Research Title
研究名称
Designing Sustainable Manufacturing Systems: A Systems Engineering Approach to Waste Reduction and Energy Conservation
设计可持续制造系统：减少废物和节能的系统工程方法
Introduction
介绍
Sustainable manufacturing has emerged as a cornerstone of modern industrial practices, driven by the urgent need to balance economic growth with environmental stewardship. As one of the world’s largest manufacturing hubs, China faces immense pressure to reduce waste and conserve energy across its industries. The integration of advanced technologies, such as Industry 4.0, and adherence to circular economy principles provide promising avenues for achieving these goals. However, the application of these strategies remains uneven, with substantial challenges in scalability and effectiveness. This research focuses on designing sustainable manufacturing systems that prioritize waste reduction and energy conservation in China. By addressing critical gaps in technological implementation, policy alignment, and systemic integration, this study aims to provide actionable insights for advancing sustainability. This approach not only aligns with global sustainability targets but also strengthens China’s industrial competitiveness, paving the way for environmentally and economically resilient manufacturing systems.
在平衡经济增长与环境管理的迫切需求的推动下，可持续制造已成为现代工业实践的基石。作为世界上最大的制造业中心之一，中国在各行各业减少浪费和节约能源方面面临着巨大压力。工业 4.0 等先进技术的整合以及对循环经济原则的坚持为实现这些目标提供了有希望的途径。然而，这些策略的应用仍然不均衡，在可扩展性和有效性方面存在重大挑战。本研究的重点是设计优先考虑中国减少废物和节能的可持续制造系统。通过解决技术实施、政策调整和系统整合方面的关键差距，本研究旨在为推进可持续发展提供可作的见解。这种方法不仅符合全球可持续发展目标，而且增强了中国的工业竞争力，为环境和经济弹性制造系统铺平了道路。
Background of Research
研究背景
Sustainable manufacturing systems represent an evolving framework designed to align industrial processes with environmental stewardship, particularly through waste reduction and energy conservation. The advent of smart manufacturing and Industry 4.0 technologies has transformed traditional practices, emphasizing energy efficiency and sustainability. These advancements are critical as global energy demand and resource consumption escalate, necessitating innovative approaches to mitigate environmental impacts. The transition from conventional manufacturing paradigms to sustainable systems underscores the integration of energy-efficient practices, zero-waste strategies, and advanced technologies to achieve ecological and economic goals simultaneously (Buzatu et al., 2021). The principles of frugal manufacturing have emerged as a pivotal element of sustainable systems. This approach minimizes material usage and energy consumption by optimizing production processes and leveraging technologies such as additive manufacturing and high-speed machining. These methods not only reduce waste but also enhance product integrity and cost efficiency, offering a holistic solution to sustainable development (Rao, 2021). Moreover, the deployment of cyber-physical systems in manufacturing has enabled real-time monitoring and optimization of energy use, fostering improvements in both efficiency and production planning (Matsunaga et al., 2022).
可持续制造系统代表了一个不断发展的框架，旨在使工业流程与环境管理保持一致，特别是通过减少废物和节约能源。智能制造和工业 4.0 技术的出现改变了传统做法，强调能源效率和可持续性。随着全球能源需求和资源消耗的不断升级，这些进步至关重要，因此需要创新方法来减轻对环境的影响。从传统制造范式到可持续系统的过渡强调了节能实践、零浪费战略和先进技术的整合，以同时实现生态和经济目标（Buzatu 等人，2021 年）。节俭制造的原则已成为可持续系统的关键要素。这种方法通过优化生产流程并利用增材制造和高速加工等技术，最大限度地减少材料使用和能源消耗。这些方法不仅可以减少浪费，还可以提高产品完整性和成本效率，为可持续发展提供整体解决方案（Rao，2021 年）。此外，在制造业中部署信息物理系统实现了能源使用的实时监控和优化，促进了效率和生产规划的改进（Matsunaga et al.， 2022）。
Advanced energy recovery systems also play a central role in the sustainable transformation of industries. For instance, integrating waste heat recovery mechanisms within manufacturing processes has demonstrated substantial reductions in energy consumption. In carbon fiber production, such systems have achieved energy efficiency improvements of up to 86%, significantly lowering carbon footprints (Khayyam et al., 2021). Similarly, renewable energy sources and circular economy principles have been integrated into manufacturing operations to address the dual objectives of waste reduction and resource optimization (Sharma et al., 2020). The adoption of zero-defect manufacturing strategies further underscores the systemic shift toward sustainability. These practices employ advanced modeling and monitoring tools to identify and eliminate inefficiencies at each stage of production, thereby minimizing waste and enhancing process reliability. The integration of semantic systems engineering frameworks has particularly enhanced precision in process industries, aligning operations with sustainable objectives (Cameron et al., 2022).
