The development in Fourth industrial revolution technologies has significantly advanced the implementation of innovative solutions to achieve manufacturing goals. However, several notable research studies show that the rapid adoption of these technologies has led to research gaps resulting in sub-optimal replication of the full potential in the smart manufacturing scene. These research gaps are largely attributed to the inability to select optimal strategies based of input requirements, output requirements and effectiveness of solutions. This paper aims to close this research gap by assessing definable metrics for evaluation of a communication architecture for smart manufacturing units and run iterations of both these metrics and communication architecture to refine both use cases for future implementation. This paper achieves this by detailing the definition of smart manufacturing and the role of communication architectures in smart manufacturing, detailing the characteristics of evaluation of a fourth industrial revolution communication architecture, comparing multiple architecture-esque implementations and drawing conclusions on how to better these approaches. The results of the paper highlight the importance of design mindsets of reduced latency and contextual awareness in communication of information for Smart Manufacturing Units, which later reveals the true advantages with guided implementations and need for further development to allow for intelligent decision making being largely enabled with the flow and access of information through a network layer approach.