In most of the manufacturing operations, production management staffs usually empirical rules or pilot run experiment results to decide production scheduling. However, the former methodology could go with high risk and uncertainty; the latter might partially verify some schedules and products due to the restricted manufacturing resources, and could easily cause delivery delay. This research performed a design of experimentation by computer simulation tool to develop a micro resistance manufacturing process model and compared the performance measurements among different dispatching rules so as to find the process bottleneck. Meanwhile, this research implemented the TOC (Theory of Constraints) theory to improve the manufacturing process and studied the efficiency of the improved process. This experiment took five performance measurements: product throughout, mean flowing time, mean tardiness time, mean queued job quantity and resources utilization in order to validate the results of the various dispatching rules and its performance simulating the real production process and further expects this model to become a reference scheduling model for batch-typed manufacturing processes. Additional production factors are also included into our experiments. For example, the proportion of product types produced, production timings of orders, manufacturing equipments operation time, numbers of manufacturing equipment and order delivery due date. The experiment results exhibit multi-type products of batch-typed flow shop manufacturing could use different dispatching rules based on product requirements to achieve production optimization and output maximization. TOC and adjustments of bottleneck machines can alleviate manufacturing equipment loading and reduce job queue quantity.