Anfis-based control and digital process monitoring of food spray drying machine
/Wilfred Ralph G. Gomez
- 204 pages : color illustration 28 cm. + 1 CD-ROM (4 ¾ in.)
Dissertation
College of Industrial Education--
Smart technologies disrupted the way the people live and helped solve 21st century problems in food manufacturing systems. In such case, these technologies can help preserve food products thru powderization by using Spray-drying machines. However, existing control methods like PID algorithm built-in in these Spray-drying machines proposes several issues in maintaining high accuracy in developing new native products that results in high-quality powders. Said problems prompted this study at designing an ANFIS-Based Control System and Digital Process Monitoring for Food Spray Drying Machine. Results revealed that testing the hardware components, designing a User Interface (UI), and adopting software components such as ANFIS Machine Learning contributed to having high accuracy in controlling the inlet temperature, feedrate, blower fan speed, and the needle speed. In addition, said activities combined with using the digital process monitoring feature unanimously improved the user's perceived smartness and usability of the prototype. This implies that the prototype can be effectively used to powderize native products which may significantly contribute to nation building-Author's abstract.
Proportional Integral Derivative (PIP) Adaptive Neuro-Fuzzy Inference System (ANFIS) Spray Drying machine