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Wireless Platforms for Smart Manufacturing

Summary:

The Wireless Platforms for Smart Manufacturing project will deliver comprehensive guidelines in the selection, deployment, and optimization of wireless technologies in manufacturing environments. Reliable and secure real-time performance of wireless platforms are challenging problems faced by manufacturers who choose wireless platforms to replace wired platforms due to their ease of installation, maintenance, and reconfigurability. Wireless technology creates enormous potential for manufacturers by increasing the monitoring and control surface of their physical processes. This potentiation for fine resolution monitoring and control also brings with it technical challenges. These challenges include the impact of the unreliable wireless environment on the ability to monitor the processes and adapt quickly. Where wireless is used for control, security, safety, and reliability become chief concerns. Current wireless technologies employed include IEEE 802.11, IEEE 802.15.4, and some proprietary protocols. The key objective for this project is to develop best-practice guidelines for evaluating and integrating wireless technologies into modern factories. The guidelines will include methodology and protocols that will enable, assess, and assure real-time performance of secure wireless platforms in "smart manufacturing" systems. These guidelines will enable manufacturers, technology providers, and solution providers to design, deploy, and assess robust, secure integrated wireless platforms. Manufacturers using wireless platforms from various providers will benefit from a standardized measurement methodology and security guidelines because they can be assured that the wireless platforms for their applications will achieve desired performance requirements and efficiency. 

Description:

Objective - The Wireless Platforms for Smart Manufacturing project will deliver comprehensive guidelines in the selection, deployment, and optimization of the wireless technologies in manufacturing environments. The guidelines will be based on measurement science research to assist manufacturers in selecting and deploying wireless technologies effectively for their industrial applications.

Power Plant

What is the new technical idea? The new technical idea is to develop best-practice guidelines for integrated performance evaluation and wireless technology selection methodology and protocols that will enable, assess, and assure real-time performance of secure wireless platforms in smart manufacturing systems. This will involve the development of performance metrics, measurement science-based methodology, and guidelines that will facilitate the deployment of wireless technologies in the smart manufacturing environment. A smart manufacturing environment will require a variety of wireless technologies to provide seamless connectivity from low-power sensor nodes to high data rate video links.  Standards-based wireless protocols will likely be used for cost reduction purposes.  Even though this project focuses on standards-based wireless protocols used in industrial environments, the metrics, methodology, and guidelines developed could be applied to proprietary wireless protocols as well.

What is the research plan?
Our research will be conducted in multiple overlapping phases. Phase 1 is the radio frequency (RF) measurement phase in which the RF environment in factories is assessed through active and passive measurements. Phase 2 entails the quantification of the factory RF environment as a parameterized statistical channel model representation. Phase 3 is the study of the cyber-physical impacts of the wireless network on the physical systems through simulation. Phase 4 is entails the use of testbed methodologies to study realized wireless networks on physical process performance. Phase 5 is the development of a set of guidelines for selecting and deploying wireless technologies in manufacturing environments. 

Phase 1: This project will begin with the fundamentals of wireless technology. While effective wireless standards for wireless sensor networks such as IEEE 802.15.4 have been developed by industry, few studies focus on the impact of the industrial RF environment or the chosen wireless networking technology on plant performance. Using modern state-of-the-art RF sounding techniques, we will measure RF propagation in partner manufacturing facilities such as an automotive assembly plant or chemical manufacturing plant. We will also measure sources of RF interference and attempt to correlate those interference sources with the happenings of plant operations. This phase of the project will produce high volumes of data on the order of hundreds of gigabytes. We will post-process the raw data to produce complex-valued correlations (impulse responses) that represent the block-box propagation losses and distortions of each sounding scan.  The data will be made available for download. 

Phase 2: The next phase will entail the encapsulation of the RF measurement data into a convenient statistical model. Well-established models exist for RF propagation. We expect that the measurement data of phase 1 to fit within one of the many standard channel models; however, the standard models require precise parameterization to accurately characterize RF propagation in the factory. The channel models will then inform the simulations and testbed activities of subsequent phases.   In addition to channel models, we will also produce packet error rate curves for various IEEE 802.15.4 receiver types. The output of this phase will include packet error rate curves and parameterized channel models. 

Phase 3: Using the raw impulse response data, channel models, and packet error rate curves, we will develop detailed network simulations integrated with models of physical processes. These integrated simulations will allow us to study the impacts of the RF environment and wireless networking technologies on the performance of physical plant processes. We will focus on continuous process control as well as robotic assembly.   

Phase 4: Again, using the raw impulse response data, channel models, and packet error rate curves, we will develop detailed network simulations integrated with models of physical processes. In this case, however, our network models will be realized with actual wireless networking hardware and control infrastructure representing various network and control implementations in factories. We will refer to this as our wireless testbed. The testbed will include continuous processes as well as models of high speed manufacturing processes that involve safety and feedback control over the wireless medium. Rather than abstract RF propagation and interference to packet error rate curves, we will recreate the factory RF environment using an RF channel emulator. The RF emulator is a black box that introduces RF amplitude, phase, and delay distortions by applying a high-speed digital tapped-delay filter to RF transmissions on a link-by-link basis.  In addition to process control and common time-scale robotics, an additional goal is to fabricate a testbed for high speed manufacturing to study the effects of wireless networking on precision time synchronization in the industrial environment. 

Phase 5: In collaboration with universities and industry partners, we will produce a document such as a NIST special publication that may be used by industrial operators, system integrators, and device manufacturers to support the effective use of wireless technologies in smart manufacturing systems. The document will be made freely available.

Major Accomplishments:

Some recent accomplishments for Wireless Platforms for Smart Manufacturing:

  • Produce a Simulation framework to measure the performance of continuous processes where wireless is deployed.
  • Field measurements and channel models is applied to optimize wireless technology selection and configuration in factories.
Robotic Assembly Line

Start Date:

October 1, 2013

Lead Organizational Unit:

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Contact
Rick Candell, Project Leader

301 975 4287 Telephone
301 990 9688 Fax  

100 Bureau Drive, M/S 8230
Gaithersburg, MD 20899-8230