Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 487 https://internationalpubls.com Python-Based Fuzzy Logic Control System for Optimizing Washing Machine Efficiency Instead of MATLAB 1Dr. K. Raja, 2Dr. I. Valliammal, 3Dr. K. Mathevan Pillai, 4M. Guna 1Associate Professor, Department of Mathematics, Sri Manakula Vinayagar Engineering College, Puducherry, India. raja.rajth@gmail.com 2Assistant Professor, Department of Mathematics, Manonmaniam Sundaranar University, Tirunelveli -12. valli.vasanthi@gmail.com 3Prof. Dept of mathematics, Francis Xavier Engineering college, Thirunelveli, Tamil Nadu. madhevanpillai@francisxavier.ac.in 4Assistant Professor, Department of Mathematics, Sri Manakula Vinayagar Engineering College, Puducherry, India. guna071085@gmail.com Article History: Received:20-11-2024 Revised:17-12-2024 Accepted:12-01-2025 Abstract- One of the most important aspects of our everyday routines is laundry. Clothing cleaning was done by hand in the past, but as technology has advanced, these manual activities have been replaced by machines, which has made life more convenient. The washing machine, which was created to save time, energy, and water, is one example of these advances. A fuzzy logic control system was created to maximize efficiency by tailoring washing procedures to user requirements. Nowadays, fuzzy logic—a kind of reasoning that deals with approximations rather than absolute or false values—is frequently used, particularly in artificial intelligence to simulate human-like decision- making in automated systems. Fuzzy logic is used in many different fields, including satellites, air conditioners, unmanned aerial aircraft, transmission systems, traffic control systems, and anti-lock brake systems. Python addresses some of the drawbacks of MATLAB by offering a simplified method of applying fuzzy logic in the context of washing machines. In this Python-based system, outputs like wash time, spin speed (RPM), drying time, and water temperature are determined by inputs like fabric type, filth level, and load size. While maintaining the best possible wash quality, the objective is to reduce time, electricity, and water usage. Simulation findings show that this strategy greatly improves wash performance and efficiency. Keywords---Python; Fuzzy logic system; Artificial Intelligence; Rule Viewer; MATLAB. I. INTRODUCTION Python is a high-level interpreted programming language that was initially created in 1980. Guido Van Rossum of Centrum Wiskunde and Informatica (CWI) in the Netherlands released mailto:raja.rajth@gmail.com mailto:madhevanpillai@francisxavier.ac.in mailto:guna071085@gmail.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 488 https://internationalpubls.com Python in 1991. The Python community awarded him the title of "Benevolent Dictator for Life" (BDFL) in recognition of his ongoing development efforts and crucial role in choosing the right course. Python is an easy and powerful programming language. It is helpful for the beginners. It can perform complex mathematics and handle large data and files. It increases the reduction of memory usage and time complexity. Python was first implemented using C language hence it was called C Python initially. The main advantage of Python is that, it does not use many symbols such as semi colon and curly braces in looping statements. Python uses indentation to indicate a block of code and hence it is easy to read and understand. Python has the major features relating to Object-Oriented Programming concepts. Python 2.0 was first released on 16th October, 2000 with innovative features and developments like Garbage collector for cycle detecting for memory management and also supports Unicode. Python 3.0 was released on 3rd December, 2008 after conducting several tests. But many of its feature have been back ported. Python 2.7 was reported by the Python community for Sunset date that is End of Life (EOL) date, but was postponed to 2020 because of many people concern that it cannot be easily forward-ported to Python 3 within the stipulated time periods. Python finds its application over several domain such as Artificial Intelligence, Machine Learning, Deep Learning, Web