sensor networks in intel fabrication plants
The deployment of large-scale sensor networks in industrial environments presents technical challenges in achieving ease of deployment, flexibility in operation, and overall commercial viability. Sensor deployments are characterized by non-uniform placement of nodes, intermittent node connectivity, and the aggregation and reliable transfer of a large amount of data as networks scale to larger and larger sizes. Operation challenges include efficiently utilizing battery powered nodes, dynamically selecting sample periods and equipment clusters of interest, integrating with existing sensing and analysis infrastructure and easily correlating faults identified by the sensor network back to key factory operations and equipment. Commercial aspects involve returning value to the organization with hardened network nodes and reliable network operation that easily justifies the sensor network deployment and operating costs. We will demonstrate a sensor network in the ultra-pure water facility of an Intel fabrication plant, including details on the fab vibration application, the hardware nodes, and the heterogeneous wireless network. The fab vibration application uses vibration analysis to predict and correct equipment failures before fab operations are impacted. The ultra-pure water facility has a diversity of pumps and metal infrastructure both in a gymnasium size room and in an outside open air area that require 51 nodes with 201 vibration sensors. Data samples of 6K bytes are taken periodically from each vibration sensor, forwarded to a central server, measured for velocity, spike energy, acceleration, and displacement, analyzed with FFTs and trend analysis, and compared against expected profiles. When the analysis detects vibration variations outside of normal operating parameters, the affected equipment is scheduled for preventive maintenance, and repairs are made during normal down times. The hardware nodes for the fab vibration application include battery-powered motes (Figure 1(a)) and line-powered gateways. The motes are powered by four C Cell batteries, use a 900 MHz transceiver, and support an RPM (Revolutions per Minute) sensor and up to six vibration sensors. The gateways contain both a 900 MHz transceiver and a 2.4 GHz transceiver running 802.11b to bridge the sensor radios to the 802.11 network. Both motes and access points use heavy metal housings and are hardened for industrial use. Motes and gateways self configure into a heterogeneous wireless network on power up. Motes form an ad hoc network and cluster to gateways. Gateways form an ad hoc 802.11b overlay network and provide high-capacity data transport allowing us to scale the network. One of the gateways is connected to the corporate network through Ethernet. The motes are cycled through planned sleep and wake periods to alternately conserve power and perform vibration data acquisitions. Motes send the data to the gateways where it is aggregated and ultimately forwarded to a server for analysis and storage. Our demonstration includes the display of actual vibration data with real time updates from an Intel fab, together with hands-on samples of gateways, motes, vibration sensors, and RPM sensors used in the deployment. Overview of the network topology and physical deployment is also shown along with the key network technologies developed and used to run the vibration application. We also discuss current learnings from the deployment and future work.
sensor networks vibration analysis predictive maintenance