Statistical Quality Control (SQC) is a systematic approach to maintaining and improving the quality of industrial products and processes through the use of statistical methods. In industrial project management, SQC helps managers identify variations in processes, control defects, reduce wastage, and ensure that the final product meets specified quality standards. Instead of depending only on inspection after production, SQC focuses on monitoring the process continuously so that quality problems can be detected and corrected at an early stage. The basic idea of SQC is that every production process contains some variation. Common-cause variation occurs naturally within a stable process, while special-cause variation results from identifiable problems such as machine failure, improper material, human error, or unsuitable working conditions. Statistical techniques help distinguish between these types of variation and support effective corrective action. SQC commonly uses sampling, frequency distributions, Pareto analysis, control charts and process capability analysis. Control charts are one of the most important tools of SQC. A control chart is a graphical method used to observe the performance of a process over time. It generally contains a central line representing the process average and an upper control limit and lower control limit. Samples are taken at regular intervals and their measurements are plotted on the chart. If the observations remain within the control limits