| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 187 - Number 67 |
| Year of Publication: 2025 |
| Authors: Ayman M. Mansour, Yazan A. Yousef, Mohammad A. Obeidat, Hesham I. Al-salem |
10.5120/ijca2025926142
|
Ayman M. Mansour, Yazan A. Yousef, Mohammad A. Obeidat, Hesham I. Al-salem . Enhancing Precision in Spice Bag Dispensing for Noodle Cup Production through Automated Fuzzy Inference System Integration. International Journal of Computer Applications. 187, 67 ( Dec 2025), 21-28. DOI=10.5120/ijca2025926142
This paper delves into the integration of an advanced spice bag dispensing system within the Noodle cup production line, focusing specifically on fried noodles. At the heart of this system lies a meticulously designed fuzzy inference system, engineered to enhance precision and adaptability in the identification and placement of spice bags. Leveraging real-time inputs from cameras, production line speed, and spice bag characteristics, the fuzzy system dynamically applies a set of rules, ensuring precise dispensing in the face of uncertainties and variations inherent in the production environment. Drawing comparisons with a scenario involving the classification of 350 collected photos, this study highlights the adaptability and precision of the fuzzy inference system. The results showcase outstanding performance, including an accuracy of 91.43%, precision of 88.24%, recall of 93.75%, and an F1 score of 90.91%. This developed system significantly contributes to elevating the quality of instant noodle production by ensuring the presence of spice packets in all final products, thereby guaranteeing actual quality despite the high-speed nature of the production line. Operating at a rate of 60,000 cartons in an 8-hour workday, each containing 24 cups of instant noodles, this system ensures heightened efficiency and productivity, maintaining a consistently high flavor profile in the production of instant noodle cups.