Green Manufacturing System Research Articles

How does green manufacturing enhance corporate ESG performance? — Empirical evidence from machine learning and text analysis

Green manufacturing, widely recognized as a crucial avenue for companies to achieve sustainable competitive advantages, exerts significant spillover effects on both environmental protection and social responsibility. Accordingly, this can significantly enhance corporate Environmental, Social, and Governance (ESG) practices and enhance overall ESG performance. This study focuses on Chinese A-share listed firms between 2009 and 2022, characterizing their ESG performance. Employing quasi-natural experimental methods, this research evaluates the causal relationships and specific channels through which green manufacturing enhances corporate ESG performance. The findings demonstrate that green manufacturing significantly empowers companies to strengthen their ESG performance. Channel analysis indicates that enhanced green innovation capabilities and the reduction of financing constraints constitute two critical channels through which green manufacturing facilitates ESG performance improvement. Further analysis indicates that all three subsystems in the green manufacturing system significantly empower companies to enhance ESG performance to varying degrees, with the most significant empowerment effect observed in the environmental dimension of ESG performance. The analysis below indicates that the enhancement of corporate ESG performance yields dual benefits, reflected in both economic gains and reputational enhancements.

Analysis of reduction of carbon emission and dynamic service policies in a green manufacturing system under isoperimetric fixed servicing budget constraint

In the recent highly saturated, fluctuated as well as competitive marketing situation, economic growth, stability and survival of a manufacturing company are substantial factors for the competent authority of a manufacturing firm. Again, due to the harmful effects of different chemicals and preservative oriented products, consumers gradually show their sensible interest towards the green products and their benefits. Furthermore, emission reduction and carbon emission tax become major issues on the sustainable growth and reputation of a manufacturing company. Fundamentally, considering these factors, this study demonstrates the prior decisions regarding best-found policy of a manufacturing company considering the effects of service with sold eco-friendly (green) products under the effects of emission taxation and reduction policies. The demand effected by level of greenness, price and dynamic service provided to the consumers. Now, due to the budget constraint, manufacturer estimates a fixed budget due to service to the consumers along with the items sold. Again, based on the carbon emission reduction policy, two distinct cases are arisen which are analyzed separately. Due to the budget constraint, maximization problem associated to the model becomes an isoperimetric control problem. Then to illustrate the realistic feasibility the proposed model, a physical example is taken under consideration and it is solved using Teaching–learning-based optimization algorithm (TLBOA) considering each of the cases. Finally, the sensitivity analyses are performed to get some important implications for the manager of the proposed manufacturing system.

Impact of warranty and green level of the product with nonlinear demand via optimal control theory and Artificial Hummingbird Algorithm

Due to the current environmental situation and human health, a green manufacturing system is very essential in the manufacturing world. Several researchers have developed various types of green manufacturing models by considering green products, green investments, carbon emission taxes, etc. Motivated by this topic, a green production model is formulated by considering selling price, time, warranty period and green level dependent demand with a carbon emission tax policy. Also, the production rate of the system is an unknown function of time. Per unit production cost of the products is taken as increasing function of production rate and green level of the products. In our proposed model, carbon emission rate is taken as linear function of time. Then, an optimization problem of the production model is constructed. To validate of our proposed model, a numerical example is considered and solved it by AHA. Further, other five metaheuristics algorithms (AEFA, FA, GWOA, WOA and EOA) are taken to compare the results obtained from AHA. Also, concavity of the average profit function and convergence graph of different metaheuristics algorithms are presented. Finally, a sensitivity analysis is carried out to investigate the impact of different system parameters on our optimal policy and reach a fruitful conclusion from this study.

