In today's competitive manufacturing landscape, operational excellence is vital. Continuous production depends on optimal machine performance to meet high demand. Unplanned downtime threatens revenue. This paper presents a case study of Reliability, Availability, and Maintainability (RAM) analysis of a machining line with 14 machines at an engine manufacturing plant. The analysis aims to address frequent machine failures and improve reliability and availability, enhancing overall plant efficiency. To perform the RAM analysis, comprehensive failure and maintenance time data for all machines were collected over the past year. After data collection, thorough cleaning and analysis techniques were applied to evaluate various statistical parameters of the reliability and maintainability models. Given the non-exponential failure and repair distributions, Semi-Markov Process (SMP) modelling was employed for availability assessment. The analysis computes RAM indices for all machines, offering insights into their current operating status. It includes a comparative study of machine failure frequencies and examines availability, maintainability, and reliability features for different machines in the production facility. It also presents reliability versus time plots for individual machines and the entire machining line. These results guide identifying critical machines, optimizing maintenance practices to minimize downtime, and provide insights for exploring Reliability-Centered Maintenance (RCM) strategies.