先进的能源回收系统在工业的可持续转型中也发挥着核心作用。例如，在制造过程中集成余热回收机制已证明可显著降低能耗。在碳纤维生产中，此类系统的能源效率提高了 86%，显著降低了碳足迹（Khayyam 等人，2021 年）。同样，可再生能源和循环经济原则已被整合到制造运营中，以实现减少废物和资源优化的双重目标（Sharma 等人，2020 年）。零缺陷制造战略的采用进一步强调了向可持续性的系统性转变。这些实践采用先进的建模和监控工具来识别和消除生产每个阶段的低效率问题，从而最大限度地减少浪费并提高流程可靠性。语义系统工程框架的集成特别提高了流程工业的精度，使运营与可持续目标保持一致（Cameron et al.， 2022）。
The synergy between sustainable design principles and advanced computational tools has also revolutionized material development. Computational approaches, including machine learning and materiomics, facilitate the creation of bioinspired materials with superior ecological profiles. These methods address the environmental challenges associated with traditional material extraction and production, promoting a transition toward greener alternatives (Shen et al., 2023). Sustainable supply chain models exemplify another dimension of progress, incorporating primary, secondary, and reverse chains to achieve near-zero waste systems. These integrated frameworks ensure that waste is converted into secondary or recycled products, thus closing the loop in material utilization (Iqbal et al., 2020). Holistic approaches to sustainable design, such as those employed in the building sector, offer further insights into cross-disciplinary integration. By implementing monitored energy management systems and renewable energy solutions, these designs achieve energy conservation while optimizing long-term operational efficiency (Buzatu et al., 2021).
可持续设计原则和高级计算工具之间的协同作用也彻底改变了材料开发。计算方法，包括机器学习和材料组学，有助于创建具有卓越生态特征的仿生材料。这些方法解决了与传统材料提取和生产相关的环境挑战，促进了向更环保替代品的过渡（Shen et al.， 2023）。可持续供应链模型体现了进步的另一个维度，它结合了一级、二级和反向链条，以实现近乎零的废物系统。这些集成框架确保废物转化为二次产品或回收产品，从而关闭材料利用的循环（Iqbal 等人，2020 年）。可持续设计的整体方法，例如建筑领域采用的方法，为跨学科整合提供了进一步的见解。通过实施受监控的能源管理系统和可再生能源解决方案，这些设计实现了节能，同时优化了长期运营效率（Buzatu et al.， 2021）。
The role of systemic integration in energy and ecological network analyses has gained prominence in quantifying sustainability. Such analyses provide a comprehensive understanding of resource efficiency and resilience, laying the groundwork for designing systems capable of mitigating environmental and operational disruptions (Hassan et al., 2023). Emerging trends in renewable integration and energy-efficient technologies point to a future where industrial systems are not only sustainable but also economically viable. These innovations underline the importance of continuous improvement and adaptation in the quest for a carbon-neutral industrial landscape (Ouyang et al., 2020). This rich tapestry of advancements underscores the necessity of a systems engineering approach to sustainable manufacturing, which harmonizes technological innovation, resource conservation, and ecological stewardship. By integrating these principles, industries are better positioned to address global sustainability challenges while achieving long-term economic and environmental objectives.