Development, installers, security systems, etc. In this paper, we use Fuzzy Logic Controller for liquid level maintaining and control. Previous approaches for Fuzzy Logic Control was designed in MATLAB. But here we have programmed Fuzzy Logic Control using Python for easy, precise and compact structure of program. II. FUZZY LOGIC SYSTEM The concept of fuzzy logic control enables computers to make decisions similarly to those made by humans. It operates using conditional statements. The majority of people are unaware of how long it takes to wash their clothes. To address these problems, washing machines that use fuzzy logic controllers (FLC) are made to be both more efficient and less expensive. The fuzzy logic concept in Python was used to develop the fuzzy logic controller for the washing machine's liquid level monitoring. Washing machine developed based on Fuzzy logic rules will be helpful in washing procedures by sensing the amount of dirt, type of dirt etc. The Fuzzy logic system used in washing time will not only reduces the energy consumption (including electricity and water) but also helps the users to save finances in commercial boundary. The application of Fuzzy logic controllers has more dynamic range when compared to the conventional PID controller. The conditions inside the machine are monitored by sensors. The fuzzy logic also has a feature of ‘one touch control’. The fuzzy logic also checks the amount of dirt and grease Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 489 https://internationalpubls.com direction of the spinning, the detergent and water to be added and so on. The reloading takes place to correct the direction of spin. Neuro fuzzy logic system has inbuilt optical sensors which detect the type of fabric used by the user. The washing machines incorporate optical sensors to find light permeability of water in washer tank, a device that converts light rays to electrical signal. The optical sensors detect change in light beams. A point at which there is no change of color in the water is known as saturation point. There is no logic or formula to determine the relationship between volumes of clothes and dirt and also the time needed to wash. The structure of washing machine controller has not let itself to ancient methods as the input and output are not clear. III. PROPOSED DESIGN The main work of washing machine is to clean the dirty clothes and other fabrics without any damage. For that, we give a particular input according to the properties of the cloth to produce output such as heavy wash or soft wash, time of washing and so on. In relation to that, 27 principles for washing time and 27 principles for water temperature are proposed and used to design this Fuzzy Logic Control System using Python. To achieve these advantages in an economical way, this washing machine uses fuzzy logic system with some of these three major input parameters: 1. Weight of Fabrics 2. Stains category 3. Type of Fabric Fig 1. Fuzzy logic Inputs and Outputs System The FLC processes the input information and produces five outputs which are: 1. Wash Duration 2. Temperature 3. RPM Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 490 https://internationalpubls.com 4. Dry Time 5. Wash quality A. Algorithm for our Fuzzy logic system: BEGIN < FUZZY LOGIC > (FAB_TYPE, DIRT_TYPE, WEIGHT) IF FAB_TYPE=SILK AND DIRT_TYPE= LIGHTLY_SOILED AND WEIGHT = BELOW_10KG THEN PRINT WASH STASTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=10_TO_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=ABOVE_15 KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=10_TO_ 15 KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=ABOVE_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=10_TO_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = SILK AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=ABOVE_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=BELOW_10KG THEN Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 491 https://internationalpubls.com PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=10_TO_ 15 KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=ABOVE_15 KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=10_TO_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=ABOVE_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=10_ TO_ 15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = WOOLEN AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=ABOVE_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=10_ TO_15 KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=LIGHTLY_SOILED AND WEIGHT=ABOVE_15KG THEN PRINT WASH STATISTICS Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 492 https://internationalpubls.com ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=10_TO_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=NORMALLY_SOILED AND WEIGHT=ABOVE_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=BELOW_10KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=10_TO_15KG THEN PRINT WASH STATISTICS ELSE IF FAB_TYPE = COTTON AND DIRT_TYPE=HEAVILY_SOILED AND WEIGHT=ABOVE_ 15KG THEN PRINT WASH STATISTICS A. Python code for our Fuzzy logic system: Fuzzy rules have been involved in the modeling of washing machines. The whole system which we have made is developed by using Python. The code for our FLC system is as follows: list1=[] def result(): #Silk print("------") print("OUTPUT") print("------") Rule 1: if((list1[0]=="silk")and(list1[1]=="lightly soiled")and(list1[2]=="below_10kg")):#1 print("Wash Duration - 0.35 h") print("Temperature - 30c") print("RPM - 400") Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 493 https://internationalpubls.com print("Dry Time - Quick") print("Quality - Good") input("Press Enter key to exit...") Rule 2: elif((list1[0]=="silk")and(list1[1]=="lightly soiled")and(list1[2]=="10_to_15kg")):#2 print("Wash Duration - 0.47 h") print("Temperature - 30c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Good") input("Press Enter key to exit...") Rule3: elif((list1[0]=="silk")and(list1[1]=="lightly soiled")and(list1[2]=="above_15kg")):#3 print("Wash Duration - 0.50 h") print("Temperature - 40c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Best") input("Press Enter key to exit...") Rule 4: elif((list1[0]=="silk")and(list1[1]=="normally soiled")and(list1[2]=="below_10kg")):#4 print("Wash Duration - 0.50 h") print("Temperature - 30c") print("RPM - 400") print("Dry Time - Long") print("Quality - Medium") input("Press Enter key to exit...") Rule 5: elif((list1[0]=="silk")and(list1[1]=="normally soiled")and(list1[2]=="10_to_15kg")):#5 print("Wash Duration - 1.18 h") print("Temperature - 30c") print("RPM - 800") Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 494 https://internationalpubls.com print("Dry Time - Quick") print("Quality - Good") input("Press Enter key to exit...") Rule 6: elif((list1[0]=="silk")and(list1[1]=="normally soiled")and(list1[2]=="above_15kg")):#6 print("Wash Duration - 1.18 h") print("Temperature - 40c") print("RPM - 600") print("Dry Time - Long") print("Quality - Medium") input("Press Enter key to exit...") Rule 7: elif((list1[0]=="silk")and(list1[1]=="heavily soiled")and(list1[2]=="below_10kg")):#7 print("Wash Duration - 0.50 h") print("Temperature -30c") print("RPM - 800") print("Dry Time - Intermediate") print("Quality - Good") input("Press Enter key to exit...") Rule 8: elif((list1[0]=="silk")and(list1[1]=="heavily soiled")and(list1[2]=="10_to_15kg")):#8 print("Wash Duration - 1.18 h") print("Temperature - 40c") print("RPM - 800") print("Dry Time - Quick") print("Quality - Best") input("Press Enter key to exit...") Rule 9: elif((list1[0]=="silk")and(list1[1]=="heavily soiled")and(list1[2]=="above_15kg")):#9 print("Wash Duration - 2.10 h") print("Temperature - 40c") Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 495 https://internationalpubls.com print("RPM - 800") print("Dry Time - Quick") print("Quality - Best") input("Press Enter key to exit...") #Woolen Rule 10: elif((list1[0]=="woolen")and(list1[1]=="lightly soiled")and(list1[2]=="below_10kg")):#10 print("Wash Duration - 0.47 h") print("Temperature - 40c") print("RPM - 800") print("Dry Time - Long") print("Quality - Medium") input("Press Enter key to exit...") Rule 11: elif((list1[0]=="woolen")and(list1[1]=="lightly soiled")and(list1[2]=="10_to_15kg")):#11 print("Wash Duration - 0.50 