Statistical Process Control (SPC) techniques such as control charts and Pareto analysis, are widely applied in quality management to evaluate process stability and identify dominant sources of variation over time. These tools provide manufacturing industries with powerful tools to drive continuous improvement, support data-driven decision-making, and enhance customer satisfaction. The main objectives of this study are to classify and analyse the different types of defects and assess the process stability in the Hot Strip mill. This study adopts a quantitative case study at the Hot Rolling Mill of the Libyan Iron and Steel Company (LISCO). Pareto analysis and C control chart were used to identify dominant defect recourse and assess process stability respectively. Inspection reports and production data were collected and processed using spreadsheet software to assess the quality performance of tinplate production. Pareto analysis reveals that approximately 80% of defects are concentrated in four categories: Telescope (TEL), Over Thickness (OVT), Under Thickness (UNT), and Cracked Edge (CRE). Control chart results further indicated irregularities in the production process, with several defect occurrences falling outside statistical control limits and the variation is systematic not random. Also. the study reveals the statistical methods are not used in continuous basis on hot strip mill. ...................... Keywords:................... Statistical Quality Control, Hot Rolling Mill, Pareto Chart,C- Control Charts, defects, variation.