Programmable logic controllers (PLCs) are an established platform, widely used throughout industrial automation but poorly understood among researchers. This article gives an overview of the state of the practice, explaining why this settled technology persists throughout industry and presenting a critical analysis of the strengths and weaknesses of the dominant programming styles for today's PLC-based automation systems. We describe the software execution patterns that are standardized loosely in IEC 61131-3. We identify opportunities for improvements that would enable increasingly complex industrial automation applications while strengthening safety and reliability. Specifically, we propose deterministic, distributed programming models that embrace explicit timing, event-triggered computation, and improved security.

We study the problem of sequential task assignment and collision-free routing for large teams of robots in applications with inter-task precedence constraints (e.g., task A and task B must both be completed before task C may begin). Such problems commonly occur in assembly planning for robotic manufacturing applications, in which sub-assemblies must be completed before they can be combined to form the final product. We propose a hierarchical algorithm for computing makespan-optimal solutions to the problem. The algorithm is evaluated on a set of randomly generated problem instances where robots must transport objects between stations in a "factory" grid world environment. In addition, we demonstrate in high-fidelity simulation that the output of our algorithm can be used to generate collision-free trajectories for non-holonomic differential-drive robots.

Industry 4.0 is changing fundamentally the way data is collected, stored and analyzed in industrial processes. While this change enables novel application such as flexible manufacturing of highly customized products, the real-time control of these processes, however, has not yet realized its full potential. We believe that modern virtualization techniques, specifically application containers, present a unique opportunity to decouple control functionality from associated hardware. Through it, we can fully realize the potential for highly distributed and transferable industrial processes even with real-time constraints arising from time-critical sub-processes. In this paper, we present a specifically developed orchestration tool to manage the challenges and opportunities of shifting industrial control software from dedicated hardware to bare-metal servers or (edge) cloud computing platforms. Using off-the-shelf technology, the proposed tool can manage the execution of containerized applications on shared resources without compromising hard real-time execution determinism. Through first experimental results, we confirm the viability and analyzed the behavior of resource shared systems with strict real-time requirements. We then describe experiments set out to deliver expected results and gather performance, application scope and limits of the presented approach.

We explore the challenges and opportunities of shifting industrial control software from dedicated hardware to bare-metal servers or cloud computing platforms using off the shelf technologies. In particular, we demonstrate that executing time-critical applications on cloud platforms is viable based on a series of dedicated latency tests targeting relevant real-time configurations.