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Sustainable manufacturing is crucial to achieving carbon neutrality targets. However, research on the sustainability of manufacturing systems is limited, and high consumption, low efficiency, and high emissions have resulted in high resource consumption and rapid environmental degradation. Therefore, it is of great importance to establish an evaluation and improvement indicator system conducive to sustainable development. To this end, this study developed a data-driven methodology for evaluating and enhancing the sustainability of manufacturing systems. Manufacturing system production process data, with data dimensions unified via the emergy method, were used to construct a sustainable development evaluation model that includes four perspectives: economy, environment, society, and sustainability. The model was applied to a flange production workshop in China to analyze the interrelation mechanisms among energy consumption, resource consumption, and environmental pollution, and identify optimization schemes to improve sustainability. After implementing these optimization schemes, the emergy yield rate (EYR) of the flange increased by 23.40%, the environmental load rate (ELR) decreased by 19.03%, the per capita emergy (EPP) increased by 6.88%, and the emergy-based sustainability index (ESI) increased by 52.76%. The method presented herein offers a novel and effective tool to analyze and visualize sustainable development in manufacturing systems and identify the relationship between technology and management in the manufacturing industry; however, this method is based on historical data and rules, and lacks of flexible response to unknown situations. The results provide a reference for enterprises to achieve sustainable and lean manufacturing. [ABSTRACT FROM AUTHOR]

The explosive growth of the logistics industry has led to an increase in energy consumption and carbon emissions. To reduce emissions and increase the efficiency of the logistics industry, we studied the driving factors and decoupling effects of carbon emissions of logistics industry (LICE). First, an energy coefficient method is used to calculate the LICE. Second, the Logarithmic Mean Divisia Index (LMDI) decomposition method is used to decompose the driving factors of LICE into five types. Third, the decoupling model is used to explore the decoupling relationship between economic growth and LICE. Considering Anhui Province as an example, this study describes the method's implementation process based on a comparison of the four Yangtze River Delta provinces and cities. The results indicate that the growth rate of LICE in Anhui Province has decreased during the research period, from 9.7% in 2013 to 2.1% in 2021; however, the Tapio decoupling elasticity has been approximately 0.4 for the last 2 years, remaining in a weak decoupling stage from economic development. The LMDI decomposition results indicate that the average contribution of economic level to carbon emissions is 1.763. This study proposes some solutions and recommendations for the logistics industry's low-carbon development to offer methodological and theoretical support for LICE research. [ABSTRACT FROM AUTHOR]

The sustainability of industrial production systems is considered to be the key to promoting green transformation and upgrading of manufacturing industry. This study proposes an emergy-based method for the measurement and evaluation of the sustainability of industrial production systems. The method uses emergy as a measure, expresses all types of inputs and outputs of production systems in terms of solar emergy, and constructs indicators for the sustainable evaluation of industrial production systems that account for economic and environmental benefits from the perspectives of system functions, ecology, and sustainability. This method was applied to a disc cam machining system at a machinery company, where the user was able to quantify the sustainability of the production system and, through feedback, optimise the production process to reduce energy consumption and environmental pollution and improve the sustainability of the production process. The results show that after optimization, the emergy yield ratio of the disc cam machining system is increased from 1.45 to 4.32, the environmental load ratio is reduced by 16%, and the emergy-based sustainability index is increased by 85%. The system has long-term sustainable development capability in the future. This study provides a new theoretical perspective on sustainability assessments of industrial production systems, and our findings provide a scientific basis for guiding the sound operation and sustainable development of industrial production systems. [ABSTRACT FROM AUTHOR]

As industry is the world's leading carbon emitter, promoting industrial carbon reduction is of key significance to carbon peak and carbon neutrality. Using a data-driven method, based on the collection and processing of relevant data from statistical yearbooks and others, we analyze the efficiency and amount of carbon emission of each industrial sector after processing multi-dimensional data by the improved IPCC EF method of calculating carbon emissions. In addition, we adopt the LMDI decomposition method for data modeling to measure the contribution of energy efficiency, industrial structure, GDP per capita, and population size to carbon emission changes, to identify targets for industrial carbon reduction, and to propose a targeted optimization path for carbon emission. We show how the method is implemented by taking the statistics of Anhui Province from 2010 to 2019 as an example and advises on an optimization path for carbon emission in Anhui Province. This study is of both theoretical and practical significance as it provides theoretical and methodological support for the low-carbon development of the regional industry, and provides a reference for other countries and regions to explore the path of low-carbon and environment-friendly green transformation and upgrading. [ABSTRACT FROM AUTHOR]

