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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 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. [ABSTRACT FROM AUTHOR]

Multi-scale defect features, blurred edges and inability to locate geometric features have been the three key factors limiting the detection of surface defects on quality control system in the industrial manufacturing process. In this study, a method based on the fusion of multi-scale features and pixel-level semantic segmentation is proposed for the detection of surface defects. The proposed method firstly fuses multi-level feature maps to balance the expressiveness of multi-scale features, then adds a boundary refinement module to enhance the accurate inference of edge fine-grained, and finally adopts an en-decoder architecture to locate geometric features at the pixel-level for each type of defects, realizing intelligent detection of geometric features of end-to-end multi-scale defects on the surface of parts. We conduct experiments using the collected parts datasets to evaluate the effectiveness of our framework. The experimental results show that the proposed model achieves MIoU of 80.1%, the recognition accuracy reaches more than 95 %, and a detection rate of up to 29.64 FPS, demonstrating the advancement and effectiveness of the proposed method with less misclassification and superior generalization performance and has progress and effectiveness in detecting surface defects of multi-scale features. It provides a research idea for the subsequent realization of surface quality inspection in the manufacturing process system. [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]

Additive manufacturing (AM) technologies, such as direct laser and selective laser melting (SLM) manufacturing, allow the fabrication of functional products with high added value. This paper proposes an emergy-based method for evaluating the environmental impact and economic cost of the SLM manufacturing process while considering the environmental flows (materials, energy, and wastes) and economic factors (time, costs, and quality). By analyzing the emergy flows in an SLM system, sustainable evaluation indexes are developed to estimate its sustainability level. Then, the method is applied to analyze the environmental impact and economic cost of the SLM of a part. The results show that the cost of the process for a single part is high, the net emergy yield ratio of the SLM system is low, and its environmental load rate is very high. The sustainability indexes of the system indicated a high environmental impact and low production efficiency. However, the waste emergy output ratio of the system was very low, which reflected the near-net-shape characteristics of SLM, indicating a high sustainability potential. The results of this study are expected to contribute to increased sustainability and optimization of SLM. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM) can be used to fabricate products with complex shapes that cannot be realized with traditional manufacturing. However, when manufacturing large metal components, AM is constrained by extended production cycles and reduced efficiency, leading to substantial resource usage and environmental impacts. To clarify the environmental impact and sustainability (EIS) of AM systems and improve their resource utilization and economic benefits, an emergy-based approach was proposed. Initially, the scope and boundary of the approach are defined, and the methodology and preparatory steps are detailed. Subsequently, emergy models for sustainability evaluation are established, including factors such as production time, quality, resource use, costs, and economic performance. A comprehensive evaluation is conducted to determine the relevant indices. The results of the evaluation of three distinct AM processes reveal that resource and energy utilization in AM systems contribute approximately 50% of the environmental impact. To mitigate the environmental impact of AM systems and improve their sustainability, reducing the energy consumption of AM systems is indicated as an effective strategy. Our method quantitatively evaluates the EIS of AM, providing a basis for informed decision-making to reduce environmental impact while enhancing production efficiency and economic benefits. • Emergy-based method to assess sustainability of additive manufacturing (AM) proposed. • It provides a unified model for the integration of quality, cost, time, energy, and materials. • It unifies different performance index measures of AM systems. • A comprehensive evaluation of different AM processes was conducted. • It provides an analytical basis for a circular economy. [ABSTRACT FROM AUTHOR]

An energy-saving and environment-friendly manufacturing process is essential to address the large energy and resource consumption in manufacturing. Sheet metal forming is an important manufacturing process and is widely used in automobile and aviation industries. Sheet metal forming is also an energy-intensive process in manufacturing and consumes a large amount of energy because of its low energy efficiency. In this study, a comprehensive energy-saving method was proposed to reduce the energy consumption and improve the energy efficiency of sheet metal forming. On the basis of the developed process energy models of sheet metal forming, a novel process optimization method was proposed to reduce the process energy consumption of metal forming parts without sacrificing their forming quality. The proposed process optimization method was melded with previous energy-matching control method of forming equipment to further decrease the energy consumption in sheet metal forming. The comprehensive energy-saving method for sheet metal forming was integrally applied to a stamping process chain. Results show that the energy consumption can be decreased by 37% compared with the original stamping process chain. Therefore, the proposed method shows significant energy-saving potential. [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]

The Internet of Things (IoT) has a significant effect on the development of manufacturing technology. Therefore, according to the analysis of the challenges and opportunities faced by manufacturing industry, this study uses the assembly process of mechanical products as the research object and analyzes the characteristics of IoT-based manufacturing systems. To improve the interconnection, perception, efficiency, and intelligence of the assembly system, this study proposes the concept of IoT-enabled intelligent assembly system for mechanical products (IIASMP). The IIASMP framework, which is based on advanced techniques such as information and communication technology, sensor network, and radio-frequency identification, is then presented. Key technologies under this framework, including assembly resources identification, information interaction technology, multi-source data perception and fusion, intelligent assembly agent, and value-added data and dynamic self-adaptive optimization, are described. Finally, the current results of IIASMP are described in the case study. The proposed framework and methods aims to have an important reference value for applying the key technologies and be used widely in the intelligent manufacturing field. [ABSTRACT FROM AUTHOR]

Limited by techniques, the process of remanufacturing exists masses of uncertainties which have a great impact on the remanufactured parts quality, how to achieve a higher quality of mechanical products by using limited remanufactured parts precision, has become one of the key issues of remanufacturing industry. Firstly, with a target to reduce uncertainties and improve the quality of automatic products, a method of tolerance grading allocation for remanufactured parts is proposed based on the uncertainty analysis of the remanufacturing assembly. The dimensional tolerances of the mechanical parts are divided into positive and negative two groups. We use selective assembly method to reduce assembling deviation. Then, the method is proven by mathematical formulas that the remanufactured parts variance can be expanded to two times, and the tolerances can be liberalized 40 % through tolerance grading allocation method. It is also the theoretical basis for improving the reuse radio and quantitatively describing the tolerance liberalization in this paper. Finally, feasibility research on this method is studied from the angle of cost-benefit. Furthermore, a tolerance grading allocation example of remanufactured engine piston assembly in a power corporation shows the validity and practicality of the proposed method. [ABSTRACT FROM AUTHOR]

Numerous pathways and narratives have been developed to shed light on how society could transform its production systems in line with the aspirational targets of the Paris Agreement and Sustainable Development Goals. Zhang et al. [[10]] address a coincineration scheme for mixing multi-component wastes in a rotary kiln for waste disposal from pesticide production. Zhang et al. [[4]] present a literature review on reverse logistics (RL) supplier selection in terms of criteria and methods and propose a three-stage typology of decision-making frameworks to understanding RL supplier selection. This Special Issue on "Green Technologies for Production Processes" will focus on publishing original research works about Green Technologies for Production Processes, including discrete production processes and process production processes, from various aspects that tackle product, process, and system issues in production. [Extracted from the article]

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]

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]

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]