This computer code contains the Tennessee Eastman (TESIM) chemical process model to be simulated using hardware-based simulation approaches. The code is optimized for wireless system integration as a part of the NIST Industrial Wireless project. This code allows for integration with external sensor and actuator equipment and the evaluation of operational performance under different wireless scenarios. Disclaimer: Certain commercial equipment, instruments, or materials are identified in this paper in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.

This repository contains code for analyzing industrial wireless sounder measurements and the generation of wireless scenarios. DISCLAIMER: Certain commercial equipment, instruments, or materials are identified in the associated paper (https://doi.org/10.6028/nist.tn.1951) in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.

This repository contains code for analyzing industrial wireless sounder measurements and the generation of wireless scenarios. DISCLAIMER: Certain commercial equipment, instruments, or materials are identified in the associated paper (https://doi.org/10.6028/nist.tn.1951) in order to specify the experimental procedure adequately. Such identification is not intended to imply recommendation or endorsement by NIST, nor is it intended to imply that the materials or equipment identified are necessarily the best available for the purpose.

Cyber-physical systems are systems governed by the laws of physics that are tightly controlled by computer-based algorithms and network-based sensing and actuation. Wireless communication technology is envisioned to play a primary role in conducting the information flows within such systems. A practical industrial wireless use case involving a robot manipulator control system, an integrated wireless force-torque sensor, and a remote vision-based observer is constructed and the performance of the cyber-physical system is examined. The resulting data from the experiments conducted are included in the dataset.

Cyber-physical systems are systems governed by the laws of physics that are tightly controlled by computer-based algorithms and network-based sensing and actuation. Wireless communication technology is envisioned to play a primary role in conducting the information flows within such systems. A practical industrial wireless use case involving a robot manipulator control system, an integrated wireless force-torque sensor, and a remote vision-based observer is constructed and the performance of the cyber-physical system is examined. The resulting data from the experiments conducted are included in the dataset.

Time-sensitive networking (TSN) is an emerging topic for the advancement of wireless networking for industrial applications. TSN, as defined under the umbrella of IEEE 802.1 working group standards, addresses issues related to providing deterministic communications over IEEE 802-based Local Area Networks (LANs). TSN was originally designed to support real-time audio/video applications over Ethernet providing better reliability and lower, more deterministic latency with traffic shaping capabilities. TSN has since expanded its scope and applicability to other applications such as those in industrial environments and automotive. Industrial examples include machine-machine communications for robot control, end-effector actuation, real-time sensing, and safety integrated systems. Applications utilizing an wireless local area network (WLAN) can also benefit from scheduling and traffic shaping as defined in the 802.1Qbv standard; however, factors such as clock stability, synchronization, resource requirements and protocol options come into play when selecting a schedule to support multiple application types on the same network. In this article, we present a scenario for a collaborative robot heavy lift operation, in which, two robots communicate over an IEEE 802.11 WLAN with TSN capabilities to lift a rigid body in three dimensions. Scheduling is performed using 802.1Qbv over WLAN with the robot operating system (ROS) used as the software middleware utilizing the transport control protocol (TCP). As a part of the research, we describe our process for schedule selection to accommodate the time-sensitive traffic of the robotic scenario while allowing an industrial internet of things (IIoT) high data rate traffic to coexist. We then provide an analysis of the impacts of TSN schedule selection on the operational performance of the collaborative robot application. The data provided within this data set was collected as a result of experiments conducted under this research effort.

Time-sensitive networking (TSN) is an emerging topic for the advancement of wireless networking for industrial applications. TSN, as defined under the umbrella of IEEE 802.1 working group standards, addresses issues related to providing deterministic communications over IEEE 802-based Local Area Networks (LANs). TSN was originally designed to support real-time audio/video applications over Ethernet providing better reliability and lower, more deterministic latency with traffic shaping capabilities. TSN has since expanded its scope and applicability to other applications such as those in industrial environments and automotive. Industrial examples include machine-machine communications for robot control, end-effector actuation, real-time sensing, and safety integrated systems. Applications utilizing an wireless local area network (WLAN) can also benefit from scheduling and traffic shaping as defined in the 802.1Qbv standard; however, factors such as clock stability, synchronization, resource requirements and protocol options come into play when selecting a schedule to support multiple application types on the same network. In this article, we present a scenario for a collaborative robot heavy lift operation, in which, two robots communicate over an IEEE 802.11 WLAN with TSN capabilities to lift a rigid body in three dimensions. Scheduling is performed using 802.1Qbv over WLAN with the robot operating system (ROS) used as the software middleware utilizing the transport control protocol (TCP). As a part of the research, we describe our process for schedule selection to accommodate the time-sensitive traffic of the robotic scenario while allowing an industrial internet of things (IIoT) high data rate traffic to coexist. We then provide an analysis of the impacts of TSN schedule selection on the operational performance of the collaborative robot application. The data provided within this data set was collected as a result of experiments conducted under this research effort.

Wireless technology is a key enabler of the vision of the future factory work-cell. Such work-cell will operate autonomously with a high degree of mobility enabled by wireless technology. This model describes the work-cell using the Systems Modeling Language (SysML). Using SysML the structural and parametric characteristics of the work-cell are described. Our model provides the architectural components and performance constraints of the work-cell in which wireless is used for a significant portion of connectivity. It identifies the structural components, interfaces, and data flows. Parametric characteristics that impact work-cell performance are included in the model. Using this model, industrial wireless networking requirements and work-cell behaviors may be developed and performance limits may be evaluated. Note: This dataset is stored in MagicDraw XML format. To open the XML file, MagicDraw 18.4 or higher with the SysML plugin is required. An HTML report is included. To view the HTML report, and browser that supports ActiveX is required.