The washing machine is one of the important home appliance. Most of today's common washing machines do not yet have smart features. Smart white goods have some decision-making functions instead of users. Smart washing machines can collect some data through their different sensors and use this data in appropriate actions. In this paper, it is aimed to suggest the most suitable program duration to the user and save energy, water and time by using a fuzzy controller system with three inputs and one output. Three different inputs are used; the dirt level of the laundry, the amount of oil and the amount of load. These input values can be obtained through related sensors. Washing time will be obtained as a single output. It is aimed to obtain optimum washing time by trying different methods in fuzzy controller. Two different types of fuzzification methods, triangular and trapezoidal, are applied as membership functions. As the fuzzy inference engine methods, product and minimum inference engine are used comparatively. This study also analyze the effects of the application of different defuzzification methods. We deployed five defuzzification methods: center of gravity, bisector, largest of maximum, smallest of maximum, and mean of maximum. The codes are written using Python programming language. For the evaluation, the results obtained from different methods were compared with each other. According to results, most suitable washing time can be obtained by using the methods of trapezoidal membership function for fuzzification, minimum inference engine and center of gravity for defuzzification.