h") print("Temperature - 40c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Good") input("Press Enter key to exit...") Rule 12: elif((list1[0]=="woolen")and(list1[1]=="lightly soiled")and(list1[2]=="above_15kg")):#12 print("Wash Duration -1.18 h") print("Temperature - 40c") print("RPM - 800") print("Dry Time - Quick") print("Quality - Good") input("Press Enter key to exit...") Rule 13: elif((list1[0]=="woolen")and(list1[1]=="normally soiled")and(list1[2]=="below_10kg")):#13 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 496 https://internationalpubls.com print("Wash Duration - 0.50 h") print("Temperature -40c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Medium") input("Press Enter key to exit...") Rule 14: elif((list1[0]=="woolen")and(list1[1]=="normally soiled")and(list1[2]=="10_to_15kg")):#14 print("Wash Duration - 0.50 h") print("Temperature - 40c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Medium") input("Press Enter key to exit...") Rule 15: elif((list1[0]=="woolen")and(list1[1]=="normally soiled")and(list1[2]=="above_15kg")):#15 print("Wash Duration - 1.18") print("Temperature - 40c") print("RPM - 800") print("Dry Time - Quick") print("Quality - Best") input("Press Enter key to exit...") Rule 16: elif((list1[0]=="woolen")and(list1[1]=="heavily soiled")and(list1[2]=="below_10kg")):#16 print("Wash Duration - 1.18") print("Temperature - 60c") print("RPM - 800") print("Dry Time - Quick") print("Quality - Best") input("Press Enter key to exit...") Rule 17: elif((list1[0]=="woolen")and(list1[1]=="heavily soiled")and(list1[2]=="10_to_15kg")):#17 Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 497 https://internationalpubls.com print("Wash Duration -1.18") print("Temperature - 40c") print("RPM - 1000") print("Dry Time - Quick") print("Quality - Good") input("Press Enter key to exit...") Rule 18: elif((list1[0]=="woolen")and(list1[1]=="heavily soiled")and(list1[2]=="above_15kg")):#18 print("Wash Duration - 2.10 h") print("Temperature - 60c") print("RPM - 1200") print("Dry Time - Quick") print("Quality - Good") input("Press Enter key to exit...") #Cottan Rule 19: elif((list1[0]=="cottan")and(list1[1]=="lightly soiled")and(list1[2]=="below_10kg")):#19 print("Wash Duration - 0.47 h") print("Temperature - 40c") print("RPM - 400") print("Dry Time - Intermediate") print("Quality - Good") input("Press Enter key to exit...") Rule 20: elif((list1[0]=="cottan")and(list1[1]=="lightly soiled")and(list1[2]=="10_to_15kg")):#20 print("Wash Duration - 0.50 h") print("Temperature - 40c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Good") input("Press Enter key to exit...") Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 498 https://internationalpubls.com Rule 21: elif((list1[0]=="cottan")and(list1[1]=="lightly soiled")and(list1[2]=="above_15kg")):#21 print("Wash Duration - 1.18") print("Temperature - 40c") print("RPM - Long") print("Dry Time - Quick") print("Quality - Best") input("Press Enter key to exit...") Rule 22: elif((list1[0]=="cottan")and(list1[1]=="normally soiled")and(list1[2]=="below_10kg")):#22 print("Wash Duration - 0.50 h") print("Temperature - 40c") print("RPM - 600") print("Dry Time - Intermediate") print("Quality - Best") input("Press Enter key to exit...") Rule 23: elif((list1[0]=="cottan")and(list1[1]=="normally soiled")and(list1[2]=="10_to_15kg")):#23 print("Wash Duration -1.18") print("Temperature - 40c") print("RPM - 800") print("Dry Time - Quick") print("Quality - Best") input("Press Enter key to exit...") Rule 24: elif((list1[0]=="cottan")and(list1[1]=="normally soiled")and(list1[2]=="above_15kg")):#24 print("Wash Duration - 2.10 h") print("Temperature - 40c") print("RPM - 1000") print("Dry Time - Quick") print("Quality - Good") input("Press Enter key to exit...") Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 499 https://internationalpubls.com Rule 25: elif((list1[0]=="cottan")and(list1[1]=="heavily soiled")and(list1[2]=="below_10kg")):#25 print("Wash Duration - Long") print("Temperature - 60c") print("RPM - 1000") print("Dry Time - Intermediate") print("Quality - Good") input("Press Enter key to exit...") Rule 26: elif((list1[0]=="cottan")and(list1[1]=="heavily soiled")and(list1[2]=="10_to_15kg")):#26 print("Wash Duration - 1.18") print("Temperature - 60c") print("RPM - 1200") print("Dry Time - Long") print("Quality - Best") input("Press Enter key to exit...") Rule 27: elif((list1[0]=="cottan")and(list1[1]=="heavily soiled")and(list1[2]=="above_15kg")):#27 print("Wash Duration - 2.10 h") print("Temperature - 60c") print("RPM - 1200") print("Dry Time - Long") print("Quality - Good") input("Press Enter key to exit...") def fun(): list1.append(str(input("Enter the Fabric_type:").lower())) list1.append(str(input("Enter the Stain_category:").lower())) list1.append(str(input("Enter the Fabric_Weight:").lower())) print(list1) if(((list1[0]=="cottan")or(list1[0]=="silk")or(list1[0]=="woolen"))and Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 500 https://internationalpubls.com ((list1[1]=="lightly soiled")or(list1[1]=="normally soiled")or(list1[1]=="heavily soiled"))and ((list1[2]=="below_10kg")or(list1[2]=="10_to_15kg")or(list1[2]=="above_15kg"))): settings=str(input("Do you want to Change the Settings (YES OR NO):").lower()) if(settings=="yes"): list1.clear() fun() elif(settings=="no"): result() else: print("Given input is wrong try again") list1.clear() fun() fun() C. Resultant values of our washing machine’s FLC python code: The decision of the fuzzy logic controller is made using previously stored data in the database. The principles which we use in this paper is derived from the logical thinking, data taken from daily usage, and experimentation of the system in a controlled environment. The set of principles used here to derive the output are based on the Fuzzy logic system using python code are given below: Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 501 https://internationalpubls.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 502 https://internationalpubls.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 503 https://internationalpubls.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 504 https://internationalpubls.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 505 https://internationalpubls.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 506 https://internationalpubls.com Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 507 https://internationalpubls.com The above input and output can be represented in a table for an easy understanding of how it works: TABLE I R. N o Linguistic Inputs Linguistic Outputs Type of Cloth es Degree of Dirtiness Mass of Cloth Load Wash Time Tempera ture RPM Dry Time Wash Quality 1 Silk lightly Below_1 0.35 h 30 c Quick Good Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 508 https://internationalpubls.com soiled 0kg 400 2 Silk lightly soiled 10_to_15 kg 0.47 h 30 c 600 Intermediate Good 3 Silk lightly soiled Above_1 5kg 0.50 h 40 c 600 Intermediate Best 4 Silk normally soiled Below_1 0kg 0.50 h 30 c 400 Long Medium 5 Silk normally soiled 10_to_15 kg 1.18 h 30 c 800 Quick Good 6 Silk normally soiled Above_1 5kg 1.18 h 40 c 600 Long Medium 7 Silk heavily soiled Below_1 0kg 0.50 h 30 c 800 Intermediate Good 8 Silk heavily soiled 10_to_15 kg 1.18 h 40 c 800 Quick Best 9 Silk heavily soiled Above_1 5kg 2.10 h 40 c 800 Quick Best 1 0 Wooll en lightly soiled Below_1 0kg 0.47 h 40 c 600 Long Medium 1 1 Wooll en lightly soiled 10_to_15 kg 0.50 h 40 c 800 Intermediate Good 1 2 Wooll en lightly soiled Above_1 5kg 1.18 h 40 c 800 Quick Good 1 3 Wooll en normally soiled Below_1 0kg 0.50 h 40 c 600 Intermediate Medium 1 Wooll normally 10_to_15 1.18 h 40 c Intermediate Medium Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 509 https://internationalpubls.com 4 en soiled kg 600 1 5 Wooll en normally soiled Above_1 5kg 1.18 h 60 c 800 Quick Best 1 6 Wooll en heavily soiled Below_1 0kg 1.18 h 60 c 800 Quick Best 1 7 Wooll en heavily soiled 10_to_15 kg 1.18 h 60 c 1000 Quick Good 1 8 Wooll en heavily soiled Above_1 5kg 2.10 h 60 c 1200 Quick Good 1 9 Cotto n lightly soiled Below_1 0kg 0.47 h 40 c 400 Intermediate Good 2 0 Cotto n lightly soiled 10_to_15 kg 0.50 h 40 c 600 Intermediate Good 2 1 Cotto n lightly soiled Above_1 5kg 1.18h 40 c 800 Quick Best 2 2 Cotto n normally soiled Below_1 0kg 0.50 h 40 c 600 Intermediate Best 2 3 Cotto