Product quality is of supreme importance in any food processing industry. Usually faulty products are discarded through proper inspection. But this inspection requires additional resource deployment while the cost of rework and machine downtime also pose potential threat by interrupting the production process and thus often cause loss in revenue. Although zero defect is a promising concept for better production planning and control, in many food processing industries the defect in product can’t be avoided completely. But even if the defects can be controlled, can be minimized, it would be highly beneficial for mass production. This paper presents a methodology to define the number of defective or bad quality products in a food processing plant as a dependent function of various input parameters during the production process. Fuzzy logic and multiple linear regression analysis are used to determine the impact of the input parameters on the quality of the product. Finally, with the help of Pareto analysis, some possible solutions are provided for minimization of defective items.