The Industrial Internet of Things (IIoT) describes a computing model where ubiquitous networks of heterogenous devices equipped with embedded sensors and actuators support innovative data-centric business models. Emergent IIoT use cases include Cyber Physical Production Systems (CPPS) to support asset optimization through self-organization of modular machines within production systems. In CPPS, raw materials, machines, and operations are interconnected to form a tightly integrated network.
To ensure manufacturing continuity as CPPS networks evolve, asset managers will need to evaluate risk across multi-disciplinary domains. The domains have different architectures, lexicons, and priorities. To contribute to the eventual codification of data risk in CPPS, this research builds on previous literature to consider how data may traverse the CPPS model. The resulting models put forward in this research are informed by a transdisciplinary panel of experts drawn from disciplines including information and operational technology to bring greater specificity to the definition of business-critical data in supporting IIoT. Based on these expert views, a conceptual hierarchical automation architecture that may characterize many future state production processes is presented.