Applying Fuzzy Multi-Criteria Decision Making for the Selection of Competitive Factors in Robotics Based on System Development Life Cycle
Robots are a technology that plays an important role in many industries today. Competition in the robot market is high, so choosing the right competitive factors for robots is important. This study uses a Fuzzy Analytic Hierarchy Process (F-AHP) method to select appropriate competitive factors for the robot. It considers competitive factors in robots and system development life cycles (SDLC). The research results found that important competitive factors for robots include: All 5 experts focus on (C1) interaction factors giving robots flexibility and adaptability to changing environmental conditions while (SC1–5) image processing gives robots the ability to sense and respond to the environment while competing effectively. Combining these two factors improves competitive performance and allows the robot to maximize its time in changing situations. Among the alternative scenarios compared with factors at levels 1 and 2, option A1 (Robotic 1) performed the best in terms of achieving optimal time, as indicated by its calculated weight (Ni) = 0.508 and All 5 students determined the weight values according to Table 1, focusing on factors (C2) Posture factors affect a robot's performance in competition. Maintaining the correct posture helps the robot be agile and efficient in carrying out its tasks and factors (SC2-6) in level 2 Climbing steep slopes gives robots the ability to burn off energy and maintain stability in difficult conditions. Efficient operation in steep conditions is an important competitive factor. Among the alternative scenarios compared with factors at level 1 and level 2, option A1 (Robotic 1) performed the best in terms of achieving optimal time, as indicated by its calculated weight (Ni) = 0.573. This study shows that the F-AHP is an effective tool for selecting appropriate competitive factors for robots.
Institutions
- Chiang Mai University (TH)
Publication Details
- Journal
- Information Technology Journal
- Published
- 2024-10-27
- DOI
- https://doi.org/10.14416/j.it/2024.v2.001
- Citations
- 1
- Primary Topic
- Advanced Data Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.33