Data-driven sustainability evaluation and manufacturing system enhancement from economic, environmental, social, and sustainability perspectives.

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.

Carbon emissions in the logistics industry: driving factors and decoupling effects.

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.

Carbon tax vs. carbon trading in China: which is better for promoting sustainable development of remanufacturing companies?

To accelerate achieving carbon neutrality, the promotion of low-carbon development in the manufacturing industry has been facilitated by the government's implementation of policies such as carbon taxation and carbon emissions trading. These measures have been put in place to reduce carbon emissions and enhance sustainability within the manufacturing sector. Remanufacturing is an important direction for the low-carbon transformation of enterprises, and improving remanufactured product quality is crucial to the sustainability of remanufacturing enterprises. To elucidate the influence of policies aimed at reducing carbon emissions on the quality of remanufactured products, we developed a game model involving three key players: the original equipment manufacturer (OEM), the remanufacturer (IR), and retailers. This model was constructed based on the heterogeneous consumer demand for both new and remanufactured products. The study delved into the effects of various governmental policies aimed at reducing carbon emissions on the quality-related decisions made by remanufacturing enterprises. Our primary focus was on the implementation of two specific policies: a high-level carbon taxation policy and a carbon trading policy characterized by elevated carbon pricing. These policies create a favorable environment for remanufacturers (IR) to enhance the quality of their products. The sales of remanufactured products are influenced by the purchasing preferences of consumers, and carbon reduction policies can be effective in reducing the total environmental impact of manufacturing. Carbon trading policy is most conducive to environmental protection and achieves a win-win situation for economic and environmental benefits for OEMs and IRs when the carbon tax per unit is compared with the carbon trading price. Hence, this situation is favorable for the sustainable growth of existing remanufacturing businesses. Consequently, the government's requirement for subsidies to enhance the quality of remanufactured products and boost the competitiveness of IRs in the market becomes less pronounced.

Data-driven low-carbon transformation management for manufacturing enterprises: an eco-efficiency perspective.

The low-carbon transformation of manufacturing enterprises is considered to be imperative to achieve carbon neutrality. Therefore, we propose a data-driven strategy to achieve a low-carbon transformation of manufacturing enterprises from an eco-efficiency perspective. Following the collection of input (energy, materials, equipment, R&D, and services) and output (waste and products) data from production systems of manufacturing enterprises, an ecological efficiency model of manufacturing enterprise production system was constructed from the perspective of carbon emissions, thus allowing the quantitative evaluation of the ecological efficiency of the production system. Furthermore, a "measurable, evaluable, and optimized" low-carbon transformation and upgrading method for manufacturing enterprise production system was established. Finally, through the production practice data of an enterprise from 2017 to 2021, the feasibility and effectiveness of this method were verified. The results show that this method can effectively improve the ecological efficiency of enterprises by 3.6% and reduce waste emissions by 12%. Our study provides new tools for improving the ecological efficiency of manufacturing systems, along with theoretical and methodological support to manufacturing enterprises for low-carbon transformation.

Subsidizing high-quality remanufactured products for sustainability.

This study aims to analyze the impact of government subsidy policies on the development of remanufacturing enterprises and product quality in the context of carbon peaking and carbon neutrality, to promote the sustainable development of the remanufacturing industry. It establishes a comparative game model for two cases of remanufacturing enterprises respectively producing low-quality and high-quality remanufactured products. In the context of government subsidies for only high-quality remanufactured products, we investigate the effects of government subsidies on remanufactured products' forms, prices, profits, and consumer preferences. The results show that government subsidies for high-quality remanufactured products help not only reduce the quality cost of remanufactured products and lower the wholesale and retail prices but also increase consumer preference for high-quality remanufactured products, enhance the market demand for remanufactured products, and promote scale expansion of the remanufacturing industry. This study provides decision support for governments to formulate subsidy coefficients for remanufacturing enterprises, offers theoretical and methodological support for the decarbonization and scale-up of remanufacturing and reduction of environmental pollution, and has significant practical value for achieving carbon peak and carbon neutralization goals.

Emergy-based sustainability measurement and evaluation of industrial production systems.

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.

Research on carbon emission measurement and low-carbon path of regional industry.

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.

Data-driven evaluation and optimization of the sustainable development of the logistics industry: case study of the Yangtze River Delta in China.

