Development of fuzzy inference system for automatic tea making

Ahamed, Nizam Uddin; Taha, Zahari; Khairuddin, Ismail B. Mohd; Rabbi, Mohammad Fazle; Sikandar, Tasriva; Palaniappan, Rajkumar; Ali, Md. Asraf; Rahman, Sabuktagin; Sundaraj, Kenneth

doi:10.1109/i2cacis.2016.7885314

Cited by 5 publications

(1 citation statement)

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“…In the study, the basic parameters of air conditioning and the oxygen level were considered as inputs for the fuzzy inference system. In addition, [16], [21], [22] investigated fuzzy logic controller design for other intelligent manufacturing technology. Different types of contamination and health hazards in pharmaceutical industries have been investigated in previous studies [17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic-based improved ventilation system for the pharmaceutical industry

Rahman

Rabbi²,

Altwijri³

et al. 2018

IJET

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Indoor air quality in pharmaceutical industry plays a vital role in the production and storing of medicine. Stable indoor environment including favorable temperature, humidity, air flow and number of microorganisms requires consistent monitoring. This paper aimed to develop a fuzzy logic-based intelligent ventilation system to control the indoor air quality in pharmaceutical sites. Specifically, in the proposed fuzzy inference system, the ventilation system can control the air flow and quality in accordance with the indoor temperature, humidity, air flow and microorganisms in the air. The MATLAB® fuzzy logic toolbox was used to simulate the performance of the fuzzy inference system. The results show that the efficiency of the system can be improved by manipulating the input-output parameters according to the user’s demands. Compared with conventional heating, ventilation and air-conditioning (HVAC) systems, the proposed ventilation system has the additional feature of the existence of microorganisms, which is a crucial criterion of indoor air quality in pharmaceutical laboratories.

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