系统整合在能源和生态网络分析中的作用在量化可持续性方面越来越突出。此类分析提供了对资源效率和弹性的全面理解，为设计能够减轻环境和运营中断的系统奠定了基础（Hassan 等人，2023 年）。可再生能源并网和节能技术的新兴趋势表明，未来工业系统不仅具有可持续性，而且在经济上也是可行的。这些创新强调了持续改进和适应在寻求碳中和工业格局方面的重要性（Ouyang et al.， 2020）。这种丰富的进步强调了可持续制造采用系统工程方法的必要性，该方法将技术创新、资源保护和生态管理协调在一起。通过整合这些原则，各行各业可以更好地应对全球可持续发展挑战，同时实现长期的经济和环境目标。
Problem Statement
问题陈述
The increasing global demand for sustainable industrial practices has intensified the need to address critical gaps in waste reduction and energy conservation within manufacturing systems. While significant advancements have been made, several pressing issues remain unaddressed, limiting the potential for achieving truly sustainable manufacturing systems. This study identifies four key issues: ineffective waste management, insufficient integration of advanced technologies for energy efficiency, the need for comprehensive supply chain sustainability, and gaps in the circular economy's practical application.
全球对可持续工业实践的需求不断增长，这加剧了解决制造系统内减少废物和节能方面的关键差距的需求。虽然已经取得了重大进展，但一些紧迫的问题仍未得到解决，这限制了实现真正可持续制造系统的潜力。本研究确定了四个关键问题：无效的废物管理、能源效率先进技术整合不足、全面供应链可持续性的需求以及循环经济实际应用方面的差距。
Manufacturing industries generate a substantial amount of waste, much of which is inadequately managed, leading to severe environmental and economic repercussions. Recent data reveals that improper waste handling contributes significantly to pollution and resource inefficiency. For instance, the waste-to-energy nexus has shown potential for addressing these issues by integrating recycling and reuse strategies, yet its implementation remains limited in industrial contexts (Sharma et al., 2020). Additionally, the growing complexity of waste streams in modern manufacturing highlights the need for innovative solutions to manage waste effectively (Jibhakate et al., 2021). The lack of systematic frameworks for identifying and addressing waste sources within manufacturing processes represents a significant research gap.
制造业会产生大量废弃物，其中大部分管理不善，导致严重的环境和经济影响。最近的数据显示，废物处理不当是造成污染和资源效率低下的重要原因。例如，废物与能源的关系已显示出通过整合回收和再利用策略来解决这些问题的潜力，但其在工业环境中的实施仍然受到限制（Sharma 等人，2020 年）。此外，现代制造业中废物流日益复杂，凸显了对创新解决方案有效管理废物的需求（Jibhakate 等人，2021 年）。缺乏识别和解决制造过程中废物来源的系统框架是一个重大的研究空白。
Energy consumption in manufacturing is a primary driver of greenhouse gas emissions and climate change. While advancements in Industry 4.0 and cyber-physical systems offer pathways to optimize energy use, these technologies are not uniformly adopted across sectors. Research demonstrates that real-time monitoring and predictive modeling can enhance energy efficiency by reducing wasteful energy practices, yet their implementation is fragmented (Matsunaga et al., 2022). Furthermore, the potential of machine learning in predicting idle durations and optimizing energy consumption remains underexplored in manufacturing systems (Zhang et al., 2021). Addressing the gap in adopting these advanced technologies is critical to achieving substantial energy conservation.
