農業用運搬車両製造会社におけるカーボンフットプリント削減のための生産スケジューリング手法：ウッタラディット県の事例研究
AN APPROACH TO PRODUCTION SCHEDULING FOR REDUCING CARBON FOOTPRINT IN AN AGRICULTURAL TRANSPORT VEHICLE MANUFACTURING COMPANY: A CASE STUDY IN UTTARADIT PROVINCE (原題)
Chatchaphon Ketviriyakit, Adul Phuk-in
🤖 gxceed AI 要約
日本語
タイの農業用車両メーカーを対象に、生産スケジューリングの数理モデルを構築し、総生産時間（メイクスパン）と製品カーボンフットプリント（CFP）の同時最小化を試みた。局所探索ヒューリスティックを用いて最適スケジュールを算出し、小・中・大規模の問題で有効性を検証。大規模事例では生産時間を約24日短縮し、CFPを497.759 kg CO2e削減、効率を28.89%改善した。
English
This study develops a mathematical model for production scheduling at an agricultural vehicle manufacturer in Thailand, aiming to minimize makespan and product carbon footprint (CFP). Using a local search heuristic, the model was validated across small, medium, and large problem sizes. In the large-scale case, production time was reduced by about 24 days, CFP by 497.759 kg CO2e, and efficiency improved by 28.89%.
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、生産計画とカーボンフットプリントの統合最適化は、省エネ法やGXリーグの排出削減要請に対応する実務的関心が高い。本手法は中小製造業の生産現場で適用可能な簡便なモデルであり、日本企業の生産管理システムへの組み込みが期待される。
In the global GX context
Globally, integrating carbon footprint considerations into production scheduling is an emerging practice aligned with ISO 14067 and supply chain decarbonization. This case study from Thailand provides a practical example for manufacturers in emerging economies to reduce emissions without significant capital investment, contributing to the broader discourse on operational decarbonization.
👥 読者別の含意
🔬研究者:Provides a concrete model for joint optimization of makespan and carbon footprint, useful for extending to multi-objective scheduling research.
🏢実務担当者:Offers a practical approach to reduce production time and carbon emissions simultaneously, applicable to manufacturing operations.
🏛政策担当者:Demonstrates that operational efficiency measures can yield significant emission reductions, supporting policies that encourage such optimizations.
📄 Abstract（原文）
This study investigates a production scheduling problem for an agricultural vehicle manufacturer in Uttaradit Province. The primary goal is to generate an improved production schedule using a mathematical model. The model is designed to minimize the total time taken to produce an entire product known as make span, while also tracking the environmental impact, or product carbon footprint (CFP), during the production of each part. A computer program was created and a local search heuristic was used to find the optimal schedule. The data was obtained from customer orders and the company's production and maintenance teams. It included information such as the number of machines they had, how long each machine needed to set up, how long each product needed to produce, how much electricity they used, how much waste they generated, and the rules and constraints they imposed on production. The production scheduling problem was divided into three levels: small, medium, and large, allowing for the determination of the optimal schedule for each scenario. The results show that the mathematical model performs well on all problem sizes. For example, in the small-scale case with six jobs and seven machines, the model took 6,961.23 minutes to compute, which took only 0.214 seconds for all machines to be fully utilized, and the CFP was 91.791 kg of CO2 equivalent. In contrast, the company's original large-scale schedule took 38,561.12 minutes, or approximately 81 working days, at an 8-hour workday. However, with the revised schedule, the time was reduced to 26,365.22 minutes, or approximately 57 working days, a saving of 24 days. Using this mathematical model, the total production time was reduced by 11,139.94 minutes, efficiency was improved by 28.89%, and CFP was reduced by 497.759 kilograms of carbon dioxide equivalent, successfully achieving the main goal of the research.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.55766/sujst11901first seen 2026-09-03 05:17:47
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