In this paper, a process improvement model that is enhanced through the integration of motion time study and quality tools is proposed. The model is intended to support the process improvement drive particularly for practitioners of time and motion study approach. Generally, industries at any scale are facing certain problem resulting in shortage of production and quality issues. Correct application of the right tool at the right time and at the right place generates wonder in many industries. But, most of the industries solved the production issues either production shortage or quality issues by using separated individual approaches, i.e. material shortage by using time study analysis approach or quality issues using quality tools approach. In motion time study approach, there is a limitation in terms of identifying the optimal solutions once all the relevant data have been gathered and analyzed. In addition, most of the continuous improvement analysis using quality tools has improved the quality issues but sometimes it has affected the production cycle time. Therefore, by integrating two approaches of motion time study and quality tools, the root causes of the bottleneck issue as well as solving the production shortage can be simultaneously identified and analyzed. The analysis of the classification and the amount of time required to perform a tasks is determined through motion time study while the solution is identified through the application of the selected quality tools, known as Modified Pareto chart, Ishikawa diagram and Failure Mode and Effect Analysis (FMEA). It is then further expanded by adopting a brainstorming approach to identify the optimal solution. The developed integration model is validated through a selected case study. The results obtained from the case study shows that the production output has significantly improved by 10 percent through the reduction in time and processes in completing the assembly work. This has also resulted in improvement in product quality and reduction in the operation costs. © International Journal of Industrial Engineering.