Remanufacturing - A manufacturing paradigm shift for deep decarbonization in a sustainable economy

再制造——可持续经济中深度脱碳的制造范式转变

• 批准号: 577125-2022
• 负责人: Jahed, HamidHR
• 金额: $ 36.41万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=760357
• 关键词: Remanufacturing; manufacturing; paradigm; shift; deep

Every stage of manufacturing, from raw materials extraction, refinement, and processing to part manufacturing contributes immensely to greenhouse gas (GHG) emissions. A shift toward re-manufacturing, where worn products or component parts are returned to like-new condition, will dramatically reduce anthropogenic GHG emissions caused by material production and distribution, help industries achieve stringent environmental mandates (net zero GHG by 2050), and contribute directly to a circular economy. The proposed project will connect expertise across mechanical and environmental engineering, computer science, supply chain and logistics, and climate change governance and sustainability to drive advances in the technologies needed for part assessment and remanufacturing, and generate data needed to build understanding and predictive models that capture the benefits of a remanufacturing-based decarbonization strategy and how it will impact policy. Specifically, the proposed research includes life assessment methodology for identifying damaged zones of parts at the end of their life, remanufacturing technology (cold spray additive manufacturing) to replace damaged parts, reverse logistics to design the optimum operation for accessing parts at the end of their life cycle and transferring them to local remanufacturers, assessment of GHG savings for one exemplar component, and forecast models that predict savings across different scenarios (e.g., for the automotive industry, we would forecast savings for exemplar components in all new cars manufactured by 2035, and 2050). A Transfer Learning algorithm will be employed to extend proposed methodology to other components. Policy barriers at federal, provincial, and municipal levels will be analyzed and mitigation strategies for sustainable transition to remanufacturing will be developed.The proposed strategy will significantly reduce GHG, provide exceptional economic opportunities for SME, and generate required data for decision makers to propose policies based on remanufacturing.

从原材料提取、精炼、加工到零件制造，制造的每个阶段都会产生巨大的温室气体 (GHG) 排放。向再制造的转变，将磨损的产品或零部件恢复到新的状态，将大大减少材料生产和分配引起的人为温室气体排放，帮助行业实现严格的环境要求（到 2050 年温室气体净零排放），并为直接走向循环经济。拟议的项目将连接机械和环境工程、计算机科学、供应链和物流以及气候变化治理和可持续性方面的专业知识，以推动零件评估和再制造所需技术的进步，并生成构建理解和预测模型所需的数据。了解基于再制造的脱碳战略的好处以及它将如何影响政策。具体来说，拟议的研究包括用于识别零件寿命结束时的损坏区域的寿命评估方法、用于更换损坏零件的再制造技术（冷喷涂增材制造）、逆向物流以设计在零件寿命结束时访问零件的最佳操作。生命周期并将其转移给当地再制造商，评估一个示例组件的温室气体节省量，以及预测不同场景下的温室气体节省量的预测模型（例如，对于汽车行业，我们将预测所有新车中示例组件的温室气体节省量）到 2035 年和 2050 年制造）。将采用迁移学习算法将提议的方法扩展到其他组件。将分析联邦、省和市各级的政策障碍，并制定可持续过渡到再制造的缓解策略。拟议的策略将显着减少温室气体，为中小企业提供特殊的经济机会，并为决策者提出政策建议提供所需的数据以再制造为基础。