The Flexible and Dynamic Job Shop Scheduling (FJSSP and DJSSP) have explicit benefits in the new age customized manufacturing environment by ways to efficaciously minimize the maximal completion of all operations on the machines for the efficient performance of the system. This paper seeks to utilize an approach called Social Network Analysis Method (SNAM) to evaluate the identified key machines in FJSSP and DJSSP using Social Network Analysis as a tool and analyzing their impact on the manufacturing system performance. Considering the two important Job Shop Scheduling problems, we propose to build their mathematical models with respect to the constraints and a framework of SNAM to generate the collaboration networks.  The collaboration networks are obtained by transforming the input data and presenting it in the form of an affiliation matrix using network analysis software packages. Eventually, we conducted various tests to analyze the collaboration networks for identifying the key machines whose effectiveness and stability has been determined by multi-objective based hybrid NSGA-II algorithm.