Supplementary data for multi-objective decision support for cost–carbon–process-hour trade-offs in prefabricated cold-formed steel residential framing
プレハブ冷間成形鋼住宅フレーミングにおけるコスト・炭素・プロセス時間のトレードオフのための多目的意思決定支援の補足データ (AI 翻訳)
Kevin Ramani, J H Lim, Kris Roy, Arthur Fang, Humaira Hameed, Shanika Raigamage
🤖 gxceed AI 要約
日本語
本研究は、ニュージーランドの事例を用いて、プレハブ鋼住宅フレーミングにおけるコスト、炭素排出量、プロセス時間の多目的最適化フレームワークを提供する。補足データには、モデル、診断、パレート解が含まれる。
English
This study provides a multi-objective optimization framework for cost, carbon emissions, and process hours in prefabricated steel residential framing, using a New Zealand case study. The supplementary data includes models, diagnostics, and Pareto solutions.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
ニュージーランドの事例だが、日本でもプレハブ住宅のコスト・炭素最適化に応用可能。SSBJや建設業の脱炭素施策の参考になる。
In the global GX context
This case study from New Zealand adds to the global body of evidence on cost-carbon trade-offs in prefabricated construction, relevant for TCFD/ISSB-aligned disclosure in the building sector.
👥 読者別の含意
🔬研究者:Researchers can leverage the multi-objective optimization methodology for similar studies in other regions or materials.
🏢実務担当者:Construction firms can use the framework to benchmark cost and carbon performance in prefab designs.
🏛政策担当者:Policymakers may consider incorporating such trade-off analyses into building codes or green procurement guidelines.
📄 Abstract（原文）
This Zenodo record contains supplementary material and processed data supporting the manuscript titled “Multi-objective decision support for cost–carbon–process-hour trade-offs in prefabricated cold-formed steel residential framing: A single-case study from New Zealand”. The archive includes the response-model formulation, coefficient audit, uncertainty-range rationale, optimisation settings, convergence diagnostics, grid-reference comparison, OC-fixed diagnostic, sensitivity outputs, processed case-study inputs, final nondominated archive, representative Pareto solutions, Monte Carlo robustness outputs, TOPSIS ranking outputs and dashboard export fields. The interactive dashboard is provided as a visualisation and shortlisting interface for the released processed outputs. The full Python analysis code is not publicly released because it contains project-specific data-processing, calibration and internal workflow scripts associated with the case-study framing package. Project-identifying and commercially sensitive information has been removed where required.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.5281/zenodo.21090108first seen 2026-07-03 04:59:41
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gxceed は公開メタデータに基づく研究支援データセットです。要約・翻訳・解説は AI 支援で生成されています。 最終的な解釈・検証は利用者が原典資料に基づいて行うことを前提とします。