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This is a Experimental Study study.

October 15, 2025Highlights in Science Engineering and Technology

Research on Production Process Quality Control Optimization Based on Multi-stage Decision Model

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Authors

RHRui HeChina University of Petroleum, Beijing LLLeo LauWestern University

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Implication

This research integrates sampling hypothesis testing and decision models to enhance quality control, suggesting significant cost reduction and defect rate improvement.

Key Points

Significant improvements include 15-20% cost reduction and 25-30% deficit rate improvement through a novel approach.
The model achieves 95% confidence for rejection and 90% for acceptance using a sampling inspection scheme.
Dynamic programming principles are applied to optimize supplier selection and production decisions under complex conditions.
Monte Carlo simulation confirms the model's effectiveness under uncertain defect rates, offering practical insights for manufacturing.

Cite This Study

He et al. (2025) studied this question.

synapsesocial.com/papers/68ef858cc6a308ba0635543f https://doi.org/10.54097/ghbyex11

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Implication

This research integrates sampling hypothesis testing and decision models to enhance quality control, suggesting significant cost reduction and defect rate improvement.

Research on Production Process Quality Control Optimization Based on Multi-stage Decision Model

Discussion

Member takes

Implication

Key Points

Cite This Study

Research on Production Process Quality Control Optimization Based on Multi-stage Decision Model

Discussion

Member takes

Implication

Key Points

Cite This Study

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