System-wide performance analysis of a manufacturing set up helps a company to stay competitive. This can be done by selecting appropriate performance analysis tool which can save time and money. Among them, the most important way to scientifically study the behavior of assembly line systems is modeling. As a problem assembly line systems are difficult to completely model and analyze using either of analytical or discrete-event simulation model. The main objective of this study is to analyze the distinct modeling capabilities of analytical modeling approach and DES approach so as to take their respective primacy for analysis of particular pertinent parameters suitable for TC assembly line industries. For the successful accomplishment of this study two main types of data sources are used. These are secondary data and primary data sources. Secondary data sources are books, journal articles and magazines that is essential to get essential basic information about the two modeling approach and their applicability in the manufacturing system especially in assembly line systems. Primary data sources such as operational time recording using stopwatch and site observation are used to obtain the production process operational time and the layout of the production process. The recorded data is transformed to input distribution by using fitted probabilistic analytical model. Both analytical and discrete-event simulation models are developed for TC production process using G/G/C and AnyLogic software respectively. The results from the two models for work in process, queue cycle time, cycle time and resource utilization have high degree of agreement. As a major finding attach fraud prevention is identified as bottleneck point of the system. By making reassignment of operators from the idle stage to the bottleneck stage the system waiting time and work in process is reduced by 12% and 13% respectively from the proposed model.