With growing concerns about energy and environmental issues, much research attention has been focused on manufacturing activities that consume significant amounts of energy and influence the environment. In the manufacturing field, additive manufacturing (AM) is a new production technology that can process complex parts and has high material utilization, which also has the problem of excessive energy consumption and has raised concern. However, the existing research primarily focuses on the process of AM energy consumption and its impact on the environment; the energy consumption distribution of AM equipment is still lacking. This study proposes an analytical method for addressing the energy consumption distribution of AM equipment by classifying the equipment into different energy units. In particular, the energy consumption and energy distribution of different types of AM equipment including fused deposition modeling (FDM), stereo lithography apparatus, and selective laser melting are discussed. Then, the energy consumption distribution characteristics of the three different AM equipment are investigated by machining a conventional structure using the proposed energy consumption quantification method based on energy units. The results show that the proposed method can effectively and quickly predict the energy consumption of AM equipment. Based on the energy consumption distribution method, to improve the process energy efficiency, a process optimization method considering energy consumption and forming quality is proposed to obtain the optimal process parameters of FDM. This method can provide support for energy consumption prediction and energy efficiency improvement of AM. [ABSTRACT FROM AUTHOR]

Highlights • Performing a comprehensive review and analysis of the energy performance certification. • Developing an operational definition of the energy performance certification. • Illustrating the scope and data of the energy performance certification. • Classifying the energy performance certification. • Analyzing the practicability of the energy performance certification. Abstract The energy performance certification has been recognized as an effective assessment methodology and tool to systematically manage energy consumption and improve energy performance. In the process manufacturing industry and building industry, a large number of energy performance certifications have been applied worldwide with remarkable results achieved in energy saving and emissions mitigation. Mechanical manufacturing industry, which is characterised as a typical discrete manufacturing having a wide distribution in operations with large consumption of energy and low efficiency, has a considerable potential of benefiting from energy saving and emissions mitigation. The objective of this paper is to perform a review and analysis of energy performance certification in the mechanical manufacturing industry for evaluating its potentials and applicability for performance enhancement. We begin with analyzing energy performance certification and research gaps to develop an operational definition of energy performance certification. The scope of energy performance certification and the method for data acquisition are reviewed. Next, we establish the classification of energy performance certification from perspectives of the energy benchmarking, rating and labelling to lay a foundation for its implementation framework and evaluating its practicability. Through the systemic review and analysis, the current state of researching energy performance certification is provided with the methods for developing energy performance certification summarized and analyzed. These findings are useful references for managers to strengthen energy management and monitoring and improve energy performance in the mechanical manufacturing industry. [ABSTRACT FROM AUTHOR]

Highlights • Presenting an emergy-based evaluation and improvement for manufacturing systems. • Constructing an emergy-based sustainable measure model. • Establishing an evaluation index system. • Proposing an improvement benchmarking card for sustainable manufacturing systems. Abstract Sustainable manufacturing, regarded as resource efficient, environment-friendly and customer satisfaction production, is major driving force for sustainable development. With growing demand for decoupling between resources and world economic development, accelerating sustainable manufacturing has become an important strategy. Therefore, a novel method based on emergy theory is proposed to perform the comprehensive evaluation and improvement of manufacturing systems. Firstly, drivers and challenges are analyzed, and the boundary and connotation of manufacturing systems are defined. Then, an emergy-based calculation model of the energy, material, service and waste is presented considering the variety and dimension of the input and output of manufacturing systems. The model expresses the mechanism of the transfer, coupling and conversion of the emergy for manufacturing systems. Besides, some indicator systems are established including functional emergy indicators, structural emergy indicators, eco-efficiency emergy indicators and sustainability indicators of manufacturing systems. The inner link between the economic, environment and social benefits of manufacturing systems is revealed through these indicators. On this basis, an improvement benchmarking card is developed to achieve the excellent quality, high efficiency, energy reduction, resource saving and environmental protection of manufacturing systems. Finally, a case study illustrates the practicability of the proposed method, and results show that the proposed method provides theoretical support for evaluating and improving the sustainability of manufacturing systems to coordinate the resources and development of the manufacturing industry. [ABSTRACT FROM AUTHOR]

Energy efficiency improvement and environmental impact reduction are emerging issues in the manufacturing industry. Aside from cutting, metal forming is also an important process in manufacturing. Metal forming is energy intensive because of the low energy efficiency of the used metal forming press. Although many literature reviews focused on the energy reduction and energy efficiency of machine tools, a comprehensive literature review of metal forming processes remains lacking because of the great difference between cutting machines and forming equipment. In addition, methods for energy efficiency and energy-saving still need to be promoted in metal forming. In this review, a novel hierarchy of the metal forming system was presented to describe the relationship among the equipment, process, and manufacturing system, providing a guideline of methods for energy efficiency and saving in metal forming. Then, existing energy consumption modeling and estimation theories and methods were discussed from two aspects. One is energy monitoring and modeling of metal forming equipment, and the other is process energy analysis of metal forming based on different parameters. On the basis of the hierarchy of the metal forming system, the present methods and technologies aiming to promote energy efficiency and energy saving effects were discussed from the aspects of equipment design and control, process optimization, and scheduling management and use. Thus, this review may serve as a reference for the decision-making of producers and managers to realize energy efficiency and energy saving at the system level. In addition, the major points that need attention are accurate energy models and control of forming equipment as well as the integrated optimization of equipment, process, and scheduling. [ABSTRACT FROM AUTHOR]

