<p>Modern manufacturing industries, particularly those operating under batch-type systems, frequently encounter inefficiencies such as high setup times and low machine utilization due to the handling of small production lots. These issues disrupt steady throughput and lead to sub-optimal use of resources. Cellular Manufacturing Systems (CMS) offer a practical solution by grouping similar machines and components into logical production cells. This work utilizes the similarity coefficient matrix (SCM) method to group machines and parts according to overlapping of processing needs. The methodology involves constructing a binary incidence matrix, computing similarity coefficients between machines, and applying a clustering algorithm to establish manufacturing cells. The resulting configurations were evaluated using key performance indicators which includes machine utilization, grouping efficiency, and the number of exceptional elements. When clustering did not produce clear cell boundaries, heuristic refinements were applied to improve the block-diagonal layout. The proposed SCM-based layout achieved a 40% reduction in material movement and a 13% increase in productivity when compared to the existing layout. The implementation of reorganization of the shop floor according to the SCM-guided cell formation helped the system realize significant reductions in the annual labor costs. This applied consequence highlights on how such an approach can be used to promote efficiency of the workflow in a batch production systems without coerce serious structural modification.</p>