材料提案機能を持つ温室効果ガスと調達コストの意思決定支援ツール開発
書誌事項
- タイトル別名
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- Development of a Decision Support Tool for GHG Emissions and Procurement Costs with Material Recommendation
説明
<p>Manufacturing has been required to reduce greenhouse gases (GHG) to deal with global warming. GHG emissions and procurement costs for a virgin material production depend on not only material types and weight determined at a product design phase but also manufactured countries because of its energy mix of the electric power. Then, product designers with multiple of design considerations need to take into account of both GHG emissions and procurement cost in selecting types of materials for each part. To visualize GHG emissions and procurement costs, an estimation method based on life cycle inventory (LCI) database with the Asian International Input-Output Table has been developed. However, the estimation method often causes longer estimation time and errors for inputting data throughout the estimation processes because the method requires to refer to several different databases manually. This study focuses on assembly products/materials produced in 9 countries including Japan, and develops a decision support tool for GHG emissions and procurement costs with material recommendation by the LCI database using Asian International Input-Output Table. The developed tool enables to estimate GHG emissions and procurement cost simultaneously and automatically for each part by only inputting its material type and weight. Moreover, the material recommendation function suggests alternative materials based on reduction targets of GHG emissions and procurement costs. First, LCI database is introduced to estimate GHG emissions and procurement costs. Next, it is described processes of automatic calculation in the developed tool and recommendation function for GHG emissions and procurement costs. Finally, user tests are conducted to validate the developed tool.</p>
収録刊行物
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- 設計工学
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設計工学 55 (4), 277-294, 2020
公益社団法人 日本設計工学会
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キーワード
詳細情報 詳細情報について
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- CRID
- 1390283659869205504
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- NII論文ID
- 130007828923
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- ISSN
- 21889023
- 09192948
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- CiNii Articles
- KAKEN
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- 抄録ライセンスフラグ
- 使用不可