制造业的能源消耗是温室气体排放和气候变化的主要驱动因素。虽然工业 4.0 和信息物理系统的进步为优化能源使用提供了途径，但这些技术并未在各个行业得到统一采用。研究表明，实时监测和预测建模可以通过减少浪费的能源做法来提高能源效率，但它们的实施是分散的（Matsunaga et al.， 2022）。此外，机器学习在预测空闲时间和优化能源消耗方面的潜力在制造系统中仍未得到充分探索（Zhang et al.， 2021）。解决采用这些先进技术的差距对于实现实质性节能至关重要。
The supply chain is an integral component of manufacturing systems, and its role in achieving sustainability cannot be overstated. Despite advancements in green supply chain management, challenges persist in aligning supply chain operations with zero-waste and energy-minimization goals. For instance, research highlights the potential for multi-layered supply chains to achieve near-zero waste, yet such models are not widely implemented due to logistical and technological barriers (Iqbal et al., 2020). Additionally, the integration of preservation technologies to minimize product degradation and waste remains an underexplored area (Yadav et al., 2021). This underscores the need for more comprehensive frameworks that incorporate both technological and operational strategies to enhance supply chain sustainability.
供应链是制造系统不可或缺的组成部分，它在实现可持续发展方面的作用怎么强调都不为过。尽管绿色供应链管理取得了进步，但在使供应链运营与零浪费和能源最小化目标保持一致方面仍然存在挑战。例如，研究强调了多层供应链实现近零浪费的潜力，但由于物流和技术障碍，此类模型并未得到广泛实施（Iqbal et al.， 2020）。此外，整合保鲜技术以最大限度地减少产品降解和浪费仍然是一个未被充分开发的领域（Yadav et al.， 2021）。这凸显了需要更全面的框架，将技术和运营战略相结合，以提高供应链的可持续性。
The circular economy aims to close resource loops through recycling, reuse, and recovery, yet its application in manufacturing systems faces numerous barriers. Although circular economy principles, such as those implemented in waste heat recovery, have demonstrated remarkable results in energy savings and carbon reduction, their adoption is not widespread (Khayyam et al., 2021). Moreover, the potential for integrating advanced technologies into circular processes, such as artificial intelligence for material tracking, remains largely untapped (Seferlis et al., 2021). Bridging this gap requires focused research on the systemic barriers to circular economy adoption and the development of scalable solutions.
循环经济旨在通过回收、再利用和再利用来闭合资源循环，但其在制造系统中的应用面临许多障碍。尽管循环经济原则（例如在余热回收中实施的原则）在节能和减碳方面取得了显着成果，但其采用并未得到广泛采用（Khayyam 等人，2021 年）。此外，将先进技术集成到循环流程中的潜力，例如用于材料跟踪的人工智能，在很大程度上仍未开发（Seferlis 等人，2021 年）。弥合这一差距需要重点研究采用循环经济的系统性障碍，并开发可扩展的解决方案。
Research Objectives
研究目标
How effective are advanced waste management strategies in reducing manufacturing waste?
先进的废物管理策略在减少制造废物方面效果如何？
What is the impact of Industry 4.0 technologies on energy conservation in manufacturing systems?
工业 4.0 技术对制造系统的节能有什么影响？
How do sustainable supply chain practices contribute to minimizing energy consumption across manufacturing networks?
可持续供应链实践如何有助于最大限度地减少整个制造网络的能源消耗？
What is the potential of circular economy principles in achieving waste reduction in manufacturing systems?
循环经济原则在实现制造系统减少浪费方面的潜力是什么？
Research Methodology
研究方法
Research Design
研究设计
This study employs a mixed-methods research design to comprehensively analyze the effectiveness of sustainable manufacturing systems in reducing waste and conserving energy in China’s industrial sector. The quantitative component involves collecting numerical data on waste generation, energy consumption, and system efficiency from manufacturing facilities, while the qualitative component includes interviews with industry professionals to explore the adoption of Industry 4.0 technologies and circular economy principles. This dual approach ensures robust findings by combining measurable outcomes with in-depth insights, enabling a holistic understanding of sustainability practices in the Chinese manufacturing context.