n normally soiled 10_to_15 kg 1.18h 40 c 800 Quick Best 2 4 Cotto n normally soiled Above_1 5kg 2.10 h 40 c 1000 Quick Good 2 5 Cotto n heavily soiled Below_1 0kg 1.18h 60 c 1000 Quick Good 2 6 Cotto n heavily soiled 10_to_15 kg 1.18h 60 c 1200 Quick Best 2 Cotto heavily Above_1 2.10 h 60 c 1200 Quick Good Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 510 https://internationalpubls.com 7 n soiled 5kg Here in this table, three types of clothes are taken into consideration. They are silk, woollen and cotton. They have the weight of 10 to 15 kg from lightly soiled to heavily soiled. Using these three parameters, the output such as the temperature ranging from 30 to 60 degree Celsius, RPM ranging from 400 to 1200, washing time differing from quick to long and washing quality ranging from medium to best. These outputs produced from inputs are calculated on the basis of fuzzy logic controller system which is programmed on python for use of a greater number of criteria and also to reduce the power consumption. Thus, the best fit of output is produced by the FLC system for the given input and to reduce the water consumption and power consumption. IV. RESULTANT AND SIMULATION Consider any type of material or cloth to be used for washing. The mass of the cloth and the degree of dirtiness comes into consideration. When these things are given as an input to the system, that is the washing machine, the fuzzy logic system working in it measures how much temperature it should be maintained while washing, what is the RPM which it has to run, the time of washing and the quality of wash using sensors are calculated and produced as the output. These can be visualized using graph simulation as given below: Fig 2. Degree of dirtiness vs Types of clothes based on Washing time Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 511 https://internationalpubls.com Fig 3. Mass of cloth load vs Types of clothes based on Washing time Fig 4. RPM vs types of clothes based on degree of dirtiness Fig 5. Mass of cloth load vs Degree of dirtiness based on RPM Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 512 https://internationalpubls.com Fig 6. Mass of cloth load vs Degree of dirtiness based on Dry time Fig 7. Count of Wash quality vs types of clothes based on degree of dirtiness Fig 8. Wash quality vs Degree of dirtiness based on Mass of cloth load Communications on Applied Nonlinear Analysis ISSN: 1074-133X Vol 32 No. 1 (2025) 513 https://internationalpubls.com V. CONCLUSION Using fuzzy logic, we have created an automatic washing machine controller that evaluates the quality of the wash according to two parameters: the drum rotation speed (RPM) and the dry/rinse duration. The wash quality index is a performance metric that precisely assesses a washing machine's operational efficiency under certain load conditions. By employing a Python-based fuzzy logic controller, the required RPM for a given input load is automatically determined. Based on this, the average rinse time of the load is assumed, which is how the wash quality index is determined. Time is managed by this system, which also conserves electricity and water. This automatic control system illustrates how fuzzy logic controllers are superior than conventional washing machines. Thus, Fuzzy logic control systems in Python provides great advantages and provides more solutions for problems that cannot be solved by MATLAB environment by reducing the disadvantages such as time management, processing speed and restricted number of input values and etc. So, Python would be the best solution to solve these problems. REFERENCES [1]. L.A. Zadeh, Fuzzy Sets, Information and Control, 338–353, (1965). [2]. Van Rossum Guido. A Brief Timeline of Python. The History of Python. Google, 2009. Retrieved 20 January 2009. [3]. Guttag John V. (2016-08-12). Introduction to Computation and Programming Using Python: With Application to Understanding Data. MIT Press. ISBN 978-0-262-52962-4 [4]. Workman, M. Hardware requirement for Fuzzy Logic Control Systems.Lubbock,TX: Texas Tech University, (1996) [5]. Daily Ned. Python 3.6.4 is now available. Python Insider. 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