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The performance of a manufacturing system can be measured by many criteria. Some commonly used evaluation criteria are lead‐time, variants, and volumes of products, as well as cost (Bi et al. 2008). Manufacturing technologies have advanced greatly to optimize system performances. Figure 1.5 gives a taxonomy of available enabling technologies in terms of the strategies, domains, and product paradigms of businesses to optimize systems against the aforementioned evaluation criteria. In the implementation of production, the majority of advanced technologies, such as CIM, FMS, Concurrent Engineering (CE), Additive Manufacturing (AM), and Total Quality Management (TQM), are enabled by CATs.

Figure 1.5 The strategies, domains, and production paradigms of advanced manufacturing technologies (Bi et al. 2008).

The advancement of CATs can be measured by their capabilities in dealing with the growing scales and complexities of systems and the autonomy of system responsiveness. Figure 1.6 shows the evolution of CATs from the perspective of these three measures (Bi et al. 2014), together with computer applications in manufacturing using numerical control (NC)/CNC workstations, FMSs, CIM, distributed manufacturing (DM), and predictive manufacturing (PM). Typical computer aided tools to support these enabling technologies are Quality Control (QC), TQM, Enterprise Requirements Planning (ERP‐I), Enterprise Resources Planning (ERP‐II), Product Lifecycle Management (PLM), Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), respectively. Correspondingly, the capacities of software systems to deal with volume, variety, and velocity of the data have been increased gradually from stream data early in the digital era to big data now. IT hardware systems must be capable of processing data in a timely manner. The computing environments have evolved from Microchip, mainframe, servers, the Internet, to today's Cloud.

Figure 1.6 Evolution of computer aided technologies in manufacturing (Bi and Cochran 2014).