Study of Decision-Making Problems in the Production Process

Tian Qin (), Jiabao Lv (), Mingyu Cao () and Fang He ()
Additional contact information
Tian Qin: Shenzhen Technology University, College of Integrated Circuits and Optoelectroinc Chips
Jiabao Lv: Shenzhen Technology University, College of Integrated Circuits and Optoelectroinc Chips
Mingyu Cao: Shenzhen Technology University, College of Integrated Circuits and Optoelectroinc Chips
Fang He: Shenzhen Technology University, College of Big Data and Internet

A chapter in Proceedings of the 2025 5th International Conference on Enterprise Management and Economic Development (ICEMED 2025), 2025, pp 492-509 from Springer

Abstract: Abstract In this paper, the decision strategy under different scenarios is studied for the decision choice problem of manufacturing enterprises in the production process. The study aims to help improve the operational efficiency and agility of enterprises through the specific analysis of the decision-making problem in the production process to provide enterprises with feasible decision support tools, improve production efficiency and resource utilization, and help intelligent manufacturing upgrade. As in the production process, the spare parts used and the synthesized finished product may be defective, and defective products to the hands of the user will have to pay a certain amount of compensation or even reduce the credibility of the enterprise. At the same time, if you choose to test the spare parts and finished products also need to pay a certain amount of testing costs. Therefore, how to better find the most profitable decision has become a major problem. In order to solve these problems, this paper divides the production situation into two categories: single process and two spare parts, and multiple processes and multiple spare parts, and assumes specific values such as product failure rate and spare part cost. In the case of single process and two spare parts, this paper constructs a decision tree model and a cost effectiveness model, and solves them by Monte Carlo (MC) simulation. In the case of multi-process and multi-part production, the production process is too complex and high-dimensional when the MC simulation method requires a large number of samples, which usually shows a lower efficiency, so we use the Slime mold algorithm (SMA) to produce results more efficiently. After experiments with specific numerical settings, it is shown that the proposed model can produce good results in many cases. This not only helps to improve the operational efficiency and agility of enterprises, but also has strategic significance in promoting the digital transformation of the manufacturing industry and realizing sustainable development.

Keywords: decision-making problem; cost effectiveness model; Monte Carlo; Slime mold algorithm (search for similar items in EconPapers)
Date: 2025
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:978-94-6463-811-0_52

Ordering information: This item can be ordered from
http://www.springer.com/9789464638110

DOI: 10.2991/978-94-6463-811-0_52

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 ().