本研究采用混合方法研究设计，全面分析可持续制造系统在减少中国工业部门浪费和节约能源方面的有效性。定量部分涉及从制造设施收集有关废物产生、能源消耗和系统效率的数值数据，而定性部分包括与行业专业人士的访谈，以探索工业 4.0 技术和循环经济原则的采用。这种双重方法通过将可衡量的结果与深入的见解相结合，确保获得可靠的发现，从而全面了解中国制造业的可持续发展实践。
Population and Sampling
总体和抽样
The target population for this study comprises manufacturing firms in China, specifically those operating in energy-intensive industries such as steel, textiles, and electronics. A purposive sampling strategy will be used to select 50 companies that have implemented or are in the process of adopting sustainable practices. These firms are chosen based on their geographic distribution across industrial hubs such as Guangdong, Jiangsu, and Shandong provinces, as well as their documented efforts in waste reduction and energy conservation. Key informants within these companies, including sustainability managers and production engineers, will be engaged for qualitative insights, while facility-level data on waste and energy metrics will be collected for quantitative analysis.
本研究的目标人群包括中国的制造企业，特别是那些在钢铁、纺织和电子等能源密集型行业运营的公司。将采用有目的的抽样策略来选择 50 家已经实施或正在采用可持续实践的公司。这些公司的选择是基于它们在广东、江苏和山东省等工业中心的地理分布，以及它们在减少废物和节能方面的记录努力。这些公司的关键信息提供者，包括可持续发展经理和生产工程师，将参与进行定性洞察，同时收集设施层面的废物和能源指标数据进行定量分析。
Instrumentation
仪表
Data collection will rely on a combination of standardized survey instruments, semi-structured interview protocols, and facility-level operational records. Surveys will measure key indicators of waste management and energy conservation using validated scales. Interview protocols will include open-ended questions to explore challenges and opportunities in implementing Industry 4.0 and circular economy strategies. Facility records, such as waste logs and energy consumption reports, will provide quantitative data. These instruments are designed to ensure reliability and validity while capturing both systemic metrics and stakeholder perspectives.
数据收集将依赖于标准化调查工具、半结构化访谈协议和设施级作记录的组合。调查将使用经过验证的量表来衡量废物管理和节能的关键指标。访谈协议将包括开放式问题，以探索实施工业 4.0 和循环经济战略的挑战和机遇。设施记录（例如废物日志和能源消耗报告）将提供定量数据。这些工具旨在确保可靠性和有效性，同时捕获系统指标和利益相关者的观点。
Data Collection
数据采集
Data collection will occur in two phases over three months. In the first phase, surveys will be distributed electronically to sustainability managers in the selected firms, followed by follow-up calls to ensure a high response rate. In parallel, facility records will be requested for quantitative analysis, focusing on waste volumes, energy use, and efficiency indicators over the past five years. In the second phase, semi-structured interviews will be conducted with key informants, either in person or virtually, depending on location and availability. All interviews will be audio-recorded and transcribed for thematic analysis.
数据收集将在三个月内分两个阶段进行。在第一阶段，调查将以电子方式分发给选定公司的可持续发展经理，然后进行后续电话跟进，以确保高回复率。同时，将要求提供设施记录进行定量分析，重点关注过去五年的废物量、能源使用和效率指标。在第二阶段，将根据地点和可用性，与关键线人进行面对面或虚拟的半结构化访谈。所有访谈都将进行录音和转录以进行主题分析。
Data Analysis
数据分析
Quantitative data will be analyzed using statistical techniques, including descriptive statistics, regression analysis, and ANOVA, to identify patterns and relationships between sustainable practices and reductions in waste and energy consumption. Facility data will be benchmarked against industry standards to evaluate performance. Qualitative data from interviews will undergo thematic analysis to uncover common
将使用统计技术（包括描述性统计、回归分析和方差分析）分析定量数据，以确定可持续实践与减少浪费和能源消耗之间的模式和关系。工厂数据将根据行业标准进行基准测试，以评估性能。访谈的定性数据将进行主题分析，以发现共同的
Research Significance
研究意义
The significance of this study lies in its potential to address critical environmental and operational challenges in manufacturing systems by advancing strategies for waste reduction and energy conservation. As global industrial activities continue to grow, the environmental consequences of waste generation and excessive energy use threaten ecological balance and resource availability. This research aims to provide actionable insights into designing sustainable manufacturing systems, aligning industrial practices with global sustainability goals.
