Improving the quality control of technical items in the defense industry with the technique of image processing and fuzzy transformation using the GLR control chart

Document Type : Original Article

Authors

1 Faculty Member in Command and Staff University, Tehran, Iran.

2 Department of Science and Technology Studies, AJA Command and Staff University, Tehran, Iran.

3 Researcher in Aja Command and Staff University, Tehran, Iran.

10.22034/dfsr.2024.2002226.1701

Abstract

Objective:
The main goal is to propose a model for quality control in the defense industry, utilizing image processing and fuzzy transform. Emphasis is on selecting the optimal generalized fuzzy transform section for image compression to enhance the performance of defense and combat weapons.
Methodology:
The methodology employs modern image processing and fuzzy transform techniques for statistical quality control. High-volume data analysis occurs in production lines, managing processes for defense and combat weapon products like glass and metals. MATLAB is the implementation platform, emphasizing the optimal selection of the generalized fuzzy transform section for image compression and processing.
Results:
MATLAB validation confirms the success of our model in quality control for defense systems. Comparative studies show the triangular fuzzy section model excels, especially in defect detection post-illumination changes, surpassing Kusha et al. in most cases.
Conclusion:
In conclusion, our study emphasizes the vital role of image processing and fuzzy transform techniques in defense. The developed model successfully achieves quality control goals, optimizes processes, and enhances defense and combat weapon quality. This reflects a growing industry trend, with an increasing adoption of these methods to meet goals and address challenges.

Keywords

Main Subjects

Defensive Future Studies
Volume 8, Issue 31
February 2024

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