Overview

This is the problem from the 2024 China Undergraduate Mathematical Contest in Modeling. We completed it within three days and won the first prize in Guangdong Province.
The paper develops a profit-oriented production decision model combining Monte Carlo simulation, dynamic transfer functions, and Bayesian inference for multi-stage manufacturing optimization.
It applies statistical testing, stochastic simulation, and probabilistic modeling to minimize cost and defect risks across inspection and assembly processes.
The model enables real-time decision adjustment via Bayesian updating and shows potential for intelligent manufacturing and industrial process optimization.