In this study, a data-driven way is proposed to evaluate and optimize the sustainable development of the logistics industry (LI). Based on a comprehensive consideration of economic, societal, and environmental factors, an evaluation index system was established for the sustainable development of the logistics industry (LISD). Logistics industry-related data were collected from the Yangtze River Delta (YRD) from 2011 to 2020. The anti-entropy method was used to determine the index weight and process the data. Furthermore, the coupling harmonization degree and barrier degree models were used to analyze the coordinated development of each subsystem and identify key obstacles. Our results indicate that there are significant temporal and spatial differences in the level of LISD in YRD, with Shanghai (score 0.4834) being the best and Anhui (score 0.4553) the worst, showing a wave-like evolution in time. The coupling and coordination states among the subsystems are significantly different, with that of environmental benefits and other subsystems being poor. Moreover, innovation ability and environmental benefits are the main obstacle factors of this system. Based on the results of this study, targeted optimization countermeasures are put forward and evaluation indicators and research methods are suggested, which will provide the government and practitioners decision support, as well as provide theoretical and methodological support for LISD.

Low-carbon technology service mode with revenue-sharing contract considering advance funding risk.

This study aims to effectively reduce carbon emissions by selecting the low-carbon technology service emission reduction modes. This paper constructs a revenue-sharing contract model based on game theory. The purpose of this paper is to analyze the choice of carbon emission reduction strategies for carbon emission-dependent manufacturers and low-carbon technology service providers with advance funding risk aversion. This study analyzes the effects on the optimal decision-making and profits of both parties of the degree of risk aversion and the investment cost coefficient of carbon emissions reduction for service providers, and initial carbon emissions of manufacturers. The optimal carbon emissions reduction strategy of manufacturers and service providers with numerical analysis is obtained, and the revenue-sharing contract coordination is realized. Finally, the validity of the contract is verified by simulation analysis. The results show that manufacturers and service providers can only achieve optimal cooperation for emission reduction within a certain range of parameters. With different investment cost coefficients of carbon emissions reduction and with different initial carbon emissions, manufacturers will adjust the fixed emissions reduction fee and the revenue-sharing coefficient to encourage service providers to offer the optimal carbon emissions reduction rate. This study enriches theoretical research on low-carbon service chains. It also provides important practical evidence to help manufacturers and service providers choose optimal strategies for coordinating revenue-sharing contracts.

Intelligent monitoring method of tridimensional storage system based on deep learning.

Growing international trade requires more flexible warehouse management to match it. In order to achieve more effective warehouse management efficiency, a shelf status-detection method based on deep learning is proposed. Firstly, the image acquisition of a multi-level shelf containing multiple bays is performed under different time and lighting conditions. Due to the difference in image characteristics between the bottom shelf on the ground and the upper shelf on the non-ground level, the collected images were divided into two groups: floor images and shelf images; and the warehouse status recognition was performed on the two groups separately. The two sets of images are cropped and center projection transformed separately to obtain the region of interest. On this basis, the improved residual network model is used to construct different depot detection models for the two sets of images, respectively, and the above algorithm is verified by actual measurements. In this paper, 102,614 images of 3246 depots with different states of non-ground layer, and 27,903 images of ground layer are collected. They are divided into training set and test set according to the ratio of 4:1, and the accuracy of training set is 99.6%, and the accuracy of test set is 99.3%. The experimental outcomes provide a theoretical method and technical support for the intelligent warehouse system management.

Impact of Carbon Tax and Subsidy Policies on Original Equipment Manufacturers and Remanufacturing Companies from the Perspective of Carbon Emissions.

To analyze the impact of government carbon tax and subsidy policies on the manufac turing industry in the context of carbon peaking and carbon neutrality. This paper constructs a game model based on two government policies: a "carbon tax" policy for the original product and a "subsidy" policy for the remanufactured product, taking the original product and the remanufactured product as the objects. The policy game model is used to study the impact of carbon taxes, government subsidies, and carbon emissions on product quality, sales, and corporate profits. The results show that under the carbon tax and government subsidy policies, the price of remanufactured products will decrease, the quality will increase, sales will improve, and remanufacturers' profits will increase; these outcomes are conducive to the development of remanufacturing enterprises. Meanwhile, the price of original products will increase, quality will decrease, sales will decline, and original equipment manufacturers will have to develop and adopt low-carbon technologies to achieve sustainable development. This paper provides decision support for the formulation of government carbon emission policy, and theories and methods for the sustainable development of the manufacturing industry.

Environmental benefits of remanufacturing mechanical products: a harmonized meta-analysis of comparative life cycle assessment studies.