Uniform-machine scheduling problems in green manufacturing system

Uniform-machine scheduling problems in green manufacturing system

Integrated Multi-Vendor Single-Buyer Inventory System Model in Textile Waste Processing Industry

PT. Superbtex Nonwoven Division is one of the industries implementing a green manufacturing system in Bandung by using textile solid waste as raw material and processing it into value-added finished products. However, the solid waste generated by consumers and garment factories is very large and cannot be accommodated in its entirety by PT. Superbtex Nonwoven Division. Another problem arises in terms of inventory both for vendors and buyers; delivering waste from vendors to buyers in small quantities and frequently can lower inventory costs for buyers, but concurrently raise transportation expenses for vendors, and vice versa. Therefore this research was conducted to solve the problem of an integrated multi vendor-single buyer inventory system that considers independent transportation, sorting, and disposal to find the minimum total system cost by finding the optimal value of order lot size, delivery frequency, and proportion of order lot size. that each vendor needs to send to the buyer. Problem-solving is done using the Mixed Integer Non Linear Programming (MINLP) method with the LINGO 18.0 solver. The results obtained from this study stated that the sorting costs at vendor 1 (S1), the sorting costs at the buyer (Sb), the transportation variable costs (Fy), the delivery truck capacity (X), and the demand rate (D) have a significant effect to changes in total system cost (TC). So that the five parameters need to be estimated carefully to determine the optimal system cost.

On developing a green and intelligent manufacturing system

This paper aims to present an autonomous intelligent system that improves the performance of conventional manufacturing processes to make them friendly to the environment. This improvement is made considering objectives that involve a reduction of supplies, use of tools, and low energy consumption; but maintaining desirable characteristics of machined parts in quality, mechanical properties, and dimensions. We present an architecture that integrates modeling with neural networks, validation using metrical statistics, and multi-objective optimization based on MOEA/D which takes experimental or historical data of the process and generates a set of parameters to satisfy all three criteria of sustainability, efficiency, and quality. Two cases for welding and machining process are presented to illustrate the use of the proposed approach which results in evidence of the feasibility of having green and intelligent manufacturing systems. In the welding process, the user can select a low amperage but increase lightly the cycles of operation to reduce energy consumption but satisfy the quality objective. In machining, the user can select a solution to avoid the use of cooling maintaining quality and efficiency in acceptable levels of operation.

The Effectiveness of the Green Design and Manufacturing Decision in Achieving the Outstanding Performance of the Industrial Companies: An Analytical Study in Al-Zawraa General Company

The objective of this research is to analyze the impact of product design decisions and green manufacturing on Al-Zawraa General Company's competitive advantage in Iraq. Data was collected through a questionnaire that measured key variables، such as product design، green manufacturing، and outstanding performance. Each major variable was further evaluated through three sub-dimensions. Out of the 75 employees invited to participate، 60 staff responded to the questionnaire. Quantitative and qualitative methods، such as arithmetic means، standard deviations، and confirmatory factor analysis، were employed to examine the effect of the key variables in implementing the green manufacturing system in the company. The study's findings suggest that the company's management should reconsider its approach to green technology by implementing modern automation methods that utilize environmentally friendly energy sources. This change would not only help to reduce industrial pollution rates and benefit the environment but also enhance the company's appeal to consumers and ensure its longevity and competitiveness in the local and global industrial markets. Furthermore، the study revealed a strong correlation between the key variables and the successful adoption of the green manufacturing system.

Status and challenges of green manufacturing: Comparative analysis of China and other countries

Energy-intensive manufacturing is a major source of GHG emissions and environmental impacts. Countries in the world are all facing challenges in green manufacturing transformation. The conceptual evolution and actual implementation of green manufacturing in China and other countries show some similarities but also discrepancy. This paper describes the green manufacturing system in China from four aspects: green factory, green product, green park and green supply chain. The comparison of the four aspects is carried out between China and world's major economics including Europe, the United States, Japan, etc. Our results show that the common challenges among countries in the process of promoting green manufacturing are absent of corresponding product baseline standards in evaluating green products and no sufficient life cycle planning within plant boundaries. China is faced with specific challenges that there is no clear green product evaluation standards in life cycle assessment methods, system boundaries and life cycle stages of products. Other countries such as Germany and the United States are faced with challenges that there is a lack of environmental and performance evaluation as well as concrete implementation of life cycle evaluation within the factory boundary, and that there is difficulty for the national manufacturing industry chain to achieve a closed loop since industrial migration. We suggest that China draw lessons from the European Union, the United States and Japan in the elaborate methods design of green products assessment. As such, China's green factory assessment framework and strict government guidance can be a reference for other countries.

