Decision support model for economical material carbon recovery and reduction by connecting supplier and disassembly part selections

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:サプライチェーンとリサイクルを統合したCO2削減モデルの新規性を評価できる。

🏢実務担当者:調達とリサイクル戦略を連携させた排出削減の意思決定に活用できる。

🏛政策担当者:サプライチェーン排出削減の政策設計に示唆を与える。

In the Internet of Things (IoT) era, manufacturers collect and share data to provide products that are more functional and less expensive. This embedded manufacturers to construct the global supply chain comprising suppliers, factories and recyclers to assemble products at a lower cost. On the other hand, global warming has become a serious environmental issue, and CO2 emissions on the global supply chain should be visualized and reduced by life cycle assessment. However, CO2 emissions vary for each country because of disparities in the energy mix. Therefore, manufacturers need to select appropriate suppliers for specific components, especially to ensure a lower procurement cost of parts and material-based GHG (GreenHouse Gas) emissions. Additionally, the economic model in the world shifts to circular economy which includes recycling the products economically because of the regenerative use for materials. If the parts inside the end-of-life (EOL) products are recycled, CO2 emissions in the procurement stage can be recovered with recycling cost. Therefore, recyclers need a disassembly part selection that selects recycling or disposal for each part in order to recover CO2 emission and reduce recycling cost in the EOL stage. Thus, certain product data, such as GreenHouse Gas (GHG) emissions and costs, needs to be shared with not only suppliers/factories but also recyclers by IoT technology on the global supply chain for connecting supplier and disassembly part selections. This study proposes a decision support model for economical carbon recovery by connecting supplier and disassembly part selections on procurement and EOL stages. First, a bill of materials (BOM) is prepared using an Asian supplier selection with the 3D-CAD model and Life Cycle Inventory (LCI) database. Second, disassembled parts of the EOL assembly products from the BOM data are selected for either recycling or disposal using 0-1 integer programming with ε constraint method. Finally, the results of the disassembly part selection, in terms of CO2 emission reduction and costs are discussed.

• openalex https://doi.org/10.1299/jamdsm.2020jamdsm0024first seen 2026-08-02 17:31:50