A Carbon Reduction-Oriented Synergistic Optimization Model for Manufacturing SAP Systems and Production Planning: Architectural Innovation, Algorithmic Advancement, and Global Industrial Validation

Qiang Fu
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Qiang Fu: Accenture (China) Co., Ltd, Shanghai 201201, China

Innovation in Science and Technology, 2025, vol. 4, issue 8, 29-37

Abstract: Manufacturing’s 35% share of global carbon emissions and the “dual carbon” goals (China: peak by 2030, neutrality by 2060) demand urgent integration of carbon reduction into production operations. However, two critical bottlenecks persist: carbon footprint accounting inaccuracy (average accuracy 0.05); (5) Average production cost increase limited to 2.3% (vs. 8.5% for single-objective carbon reduction methods). The model has been adopted by the Ministry of Ecology and Environment of China as a “Dual Carbon Digital Transformation Recommended Solution” and the International Iron and Steel Institute (IISI) as a global reference. It has been promoted in 68 enterprises, generating cumulative carbon reductions of 186,000 tons and cost savings of $124 million. Future integration of generative AI (e.g., GPT-4-based demand identification) is expected to further reduce maintenance costs by 25% and improve self-adaptation to industrial changes.

Keywords: carbon reduction; SAP system; production planning; synergistic optimization; carbon footprint accounting; multi-objective genetic algorithm; dynamic emission factors; manufacturing sustainability; global industrial validation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:bdz:inscte:v:4:y:2025:i:8:p:29-37

DOI: 10.63593/IST.2788-7030.2025.09.005

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