Industrial structure optimization under the rigid constraint of carbon peak in 2030: A perspective from industrial sectors

To explore how China can achieve sustainable economic development through industrial structure optimization of 28 sectors, this paper proposes a multi-objective economic-CO2 emission optimization model based on a rigid carbon peak constraint. Different development scenarios are set to reflect the tradeoff between economic development and CO2 emission control. The results reveal that (1) China can peak with 15,919.21 Mt. and 15,861.62 Mt. in 2030 under the emission control scenario and equilibrium development scenario, respectively. (2) The manufacturing sector (dominated by S11, S12 and S14), along with the electric power and heat production sector (S22) contribute most of the CO2 emissions in peak year. (3) After achieving the carbon peak, S11 has greater potential for economic growth and emission reduction; S12 and S14 will pay a higher cost to increase their emission reduction; while S22 can maintain stable output growth but has limited potential to reduce emissions. In addition, this study recommends that the construction of green manufacturing system and differentiated emission reduction policy system are necessary measures to reduce the carbon peak.

Analysis of supporting factors of the successful implementation of green manufacturing for Indonesian Manufacturing SMEs

Many manufacturing SMEs experience difficulties in finding an effective framework for building green manufacturing system for production and operations activities. The study purpose to identify the elements support the successful implementation of green manufacturing systems in SMEs, develop a conceptual hierarchical model of elements based on the ISM approach, and identify and analyze the dominant elements. This study applies a survey method to obtain data that is relevant to the research objectives. The respondents involved were 32 managers/owners of manufacturing SMEs located in Tegal Regency, Central Java Province of Indonesia. The study results show the existence of 39 supporting elements for the successful implementation of green manufacturing in SMEs. Factor analysis shows that these elements can be simplified into 12 common elements. MICMAC analysis shows that five elements can be categorized as dependent elements; lower production costs, environmental knowledge, Improved waste management, investing in innovation and technology, and new market opportunities; seven elements can be categorized as independent elements, namely green supply chain, government promotion and regulation, pressure from the market, organizational culture, involvement of various business stakeholders, top management commitment, and environmental specialist assistance. ISM analysis shows there are four elements that can be categorized as dominant elements; namely green supply chain, involvement of various business stakeholders, top management commitment, and government promotion and regulation.

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.

Impact of Smart, Green, Resilient, and Lean Manufacturing System on SMEs’Performance: A Data Envelopment Analysis (DEA) Approach

In the present era of the fourth industrial revolution, small and medium enterprises (SMEs) are adopting smart, green, resilient, and lean (SGRL) practices to enhance their performance and achieve sustainability. For SMEs to perform well in their supply chains and satisfy customers, the impact of the combined effects of SGRL manufacturing on SMEs’ performance needs to be studied. Although SGRL manufacturing has been studied independently in order to understand its impact on SMEs’ performance, there is still a need for significant research on its combined effect. The objective of the present work is to evaluate the performance of SMEs and to understand the combined effect of SGRL manufacturing on SMEs’ performance. This research applied the data envelopment analysis (DEA) methodology to evaluate 30 SMEs identified in the northern region of India. A DEA model was developed that considers environmental, operational, and social performances as output criteria while considering SGRL practices as input criteria. Sixteen decision-making units (DMUs) were identified as inefficient using the DEA approach and one of them was considered for a case study for comparison with efficient SMEs. The case study employed a Strength, Weakness, Opportunity, and Threat (SWOT) analysis to provide remedial action to one of the selected underperforming SMEs, i.e.,SME11. The strengths, weaknesses, opportunities, and threats of SME11 were identified and strategies were suggested by benchmarking SME11 with one of the efficient SMEs, i.e., SME23. The findings of this research work will help policymakers, owners, and managers of SMEs take necessary actions and enhance their performance by adopting the proposed DEA model using SGRL manufacturing practices.

Going green: Impact of green supply chain management practices on sustainability performance.