In order to quantitatively evaluate and improve the sustainability of machining systems, this paper presents an emergy (the amount of energy consumed in direct and indirect transformations to make a product or service) based sustainability evaluation and improvement method for machining systems, contributing to the improvement of energy efficiency, resource efficiency and environmental performance, and realizing the sustainability development. First, the driver and challenge are studied, and the scope and hypothesis of the sustainable machining system are illustrated. Then, the emergy-based conversion efficiency model is proposed, which are (1) effective emergy utilization rate (EEUR), (2) emergy efficiency of unit product (EEUP) and (3) emergy conversion efficiency (ECE), to measure and evaluate the sustainable machining system from the perspectives of energy, resource and environment. Finally, the proposed model is applied to a vehicle-bridge machining process, and the results show that this paper provides the theoretical and method support for evaluating and improving the sustainable machining processes to decouple the resources and development of the manufacturing industry. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has been a vital element of smart manufacturing. The high energy intensity or environmental sustainability issue of AM, however, has posed a great challenge to the future massive application, particularly laser-based direct energy deposition (L-DED). This study aims to determine the optimal processing parameters for energy-saving without compromising the geometrical appearance. A quantification model for energy efficiency at the process level was established, with two energy efficiency indicators of AM process. Then, a meta-heuristic Mayfly algorithm, augmented with Bayesian technique and mutation strategies, was proposed to improve hyperparameters in a typical machine learning model (XGBoost). Based on the full factorial L-DED experiments, this study compared the improved XGBoost with four types of XGBoost derivatives via four algorithm evaluation metrics. Non-dominated sorting genetic algorithm II was adopted to optimize the processing parameters subject to the constraints of geometrical appearance. Results indicated that the proposed algorithm outperformed other XGBoost derivatives in terms of prediction accuracy and convergence rate. The energy efficiency could be improved by 76.35 J/g or 6.78 % on average while ensuring the geometry of the deposited layers. This study could help enhance energy-efficient additive manufacturing via proper processing parameters selection and facilitate the sustainability in AM domain. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) has significant advantages, including design freedom, mass customization, and complex-structure manufacturing capabilities. As reducing the manufacturing energy is challenging in terms of the industrial sustainability, the AM energy consumption must be further explored. Existing energy consumption quantitation methods for AM require complex models that considering the energy characteristics of equipment. Therefore, we propose a feature-based energy consumption quantitation method for complex AM parts using simple models and suitable for different AM technologies. First, a feature segmentation method is proposed to divide complex AM parts into typical AM features. Then, the energy consumption model for each AMF is developed for energy consumption quantification during part fabrication. Finally, the energy consumption of a typical mechanical part manufactured via three different AM processes is investigated using the proposed method and measured experimentally. The results show that the proposed method can effectively and rapidly predict the energy consumption of AM processes with an accuracy of more than 95 %. Furthermore, the efficiency of the three AM processes is compared and discussed to address suitable efficiency improvement methods. In general, the proposed method can be integrated into three-dimensional AM models, providing a reference for the structural optimization of AM parts and sustainable manufacturing. • A feature-based energy consumption method for complex AM parts is proposed • The proposed method uses simple models and is suitable for various AM technologies • Feature dissection is employed to divide AM parts into typical AM features • The proposed method predicts energy consumed in AM parts effectively and accurately [ABSTRACT FROM AUTHOR]

Energy modeling and visualization of machining have been recognized as effective and powerful ways to explore energy-saving potential and to improve energy efficiency. However, energy modeling and visualization of the drilling process have not been investigated adequately. To address this challenge, sub-power models-based energy modeling and multi-angle energy visualization analysis methods of drilling process were proposed in this study. More specifically, three tasks were carried out: (1) detailed sub-power models of drilling were established; (2) sub-power models-based energy modeling method of drilling was proposed; (3) based on the detailed sub-power models and energy data, multi-angle energy visualization analysis was conducted. Application of the proposed drilling energy model in common drilling processes indicated that its average prediction accuracy of the proposed drilling energy model was 96.2%. The results also showed that 7417.8 J energy saving and 12.6% energy efficiency improvement were achieved with the visualization analysis. The proposed method contributed to energy-saving activities for the drilling process, including providing high accuracy energy model, analyzing energy saving potential and improving energy efficiency. We believe that the outcomes of this research can help engineers and managers to better understand and manage the energy characteristics of drilling. • Proposing a new, sub-power-based energy modeling method of drilling. • Average prediction accuracy of drilling energy is improved to 96.2%. • A novel multi-angle energy visualization analysis method is proposed. • 7417.8 J energy saving potential is identified by energy visualization analyzing. • Energy efficiency is improved by 12.6% through implementing the proposed method. [ABSTRACT FROM AUTHOR]