这项研究的意义在于它有可能通过推进减少废物和节能的策略来解决制造系统中的关键环境和运营挑战。随着全球工业活动的持续增长，废物产生和过度能源使用对环境的影响威胁着生态平衡和资源可用性。本研究旨在为设计可持续制造系统提供可作的见解，使工业实践与全球可持续发展目标保持一致。
By evaluating advanced waste management strategies, the study contributes to reducing industrial waste and mitigating its adverse environmental effects. Such strategies are vital for industries striving to achieve zero-waste systems, aligning with international sustainability targets such as the United Nations’ Sustainable Development Goals (SDGs). Furthermore, the integration of Industry 4.0 technologies, such as cyber-physical systems and real-time energy monitoring, offers transformative potential for energy conservation. This study’s findings will empower industries to optimize resource utilization, reduce operational costs, and minimize carbon footprints, contributing to the global transition toward energy-efficient production.
通过评估先进的废物管理策略，该研究有助于减少工业废物并减轻其对环境的不利影响。此类策略对于努力实现零废物系统的行业至关重要，与联合国可持续发展目标 （SDG） 等国际可持续发展目标保持一致。此外，工业 4.0 技术的集成，如信息物理系统和实时能源监控，为节能提供了变革性的潜力。这项研究的结果将使行业能够优化资源利用、降低运营成本并最大限度地减少碳足迹，从而促进全球向节能生产过渡。
In exploring sustainable supply chain practices, the study addresses the broader industrial ecosystem, emphasizing the interconnectedness of supply chain decisions with environmental and energy outcomes. Insights derived from this research will guide industries in adopting holistic approaches that enhance supply chain sustainability while maintaining economic competitiveness. The focus on circular economy principles fosters the rethinking of resource flows, promoting recycling, reuse, and recovery. By demonstrating the feasibility of circular manufacturing processes, this research offers a roadmap for industries seeking to implement regenerative practices.
在探索可持续供应链实践的过程中，该研究涉及更广泛的工业生态系统，强调供应链决策与环境和能源成果的相互关联性。从这项研究中得出的见解将指导行业采用整体方法，在保持经济竞争力的同时增强供应链的可持续性。对循环经济原则的关注促进了对资源流动的重新思考，促进了回收、再利用和恢复。通过证明循环制造工艺的可行性，本研究为寻求实施再生实践的行业提供了路线图。
Literature Review
文献综述
Li et al. (2020) explored the role of green innovation in China’s energy-intensive manufacturing sector, emphasizing the dimensions of product innovation, recycling, and publicity. They found significant links between these innovations and environmental, social, and financial sustainability. However, their study did not extensively address how systemic waste reduction can be scaled across diverse manufacturing sub-sectors. This highlights a gap in understanding the broad applicability of these green practices, especially in regions with varying industrial capacities. Wang et al. (2020) analyzed the energy conservation potential of solid waste recycling in China, revealing a 12.29% reduction in energy consumption and an 8.46% reduction in CO2 emissions through optimized recycling processes. While these findings underscore the environmental benefits of recycling, the study mainly focuses on municipal solid waste, leaving a critical gap in addressing industrial waste streams and their integration into circular manufacturing models.
