Advanced Study: Improving the Quality of Cooling Water Towers’ Conductivity Using a Fuzzy PID Control Model

You-Shyang Chen, Ying-Hsun Hung (), Mike Yau-Jung Lee, Jieh-Ren Chang (), Chien-Ku Lin and Tai-Wen Wang
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You-Shyang Chen: College of Management, National Chin-Yi University of Technology, Taichung 411030, Taiwan
Ying-Hsun Hung: Department of Finance, Chaoyang University of Technology, Taichung 413310, Taiwan
Mike Yau-Jung Lee: Department of Business Administration, China University of Technology, Taipei City 116, Taiwan
Jieh-Ren Chang: Department of Electronic Engineering, National Ilan University, I-Lan 26047, Taiwan
Chien-Ku Lin: Department of Business Management, Hsiuping University of Science and Technology, Taichung City 412406, Taiwan
Tai-Wen Wang: Department of Electronic Engineering, National Ilan University, I-Lan 26047, Taiwan

Mathematics, 2024, vol. 12, issue 20, 1-27

Abstract: Cooling water towers are commonly used in industrial and commercial applications. Industrial sites frequently have harsh environments, with certain characteristics such as poor air quality, close proximity to the ocean, large quantities of dust, or water supplies with a high mineral content. In such environments, the quality of electrical conductivity in the cooling water towers can be significantly negatively affected. Once minerals (e.g., calcium and magnesium) form in the water, conductivity becomes too high, and cooling water towers can become easily clogged in a short time; this leads to a situation in which the cooling water host cannot be cooled, causing it to crash. This is a serious situation because manufacturing processes are then completely shut down, and production yield is thus severely reduced. To solve these problems, in this study, we develop a practical designation for a photovoltaic industry company called Company-L. Three control methods are proposed: the motor control method, the PID control method, and the fuzzy PID control method. These approaches are proposed as solutions for successfully controlling the forced replenishment and drainage of cooling water towers and controlling the opening of proportional control valves for water release; this will further dilute the electrical conductivity and control it, bringing it to 300 µS/cm. In the experimental processes, we first used practical data from Company-L for our case study. Second, from the experimental results of the proposed model for the motor control method, we can see that if electrical conductivity is out of control and the conductivity value exceeds 1000 µS/cm, the communication software LINE v8.5.0 (accessible via smartphone) displays a notification that the water quality of the cooling water towers requires attention. Third, although the PID control method is shown to have errors within an acceptable range, the proportional (P) controller must be precisely controlled; this control method has not yet reached this precise control in the present study. Finally, the fuzzy PID control method was found to have the greatest effect, with the lowest level of errors and the most accurate control. In conclusion, the present study proposes solutions to reduce the risk of ice-water host machines crashing; the solutions use fuzzy logic and can be used to ensure the smooth operation of manufacturing processes in industries. Practically, this study contributes an applicable technical innovation: the use of the fuzzy PID control model to control cooling water towers in industrial applications. Concurrently, we present a three-tier monitoring checkpoint that contributes to the PID control method.

Keywords: cooling water towers; electrical conductivity; motor control; PID control; fuzzy PID control (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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