The rising environmental challenges are capturing the attention of stakeholders of corporations due to increasing competition. The sustainable performance of firms does not merely gauge their economic performance but also their sustainable development. Since the environmental supply chain management of firms has an important part in maneuvering their sustainable performance, the present study focuses on assessing the impact of green supply chain management practices on the sustainable performance of the textile, automobile, and tobacco industries. The data were collected from 384 organizations and analyzed through SPSS and AMOS. The results reveal that the impact of green manufacturing, green purchases, eco-design, and green information system are significant and positive on the sustainable performance of the organizations, whereas the impact of cooperation with customers is insignificant. Similarly, the moderation of institutional pressures between green manufacturing, green purchases, eco-design, and sustainability performance is insignificant, whereas it significantly moderates between cooperation with customers, green information systems, and sustainable performance. The study is significant and novel for considering five different factors of green supply chain management (GSCM): green manufacturing, green purchasing, cooperation with customers, eco-design, and green information systems. Furthermore, adding institutional pressures as a moderator between GSCM and sustainable performance adds to the novelty and uniqueness of the research. The managerial implications have also been discussed.

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.

Coupling and coordinated development of urban land use economic efficiency and green manufacturing systems in the Chengdu-Chongqing Economic Circle

• Measure the CCD of land use economic efficiency and green manufacturing system level • Construct a comprehensive and multi-dimensional green manufacturing system • Combine SBM model, the weighting method, the CCD model and convergence model • Spatially, the urban belt aggregation pattern exists in the Chengdu-Chongqing UA • In temporal distribution, the CCD begins to shift to the direction of convergence Industrial activity has been a powerful driver of urbanization and economic growth in China, which has often been at the expense of the natural environment. However, sustainable urban development requires improvements in the coupling and coordination of urban land use economic efficiency and green manufacturing systems. Based on statistical data from the Chengdu-Chongqing urban agglomeration, two index systems: urban land economic efficiency and green manufacturing systems; were developed to reveal the agglomeration's spatio-temporal sustainable development evolution from 2007 to 2019. A global SBM-DEA model was combined with a weighting method, a coupling coordination degree (CCD), and a convergence model, from which it was found that the CCD between the urban land use economic efficiency and green manufacturing system level in the Chengdu-Chongqing Economic Circle was in a slow growth stage. The government should formulate a scientific regional urban development strategy that condenses the special relationship between the two core cities and strengthens their driving effects to decrease the siphoning effect.

Pengukuran kinerja green manufacturing pada industri tahu sumedang untuk meningkatkan kinerja terhadap lingkungan menggunakan GSCOR dan LCA

The application of an environmentally sound industry is one of the environmental conservation issues and a global issue in the industry. The application of an environmentally sound industry can be implemented in the Green Manufacturing system. The tofu industry in the production process uses a high volume of water, resulting in a high volume of liquid waste, which can pollute the environment. The problem with the Sari Kedelai industry is that there has not been a performance measurement on the environment and an analysis of the resulting impact. This study aims to measure the performance of Green Manufacturing with the GSCOR (Green Supply Chain Operations Reference) and LCA (Life Cycle Assessment) methods as well as formulate suggestions for improvements to the Sari Kedele industry in the context of implementing Green Manufacturing. The results of performance measurement using the GSCOR method in the Sari Kedele industry has a value of 79.78 which was included in the good category. Environmental impact analysis is assessed with a focus on GHG emissions (Greenhouse Gases) that uses LCA with an ISO 14040 approach resulting in a GHG emission value of CO2-eq/kg tofu of 3.7107.

Implementation of Strategic Structure By Integrating Flexible Manufacturing System With Green Technology for Enhancement of Productivity And Quality Of Product