Li et al. （2020） 探讨了绿色创新在中国能源密集型制造业中的作用，强调了产品创新、回收和宣传的维度。他们发现这些创新与环境、社会和财务可持续性之间存在重要联系。然而，他们的研究并没有广泛地解决如何在不同的制造业子行业中扩展系统性减少废物的问题。这凸显了对这些绿色实践的广泛适用性的理解存在差距，尤其是在工业能力不同的地区。Wang et al. （2020） 分析了中国固体废物回收的节能潜力，发现通过优化回收工艺，能源消耗减少了 12.29%，二氧化碳排放量减少了 8.46%。虽然这些发现强调了回收利用的环境效益，但该研究主要集中在城市固体废物上，在解决工业废物流及其整合到循环制造模式方面留下了关键差距。
Joensuu et al. (2020) emphasized circular economy practices in urban settings, identifying management strategies for waste prevention and resource recovery. Their review suggests that urban-industrial symbiosis could drive sustainability but notes a lack of effective cross-sectoral frameworks to extend these strategies to manufacturing. This gap underscores the need for research into how urban and industrial systems can collaboratively address waste reduction within China's manufacturing context. Cheng et al. (2020) studied the impact of research and development (R&D) on energy conservation in eastern China’s manufacturing sector, predicting a reduction of 1066.28 million tons of coal equivalent energy use by 2025 under advanced innovation scenarios. While the findings underscore R&D's transformative potential, the study does not address how these innovations can be effectively transferred to less developed industrial regions, posing a barrier to widespread implementation.
Joensuu 等人（2020 年）强调了城市环境中的循环经济实践，确定了预防废物和资源回收的管理策略。他们的综述表明，城市-工业共生可以推动可持续性，但指出缺乏有效的跨部门框架来将这些策略扩展到制造业。这一差距凸显了研究城市和工业系统如何在中国制造业环境中协同解决减少废物问题的必要性。Cheng et al. （2020） 研究了中国东部制造业研发 （R&D） 对节能的影响，预测在先进创新情景下，到 2025 年将减少 10.6628 亿吨煤炭当量能源使用。虽然研究结果强调了研发的变革潜力，但该研究并未解决如何将这些创新有效地转移到欠发达的工业区域，从而对广泛实施构成障碍。
Liu et al. (2021) examined the effects of environmental regulation on green technological progress in China, finding a threshold effect where moderate regulation fosters innovation while excessive regulation stifles progress. This nuanced understanding of policy impacts is critical but does not delve deeply into how regulations can be tailored to balance innovation and practical waste reduction strategies within manufacturing. Zhang et al. (2020) demonstrated the potential of anaerobic digestion technology to halve greenhouse gas emissions from food waste treatment by 2040. While the study focuses on municipal food waste, it highlights the untapped potential for applying similar energy recovery technologies in industrial waste contexts, which could significantly contribute to sustainable manufacturing systems.
Liu 等人（2021 年）研究了环境监管对中国绿色技术进步的影响，发现了阈值效应，即适度监管促进创新，而过度监管扼杀进步。这种对政策影响的细致入微的理解至关重要，但并未深入研究如何定制法规以平衡制造业中的创新和实际减少浪费策略。Zhang 等人（2020 年）证明了厌氧消化技术到 2040 年将食物垃圾处理的温室气体排放量减半的潜力。虽然该研究侧重于城市食物垃圾，但它强调了在工业垃圾环境中应用类似能源回收技术的未开发潜力，这可能会为可持续制造系统做出重大贡献。
Yalçıntaş et al. (2023) conducted a bibliometric analysis on sustainable waste management, revealing China’s leadership in research output but a persistent gap in actionable frameworks for industrial applications. This indicates a disconnect between academic advancements and practical implementation in manufacturing environments, necessitating studies that bridge this divide. Sasmoko et al. (2022) examined bio-waste recycling’s role in supporting circular economies, finding significant reductions in emissions when integrated into industrial processes. However, their study underscores the challenges of scaling such initiatives in rapidly industrializing economies like China, where inconsistent recycling infrastructures hinder comprehensive adoption.
Yalçıntaş et al. （2023） 对可持续废物管理进行了文献计量分析，揭示了中国在研究产出方面的领导地位，但在工业应用的可作框架方面仍然存在差距。这表明学术进步与制造环境中的实际实施之间存在脱节，因此需要研究来弥合这一鸿沟。Sasmoko 等人（2022 年）研究了生物废物回收在支持循环经济方面的作用，发现当整合到工业流程中时，排放量会显着减少。然而，他们的研究强调了在像中国这样快速工业化的经济体中推广此类举措所面临的挑战，这些经济体不一致的回收基础设施阻碍了全面采用。