizations to leverage their resources in a timely manner to adopt ECM successfully.

An explorative study to enable environmentally conscious manufacturing for an industrial gearbox manufacturing organization

In recent years, environmentally conscious manufacturing (ECM) has become an important aspect and proactive approach for majority of the manufacturing organizations in India. The reason is that ECM not only helps to produce environment friendly, but also helps to make money by reducing cost or achieving competitive advantage. Industrial gearbox manufacturing organizations have significant environmental impacts as industrial gearbox manufacturing involves several steps which use valuable resources and pollute the environment. Hence, this paper presents an explorative environmental study of an Indian industrial gearbox manufacturing organization. The objective of the current paper is (i) to identify the environmental problems and environmentally conscious manufacturing indicators (ECMI), (ii) to find out the root causes of these problems and (iii) to solve the root causes based on the available state-of-the-art literature. This research work not only reviews the efficient environment friendly manufacturing techniques, but also helps the organization to become eco-efficient by producing environment friendly while making money. First ECMIs selected from literature review, are validated through process mapping. Then these indicators are prioritized using analytic hierarchy process (AHP) to find out the critical environmentally conscious manufacturing indicators (CECMI). The sources of CECMIs are identified using either data envelopment analysis (DEA) or direct observation of the available database. Finally, some possible solutions are also addressed in this paper.

Fuzzy TOPSIS method for ranking barriers to environmentally conscious manufacturing implementation: government, industry and expert perspectives

A growing number of organisations have begun working towards implementation of Environmentally Conscious Manufacturing (ECM) because of increased concerns about the pollution increase, natural resources depletion and global warming. But some barriers hinder the implementation of ECM systems. In order to mitigate these barriers, the ranking of barriers is very essential as high-ranked barriers can be taken up first to address the issue more effectively within the availability of resources and capacity to improve environment. This paper aims at identifying and ranking barriers to ECM implementation. Twelve barriers have been identified and grouped as economic, internal, policy and societal barriers. A fuzzy TOPSIS multi-criteria decision model has been developed to rank these barriers from government, industry and expert perspectives by using the data inputs from various sources in India. The ranking of the barriers from different perspectives will help the decision/policy makers in government and industry to mitigate these barriers in an effective manner.

Assessment of hierarchy and inter-relationships of barriers to environmentally conscious manufacturing adoption

Purpose – The purpose of this paper is to develop hierarchy and inter-relationship among barriers to environmentally conscious manufacturing (ECM) adoption using an interpretive structural modeling (ISM) technique. The paper will demonstrate how ISM supports policy makers in the government and industry in identifying and understanding interdependencies among barriers to ECM. Interdependencies among barriers will be derived and structured into a hierarchy in order to derive subsystems of interdependent elements with corresponding driving power and dependency. Design/methodology/approach – ISM was used to identify hierarchy and inter-relationships among barriers to ECM adoption and to classify the barriers according to their driving and dependence power using MICMAC analysis. The barriers to ECM adoption are identified through the review of literature followed by developing a model of barriers using ISM based on the inputs from experts from industry and academia. Findings – The main findings of the paper in...

Development of a model of barriers to environmentally conscious manufacturing implementation

Manufacturing firms consume energy and natural resources in highly unsustainable manner and release large amounts of green house gases leading to many economic, environmental and social problems from climate change to local waste disposal. Consciousness about these issues has led to a new manufacturing paradigm of environmentally conscious manufacturing (ECM). However, there are various barriers to the implementation of ECM. A proper understanding and analysis of these barriers will allow the management of the company and government to prioritise their focus to mitigate root barriers for effective implementation of ECM. This paper aims at identifying the barriers to ECM, developing a model of these barriers using statistical analysis and testing the model using structural equation modelling technique. The results provide three types of barriers – internal, policy and economic. The results show that internal barriers are the root barriers and cause policy and economic barriers. It reflects that the barriers which are internal to the organisation should be mitigated first for effective implementation of ECM.