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.

Data-driven analysis and evaluation of regional agriculture for high-quality development of Anhui Province in the Yangtze River Delta.

This study aims to promote the high-quality development of regional agriculture. This study proposes a data-driven method for regional agricultural analysis and evaluation. Based on the data collection and processing related to regional agricultural development, the location entropy index was used to analyze the industrial agglomeration level, and the shift-share model was constructed to evaluate the industrial structure and competitiveness. Based on the above analysis and evaluation, high-quality development policy suggestions for regional agriculture were provided. Taking the agricultural development of the Yangtze River Delta from 2010 to 2019 as an example, this study shows the implementation process of the method. From the perspective of high-quality agricultural development in the Anhui Province, this paper proposes policy suggestions on industrial structure adjustment and promoting competitiveness. This study provides theoretical and methodological support for the development of high-quality regional agriculture.

Decoupling of wastewater eco-environmental damage and China's economic development.

Wastewater pollution has been considered as a prominent bottleneck restricting global sustainable development. China is one of the largest discharges and eco-environmental damages of wastewater in the world. Through analyzing wastewater discharge data using emergy method in China from 2011 to 2017, the wastewater eco-environmental damage of 31 provinces is calculated with GDP and area to reveal the fundamental origins of inflection point of wastewater discharge in China. Studies results show that, (i) Chinese "12th Five-Year Plan" (2011-2015) is a watershed in wastewater discharge, and the eco-environment damages caused by China's wastewater accounted for more than 1/4 of GDP; (ii) China has the great potential to reduce eco-environment damages of 1.73 trillion $/year; (iii) In 2016 and 2017, wastewater eco-environmental damage has decreased by about 50% compared with that in 2015, and the effect of government policies was remarkable. We conclude that decoupling of China's economic development form eco-environmental damages of wastewater is began to appear, the strict formulation and implementation of China's environmental policies and the green upgrading of industrial structure are main driving forces, and it is little correlation with economic slowdown. This study offers the detailed list of China wastewater pollution and reveals the relationship between wastewater eco-environmental damages and economic development, and shows the experience and achievements of the Chinese government in the treatment of wastewater pollution, which provides a useful reference for the treatment of wastewater pollution in the world.

Emergy-based ecological efficiency evaluation and optimization method for logistics park.

With the rapid development of logistics park, how to evaluate and optimize the ecological efficiency of logistics park to achieve its sustainable development has become a concern of academia. In order to achieve this goal, this paper puts forward a method based on emergy, which processes the data in a unified dimension. By constructing the ecological efficiency evaluation model of logistics park, it quantitatively evaluates the ecological efficiency of logistics park, and analyzes the correlation between various factors and ecological efficiency. The application results of H logistics park show that fuel oil, information technology, net profit, and waste gas are closely related to the ecological efficiency of logistics park, and the correlation coefficients are 0.8248, -0.6949, 0.8544, and 0.7661, respectively. On this basis, the paper puts forward some suggestions to improve the ecological efficiency of the logistics park. This paper provides theoretical and methodological support for the evaluation and optimization of the ecological efficiency of the logistics park.

Driving forces of China's CO2 emissions from energy consumption based on Kaya-LMDI methods.

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 positivelycorrelateswith carbon emission reduction. This study is also aimed at this, hoping to provide some proposals about reducing CO2 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.

Promoting sustainability of manufacturing industry through the lean energy-saving and emission-reduction strategy.

The energy-saving and emission reduction (ESER) strategy is a crucial measure for promoting the sustainability of manufacturing industry in green transition. Analyzing current practices and limitations of the ESER in the manufacturing industry, this paper proposes a new concept entitled lean energy-saving and emission-reduction (LESER) and an approach to effectively improve the energy efficiency and reduce waste emissions. This paper illustrates the definition of the LESER and establishes an implementation framework for LESER to improve the manufacturing process. To quantify and evaluate performance of LESER, the state space model of the carbon footprint for energy consumption and waste discharge is established. A method for implementing the LESER strategy is constructed in the following steps: (i) clarification of the current situation; (ii) analysis of the root cause; (iii) improvement; (iv) evaluation of the carbon emissions; (v) sustaining and standardizing. Finally, the LESER strategy is applied to the Zcrubber Group Co. Ltd., which is characterized with high pollution, high energy consumption, and high emission in green transition. Results demonstrate practicability of the proposed strategy to offer an effective measure for promoting sustainability of manufacturing industry.