Selecting Image Processing Supplier for Quality Control AI Software in Metal Cataphoretic Painting Firm by Using Fuzzy AHP and Fuzzy Topsis

Abstract

Nowadays many companies try to adopt Industry 4.0 technology in their production lines, supply chains, etc. Industry 4.0 makes a company more profitable and automatized. There are many beneficial impacts of Industry 4.0 in companies unless there is a wrong application. Companies usually buy Artificial Intelligence software and they implement applications for them. The selection of the supplier is the most important part of applying this technology in a company. The application of Industry 4.0 in companies starts with defining the issue or eligible ways of developing. After AI solution is selected, the next phase is defining needs, budget and materials. All phases depend on the supplier. There are many qualitative and quantitative criteria in selecting the supplier of quality control AI software and this causes a lot of complicated processes. As Industry 4.0 is more popular globally, there is a significant increase in supplier numbers. When companies need to select a supplier, they want the selection process simpler and more accurate. Uncertainty in the future makes supplier selection more difficult. Therefore, Fuzzy AHP and Fuzzy TOPSIS methodologies are proper and when companies deal with uncertain situations. As a case study, Karakaya86 firm wants to implement Image Processing technology with Artificial Intelligence in their Quality Control processes for cataphoretic painting metal to the surface, and the study shows which supplier will fit with their needs for quality control defect software by using Fuzzy AHP and Fuzzy TOPSIS. We have not seen any paper similar to our study.

Keywords

• quality control defect detection
• chemistry
• artificial intelligence
• image processing
• supplier selection
• fuzzy topsis
• fuzzy ahp

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