Research on AI-Driven Production Decision-Making in the Manufacturing Industry

Fangyu Zhao (), Shuo Han (), Rui Li () and Zelin Lu ()
Additional contact information
Fangyu Zhao: China Academy of Industrial Internet
Shuo Han: Beijing University of Posts and Telecommunications
Rui Li: China Academy of Industrial Internet
Zelin Lu: China Mobile Communication Co., Ltd.

A chapter in Proceedings of the 2026 6th International Conference on Enterprise Management and Economic Development (ICEMED 2026), 2026, pp 293-305 from Springer

Abstract: Abstract Against the backdrop of the deep integration of artificial intelligence (AI) and the real economy, production decision-making in the manufacturing industry is transforming from traditional experience-driven to data intelligence-driven, and the application value of AI in this process is becoming increasingly prominent. Focusing on the optimization of manufacturing costs, this paper explores the cost optimization-driven path of AI empowering production decision-making. By sorting out the current application status of AI in manufacturing production, analyzing the limitations of the traditional experiential learning curve and capacity utilization models, and combining a business simulation case of a multinational mobile phone manufacturer, this paper constructs an AI-driven manufacturing cost optimization model that integrates the learning curve effect and the capacity utilization effect. It systematically analyzes the specific paths of AI empowering manufacturing production decision-making from three dimensions: cost prediction, capacity planning, and make-or-buy decision-making, and verifies the practical application value of the model through case application. Finally, it points out the shortcomings of the research and prospects the future research directions of AI empowering manufacturing production decision-making.

Keywords: Artificial Intelligence; Manufacturing Cost Optimization; Production Decision-Making; Learning Curve (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:advbcp:978-94-6239-719-4_34

Ordering information: This item can be ordered from
http://www.springer.com/9789462397194

DOI: 10.2991/978-94-6239-719-4_34

Access Statistics for this chapter

More chapters in Advances in Economics, Business and Management Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().