Integrating Fuzzy Inference System, Image Processing and Quality Control to Detect Defects and Classify Quality Level of Copper Rods
Publish place: International Journal of Industrial Engineering & Production Research، Vol: 29، Issue: 4
Publish Year: 1397
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_IJIEPR-29-4_005
تاریخ نمایه سازی: 7 دی 1399
Abstract:
Human-based quality control reduces the accuracy of this process. Also, the speed of decision making in some industries is very important. For removing these limitations in human-based quality control, in this paper, the design of an expert system for automatic and intelligent quality control is investigated. In fact, using an intelligent system, the accuracy in quality control is increased. It requires the knowledge of experts in quality control and design of expert systems based on the knowledge and information provided by human and equipment. For this purpose, Fuzzy Inference System (FIS) and Image Processing approach are integrated. In this expert system, the input information is the images of the products and the results of processing on images for quality control are as output. At first, they may be noisy images; the pre-processing is done and then a fuzzy system is used to be processed. In this fuzzy system, according to the images, the rules are designed to extract the specific features that are required. At second, after the required attributes are extracted, the control chart is used in terms of quality. Furthermore, the empirical case study of copper rods industry is presented to show the abilities of the proposed approach.
Keywords:
Image processing , Quality control , Fuzzy inference system , Features from accelerated segment test , Copper rods
Authors
Mohammad Mahdi Dehdar
Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
Mustafa Jahangoshai Rezaee
Faculty of Industrial Engineering, Urmia University of Technology, Urmia, Iran
Marzieh Zarinbal
Iranian Research Institute for Information Science and Technology, Tehran, Iran
Hamidreza Izadbakhsh
Faculty of Engineering, Department of Industrial Engineering, Kharazmi University, Tehran, Iran