持続可能な産業生産システムにおける信頼性中心保全と再生可能エネルギー調整のための統合意思決定フレームワーク
An Integrated Decision Framework for Reliability-Centered Maintenance and Renewable Energy Coordination in Sustainable Industrial Production Systems (原題)
Rohan SI
🤖 gxceed AI 要約
日本語
本研究は、信頼性中心保全（RCM）と再生可能エネルギー配分を統合した意思決定フレームワークを提案。エネルギー集約型製造施設のケーススタディで、年間コスト16.6%削減、炭素排出19.8%削減、計画外停止43.8%削減、再生可能エネルギー利用率26.1%向上を実証。多目的最適化とMCDMを用い、コスト・信頼性・持続可能性のトレードオフを評価する実践的ツールを提供。
English
This study proposes an integrated decision framework combining reliability-centered maintenance (RCM) and renewable energy dispatch. A case study of an energy-intensive manufacturing facility demonstrates 16.6% annual cost reduction, 19.8% lower carbon emissions, 43.8% reduction in unplanned downtime, and 26.1% increase in renewable energy utilization. Using multi-objective optimization and MCDM, it provides a practical tool for evaluating trade-offs among cost, reliability, and sustainability.
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
日本の製造業では、再エネ導入と設備保全の統合はSSBJ開示やカーボンニュートラル目標達成に直結。本フレームワークは、コスト削減と排出削減を同時に実現する実証データを提供し、投資家対応や統合報告書での活用が期待される。
In the global GX context
Globally, this framework addresses the integration of renewable energy and maintenance optimization, a key challenge for industrial decarbonization. It provides empirical evidence on cost and emission reductions, relevant for companies aligning with TCFD/ISSB disclosures and transition finance criteria.
👥 読者別の含意
🔬研究者:Provides a novel integrated optimization model for maintenance and renewable energy coordination, with quantitative results.
🏢実務担当者:Offers a practical decision tool for manufacturing facilities to reduce costs and emissions while improving reliability.
🏛政策担当者:Demonstrates potential for industrial energy efficiency and emission reductions, informing policy on renewable integration.
📄 Abstract（原文）
This research develops an Integrated Decision Framework for Reliability-Centered Maintenance and Renewable Energy Coordination (IDF-RCM-REC) to support sustainable industrial production under energy uncertainty. The study addresses the lack of unified models that jointly optimize maintenance policies and renewable energy dispatch, which currently leads to suboptimal reliability, cost, and sustainability outcomes. A multi-objective optimization framework integrating RCM-based reliability modeling, stochastic renewable energy coordination, and MCDM-guided solution selection is formulated and validated through a case study of an energy-intensive manufacturing facility. Results show a 16.6% reduction in total annual cost, 19.8% lower carbon emissions, 43.8% reduction in unplanned downtime, and a 26.1% increase in renewable energy utilization, alongside a shift toward predictive and condition-based maintenance strategies. The framework enables decision makers to evaluate trade-offs between cost, reliability, and sustainability and to select strategies aligned with organizational objectives. This work provides a practical, mathematically grounded tool for aligning maintenance and energy management in renewable-integrated industrial systems, advancing both theoretical understanding and operational practice in sustainable production.
🔗 Provenance — このレコードを発見したソース
- Research Square https://doi.org/10.20944/preprints202608.1285.v1first seen 2026-08-22 04:24:06 · last seen 2026-09-02 04:34:40
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