Wireless Cyber-Physical Systems Performance Evaluation through a Graph Database Approach.

Despite the huge efforts to deploy wireless communications technologies in smart manufacturing scenarios, some manufacturing sectors are still slow to massive adoption. This slowness of widespread adoption of wireless technologies in cyber-physical systems (CPS) is partly due to not fully understanding the detailed impact of wireless deployment on the physical processes especially in the cases that require low latency and high reliability communications. In this paper, we introduce an approach to integrate wireless network traffic data and physical processes data in order to evaluate the impact of wireless communications on the performance of a manufacturing factory work-cell. The proposed approach is introduced through the discussion of an engineering use case. A testbed that emulates a robotic manufacturing factory work-cell is constructed using two collaborative-grade robot arms, machine emulators, and wireless communication devices. All network traffic data is collected and physical process data, including the robots and machines states and various supervisory control commands, is also collected and synchronized to the network data. The data is then integrated where redundant data is removed and correlated activities are connected in a graph database. A data model is proposed, developed, and elaborated; the database is then populated with events from the testbed, and the resulting graph is presented. Query commands are then presented as a means to examine and analyze network performance and relationships within the components of the network. Moreover, we detail the way by which this approach is used to study the impact of wireless communications on the physical processes and illustrate the impact of various wireless network parameters on the performance of the emulated manufacturing work-cell. This approach can be deployed as a building block for various descriptive and predictive wireless analysis tools for CPS.

Frame-Based Randomized Scheduling of Packets with Random-Deadlines for Multi-Flow Wireless Networks.

The use of wireless communications in industrial applications has motivated various advances in manufacturing automation by allowing more flexibility in installing wireless sensors and actuators than their wired counterparts. The main challenge in industrial wireless deployment is the strict timing and reliability requirements in these systems. Industrial wireless networks are commonly characterized by strict packet deadlines. As a result, Time Division Multiple Access (TDMA) protocols have been widely exploited in various technologies due to their ease of implementation and packet collision avoidance. Moreover, the use of frame-based protocols is motivated by the need for short processing times at the edge nodes of the network. In this work, we consider the problem of scheduling multiple data flows over a wireless network operating in an industrial environment. These flows are characterized by random strict deadlines for each packet following a given probability distribution. Each of these flows may represent the data coming from a sensor to the controller or the control commands from the controller to an actuator. A randomized frame-based scheduling scheme is analyzed where each time slot in the frame is assigned to a data flow randomly.

A SysML Representation of the Wireless Factory Work-cell: Enabling real-time observation and control by modeling significant architecture, components, and information flows.

A fourth industrial revolution, occurring in global manufacturing, provides a vision of future manufacturing systems that incorporate highly dynamic physical systems, robust and responsive communications systems, and computing paradigms to maximize efficiency, enable mobility, and realize the promises of the digital factory. Wireless technology is a key enabler of that vision. A comprehensive graphical model is developed for a generic wireless factory work-cell which employs the Systems Modeling Language (SysML), a standardized and semantically rich modeling language, to link the physical and network domains in such a cyber-physical system (CPS). The proposed model identifies the structural primitives, interfaces, and behaviors of the highly-connected factory work-cell in which wireless technology is used for significant data flows involved in control algorithms. The model includes the parametric definitions to encapsulate information loss, delay, and mutation associated with the wireless network, and it identifies pertinent wireless information flows.

Wireless Network Design for Emerging IIoT Applications: Reference Framework and Use Cases.

Industrial Internet of Things (IIoT) applications, featured with data-centric innovations, are leveraging the observability, control, and analytics, as well as the safety of industrial operations. In IIoT deployments, wireless links are increasingly used in improving the operational connectivity for industrial data services, such as collecting massive process data, communicating with industrial robots, and tracking machines/parts/products on the factory floor and beyond. The wireless system design for IIoT applications is inherently a joint effort between operational technology (OT) engineers, information technology (IT) system architects, and wireless network planners. In this paper, we propose a new reference framework for the wireless system design in IIoT use cases. The framework presents a generic design process and identifies the key questions and tools of individual procedures. Specifically, we extract impact factors from distinct domains including industrial operations and environments, data service dynamics, and the IT infrastructure. We then map these factors into function clusters and discuss their respective impact on performance metrics and resource utilization strategies. Finally, discussions take place in four exemplary IIoT applications where we use the framework to identify the wireless network issues and deployment features in the continuous process monitoring, discrete system control, mobile applications, and spectrum harmonization, respectively. The goals of this work are twofold: 1) to assist OT engineers to better recognize wireless communication demands and challenges in their plants, 2) to help industrial IT specialists to come up with operative and efficient end-to-end wireless solutions to meet demanding needs in factory environments.

A Black-Box Noninvasive Characterization Method for Industrial Wireless Networks.

Industrial control systems are increasingly using wireless communications to improve monitoring and control of industrial processes. In existing installations, distances and costs for installation often prohibit the running of new cables and conduits, making wireless solutions very attractive. With costs reduced, monitoring of the physical process becomes easier, and operators often desire to extend wireless to include supervisory and feedback control. Feedback control, in particular, requires certain reliability, latency, and performance guarantees that are difficult to characterize. Industrial wireless solutions rarely make quality-of-service measurements available at the control system level. When they do, indicators such as per-link packet success rate are often difficult to translate into meaningful metrics useful to the control system designer. This is especially true for multihop mesh network architectures, where it is difficult to translate link performance to system performance. In this paper, we propose a more useful method to characterize true network latency and reliability of a deployed industrial wireless network without the need for physical layer and link layer performance metrics and design knowledge.

Industrial Wireless End-to-End Measurements and Impacts in a Gas-Sensing Scenario.

Industrial wireless is a potential networking solution in many scenarios due to its flexibility and ease of communications in harsh environments. Industrial wireless in gas-sensing and air-quality monitoring applications is essential when wired communications cannot perform the task safely and effectively. A major example of such environments is confined spaces where attaching mobile gas sensors with wires is a major concern for safety and cannot be deployed in some cases. At the National Institute of Standards and Technology (NIST), we developed an end-to-end characterization method for industrial wireless networks. We employed this characterization method to study the end-to-end error and delay performance for a confined-space gas-sensing scenario. We have built the scenario using the NIST industrial wireless test bed, which includes ISA100.11a wireless devices, a channel emulator, and a high-performance programmable logic controller (PLC), where the physical process is simulated. In this work, we studied the effects of the size of the confined space, the relaying, input signal rate, and the impact of the existing workers in the confined space.