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Today’s manufacturing facilities and processes offer the potential to collect data on an unprecedented scale. However, conventional Programmable Logic Controllers are often proprietary systems with closed-source hardware and software and not designed to also take over the seamless acquisition and processing of enormous amounts of data. Furthermore, their major focus on simple control tasks and a rigid number of static built-in I/O connectors make them not well suited for the big data challenge and an industrial environment that is changing at a high pace. This paper, advocates emerging hardware- and I/O reconfigurable Programmable System-on-Chip (PSoC) solutions based on Field-Programmable Gate Arrays to provide flexible and adaptable capabilities for both data acquisition and control right at the edge. Still, the design and implementation of applications on such heterogeneous PSoC platforms demands a comprehensive expertise in hardware/software co-design. To bridge this gap, a model-based design automation approach is presented to generate automatically optimized HW/SW configurations for a given PSoC. As a case study, a metal forming process is considered and the design automation of an industrial closed-loop control algorithm with the design objectives performance and resource costs is investigated to show the benefits of the approach.