Random in-process quality control (IPQC) is conducted in one of the departments in a circuit board manufacturing company, Company A, which produces high-mixed products, and results in complete failure of ensuring the quality of parts produced. Consequently, defects occur on the parts produced, leading to high rejection rate. This high rejection rate eventually results in high cost of non-value-added activities, which include rework of rejected parts. This paper introduces quality planning to ensure the quality of work-in-progress (WIP) parts in the production with discrete event simulation (DES) software. A series of experiments is conducted by using varying parameters, including flow patterns of parts in the shop floor and number of IPQC inspector, to assess the significance of these parameters on the performance measures relevant to quality perspective. Statistical analysis is conducted on the simulation results via ANOVA. Findings from this research prove that varying the parameters has a significant effect on the performance measures.