The worldwide advancements of new innovations are developing at a touchy rate, yet associations are embracing more gradually henceforth, serious promoting society and incorporated supervisory crews are required in an organization to exploit new advances. Adaptable assembling innovations are seen by organizations to be a significant component Exceeding competitiveness and seriousness. Notwithstanding, dominating in the present market isn’t easy and straightforward like the procurement of fresh improvement. So as to accomplish more of advantages, the structural framework associations will combine to ensure that the execution of innovation should lead to the normal benefits. Hence, a structure that encourages flexible manufacturing system companies deciding the prerequisites of the FMS reception, with the correct blend of green technology and vital components is required. The study examines particular dimensions of green manufacturing Index Applicability and FMS such as Information technology, planning, flexible automation techniques. The outcome will determine the major substantiate to establish and strengthen the value of product with superior performance, Using the findings the research will suggests the implication and adoption for further research. It would definitely enhance the performance in any industrial organisation with economic growth. This Research aims to report the findings of an exploratory work by integrating Green Manufacturing and flexible Manufacturing system techniques to generate new strategies which can be further administered in an industrial organization and sectors such as component manufacturing, automobile parts and processing sectors.

The integrated lean and green manufacturing system: a case study at the peeled loaf production

The bakery industries soared as bread become one of the staple food for many people. UD. ABC is one of the bakeries in Banda Aceh that produces various types of bread and jam includes the peeled loaf. Peeled loaf uses many machines for its production process thus will produce waste and consume lots of energy. This study aims to analyze waste and measure energy use in the production process of peeled loaf based on the integrated Lean and Green Manufacturing concept. There are VSM and EVSM as a tool to describe the flow of material and energy usage from the production process. The activities of Value Added (VA), Non-Value Added (NVA) and Necessary Non-Value Added (NNVA) will be analyzed using PAM. The tool for improvement recommendations is five whys analysis. Then, the Future State Map (FSM) shows the improved design with a reduction in the lead time of 20.28 minutes. From this study also obtained the results of saving energy use as much as 0.13 kWh. This energy-saving will realize a lean and environmentally friendly production process at UD. ABC.

An Evaluation Model for Green Manufacturing Quality of Children’s Furniture Based on Artificial Intelligence

With the differentiation of the furniture market, there is a growing demand for children’s furniture. The design of children’s furniture must fully consider the special cognition and preference of children, highlight environmental friendliness and health, and benefit the physical and mental development of children. These design objectives are similar to those of green furniture. Therefore, it is necessary to accurately evaluate the quality of green manufacturing, the key link of green furniture production, with the aid of the excellent data processing technique of artificial intelligence (AI). Thus, this paper summarizes the AI applications in quality testing of children’s furniture and statistical analysis on its greenness, and constructs an evaluation model for green manufacturing quality of children’s furniture. Firstly, the authors introduced the architecture of the green manufacturing system for children’s furniture, and analyzed the product lifecycle and environmental pollutions. On this basis, a complete and scientific evaluation index system (EIS) was constructed. Next, the weight coefficients of the goal layer and criteria layer were determined by the entropy method, and the initial evaluation result were provided. Finally, a comprehensive evaluation model was established for the green manufacturing quality of children’s furniture, based on backpropagation neural network (BPNN), and genetic algorithm with adaptive mutation (AMGA). The proposed EIS and model were proved effective through experiments. The research results provide a reference for the quality evaluation in other fields.

Optimal Manufacturing-Reconditioning Decisions in a Reverse Logistic System under Periodic Mandatory Carbon Regulation

Due to environmental concerns, firms are under increasing pressure to comply with legislations and to take up environmental strategies. This leads researchers and firms to develop new sustainable supply chains, where a new area has emerged for a manufacturing and reconditioning system. The originality of this work consists in simultaneously considering carbon emissions strategies, carbon tax and mandatory emission in a manufacturing-reconditioning system. The proposed system is composed of two parallel machines, a manufacturing stock, a reconditioning stock and a recovery inventory. In order to make the proposed green manufacturing system more realistic, it is assumed that manufactured (new products) and reconditioned products are distinguishable. The quantity of worn products (used products) depends on the sales in the previous periods, and the repair periods of the machines are stochastic and independent. The aim of this work is to determine the optimal capacities of manufacturing and reconditioning stocks that maximize the total profit, as well as the optimal value of worn products under two carbon emissions’ limitations. An evolutionary algorithm is developed, along with an efficient improvement method, to find the optimal value of decision variables. Ultimately, numerical results are provided to show the impact of the period of carbon limit and the worn products (returned products) on decision variables.