Remanufactured mechanical products with high-added value are generally claimed to gain environmental benefits. These claims were made based on different products and assessment methodologies. The variability of life cycle assessment (LCA) results precludes a meaningful comparison across products and studies. This paper aims to critically and systematically evaluate the lifecycle environmental performance of remanufactured products compared with their new counterparts and to identify the key factors, strengths, and limitations in the assessment procedure. Faced with the noteworthy variations, we closely examined and harmonized the unit function, allocation approach, system boundary, impact assessment method, and the underlying assumptions in screened 20 papers regarding 11 types of products. The environmental indicators adopted in this study were global warming potential (GWP) and primary energy consumption (PEC). In terms of these two indicators, the environmental burdens of remanufactured products relative to newly manufactured alternatives were harmonized to the comparison ratios. With these harmonized samples, descriptive statistics were calculated using Monte Carlo Simulation to disclose the variations of comparison results and identify the general tendency. Results of this meta-study showed that remanufacturing could contribute to over 50% reduction for GWP when usage and end-of-life stages were excluded from the life cycle. The GWP and PEC of remanufactured mechanical products account for 28.5% and 25.9% of the new counterparts, respectively, on average. This meta-analysis of comparative LCAs on new and remanufactured products would advance the understanding of the environmental advantages of remanufacturing. • Meta analysis was performed on the comparison of new and remanufactured products. • Variation in the calculations of life cycle impact was harmonized. • Remanufactured products cause over 50% reduction in Global Warming Potential. • The key factors and limitations in the screened papers were identified. [ABSTRACT FROM AUTHOR]

The stamping industry is critical in the automotive and aerospace industries, and the environmental impacts and sustainability of stamping systems have attracted considerable attention. To analyze the environmental impact and sustainability of stamping systems quantitatively, this paper presents an emergy-based evaluation method considering all the associated environmental impact factors of a pressing workshop including material and energy consumption, waste flows, time and mass losses, and processing costs. On the basis of analyzing the stamping processes and sustainability, this method comprises data collection, emergy based sustainability evaluation model and the development of sustainable evaluation indexes and systems. Based on the proposed method, the environmental impact of an industrial vehicle stamping workshop was evaluated. The results show that the net emergy yield ratio of the stamping system was greater than 2, and the waste emergy output ratio was very low, indicating that the system had high productivity levels, high yields, and low pollution discharge rates. However, its sustainability index was less than one owing to its high energy and material consumption during the production processes. To reduce the environmental impact of this stamping system and improve its sustainability, we investigated the potential improvements that could be achieved in energy consumption, productivity, and environmental impact by implementing energy-saving scheduling in the stamping workshop. The results show that the corresponding net emergy yield ratio and sustainability index of the system were both improved. The proposed emergy-based method could be used to quantitatively evaluate the environmental impacts and sustainability of stamping systems and facilitate efforts to reduce the environmental impacts of pressing workshops while improving their productivity and economic profitability. [ABSTRACT FROM AUTHOR]

• Analyzing driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods. • Economic activity being the greatest driving force for CO 2 emissions growth of China. • Reducing the proportion of coal consumption mainly through vigorous development of natural gas currently. • Electricity trading can serve as a valid temporary means for reducing CO 2 emissions. Anthropogenic carbon emission gives rise to a situation where global warming is becoming serious. China is paying for reducing carbon emissions. The concept of carbon curse suggests that countries rich in fossil fuels tend to be closely linked to high carbon emissions, but this is not absolute, which reminds policymakers that the policies implemented are positively correlates with carbon emission reduction. This study is also aimed at this, hoping to provide some proposals about reducing CO 2 emissions to policy-makers by decomposing and analyzing the important factors. To achieve this target, this paper employs the extended the Kaya identity, combines the LMDI method to analyze the impact factors of carbon emissions in China from 1996 to 2016 and discusses the effects and causes of each factor according to the actual situation. It is found that the economic activity is the greatest driving force to promote carbon emissions, while on the contrary, energy intensity is the biggest suppressor. Optimizing industrial structure, improving the structure of energy and export-import trade and intensifying the development of clean energy can effectively restrain the growth of carbon emissions. In addition, the relative innovation point in this study is to analyze carbon emissions with the combination of electricity trading and discusses that increasing imported electricity is also a strategy to reduce carbon emissions. [ABSTRACT FROM AUTHOR]