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
References
- Almeida, E., Alves, I., Brites, C., & Fedrizzi, L. (2003). Cataphoretic and autophoretic automotive primers: a comparative study. Progress in Organic Coatings, 46(1), 8-20.
- Bračun, D., & Lekše, I. (2019). A visual inspection system for KTL coatings. Procedia CIRP, 81, 771-774.
- Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1-9.
- Fedel, M., Druart, M. E., Olivier, M., Poelman, M., Deflorian, F., & Rossi, S. (2010). Compatibility between cataphoretic electro-coating and silane surface layer for the corrosion protection of galvanized steel. Progress in Organic Coatings, 69(2), 118-125.
- Hylák, K. M. (2019). Development of equipment for mass cataphoresis painting. In Materials Science Forum. Trans Tech Publications Ltd.
- Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi‐criteria supplier selection using fuzzy AHP. Logistics information management. Emerald Group Publishing
- Kekilli, E., Cebeci, U., & Sılay, L. (2021). Selection of VFQ consultant by using integrated fuzzy AHP and fuzzy TOPSIS. Avrupa Bilim ve Teknoloji Dergisi, (24), 262-267.
- Klir, G., & Yuan, B. (1995). Fuzzy sets and fuzzy logic theory and applications. New Jersey: Prentice Hall.
- Nădăban, S., Dzitac, S., & Dzitac, I. (2016). Fuzzy TOPSIS: a general view. Procedia Computer Science, 91, 823-831.
- Roy, T., & Dutta, R. (2018). Integrated fuzzy AHP and fuzzy TOPSIS methods formulti-objective. Springer.
- Somsuk, N., & Laosirihongthong, T. (2014). A fuzzy AHP to prioritize enabling factors for strategic management of university business incubators: Resource-based view. Technological Forecasting and Social Change, 85, 198-210.
- Speight, J. G. (2014). Oil and gas corrosion prevention: From surface facilities to refineries. Gulf Professional Publishing.
- Zadeh, L. (1996). Fuzzy sets. In Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh. Los Angles: World Scientific.
Abstract
References
- Almeida, E., Alves, I., Brites, C., & Fedrizzi, L. (2003). Cataphoretic and autophoretic automotive primers: a comparative study. Progress in Organic Coatings, 46(1), 8-20.
- Bračun, D., & Lekše, I. (2019). A visual inspection system for KTL coatings. Procedia CIRP, 81, 771-774.
- Chen, C. T. (2000). Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets and Systems, 114(1), 1-9.
- Fedel, M., Druart, M. E., Olivier, M., Poelman, M., Deflorian, F., & Rossi, S. (2010). Compatibility between cataphoretic electro-coating and silane surface layer for the corrosion protection of galvanized steel. Progress in Organic Coatings, 69(2), 118-125.
- Hylák, K. M. (2019). Development of equipment for mass cataphoresis painting. In Materials Science Forum. Trans Tech Publications Ltd.
- Kahraman, C., Cebeci, U., & Ulukan, Z. (2003). Multi‐criteria supplier selection using fuzzy AHP. Logistics information management. Emerald Group Publishing
- Kekilli, E., Cebeci, U., & Sılay, L. (2021). Selection of VFQ consultant by using integrated fuzzy AHP and fuzzy TOPSIS. Avrupa Bilim ve Teknoloji Dergisi, (24), 262-267.
- Klir, G., & Yuan, B. (1995). Fuzzy sets and fuzzy logic theory and applications. New Jersey: Prentice Hall.
- Nădăban, S., Dzitac, S., & Dzitac, I. (2016). Fuzzy TOPSIS: a general view. Procedia Computer Science, 91, 823-831.
- Roy, T., & Dutta, R. (2018). Integrated fuzzy AHP and fuzzy TOPSIS methods formulti-objective. Springer.
- Somsuk, N., & Laosirihongthong, T. (2014). A fuzzy AHP to prioritize enabling factors for strategic management of university business incubators: Resource-based view. Technological Forecasting and Social Change, 85, 198-210.
- Speight, J. G. (2014). Oil and gas corrosion prevention: From surface facilities to refineries. Gulf Professional Publishing.
- Zadeh, L. (1996). Fuzzy sets. In Fuzzy sets, fuzzy logic, and fuzzy systems: selected papers by Lotfi A Zadeh. Los Angles: World Scientific.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Articles |
| Authors | |
| Early Pub Date | September 5, 2021 |
| Publication Date | December 31, 2021 |
| Published in Issue | Year 2021Volume: 12 |
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