Swift Sensors advances predictive maintenance with new trend analytics tools for manufacturing applications


Swift Sensors announced on Wednesday its new predictive maintenance tools for its Manufacturing Analytics Dashboard. These tools add trend analytics to key manufacturing metrics of compliance, utilization, maximum, minimum and average measured values monitored by the wireless sensor system. Eleven new dashboard panels have been added for measuring analytic trends across multiple shifts.

With the new dashboard panels, a trend line is calculated using the best fit line algorithm for the measurement data across each shift. The slope of the trend line represents the trend per shift, which indicates the overall tendency of the analytics value to increase or decrease by a specific amount from one shift to the next.

The trend analytics include a confidence percentage to indicate how well the trend line correlates with the historical data. A high confidence level indicates the trend is more likely to continue. Conversely, a low confidence level indicates the trend is not a reliable predictor of future values because the historical data is too chaotic.

Headquartered in Austin, Texas, Swift Sensors provides a low-cost sensor system for industrial and commercial applications. One of its product – Swift Sensors Cloud Wireless Sensor System – comprises of low-power wireless sensors and cloud-based monitoring, notifications, analytics, and reporting. The sensor system proactively protects and monitors a wide range of equipment and processes. Swift Sensors applications include manufacturing, food service, facility management, cold chain, transportation, research & development, and power.  

“We have deployed more than 100 Swift Sensors in our manufacturing facility to improve operational efficiency,” said Jackson Minear, Continuous Improvement Engineer at Meggitt Airframe Systems. “We use just about every feature in the Analytics Dashboards to track utilization of our equipment as well as critical trends across multiple shifts over time. Conservatively, we’ve improved our machine utilization by 20% while saving six figures in capital equipment expenditures.”

“Our manufacturing customers, particularly those using our wireless temperature and vibration sensors, frequently ask for advanced analytics tools to improve operational efficiency through higher overall equipment effectiveness (OEE) and lower maintenance costs,” said Sam Cece, founder and CEO of Swift Sensors. “With the access to data from our wireless sensor system, Predictive Maintenance (PdM) programs can be easily created using our Manufacturing Analytics tools, which is included in the new Trend Analytics Dashboards.”

Trend analysis is available for compliance, utilization, productivity, average value, maximum and minimum values of individual measurements. Group Trend analysis is available for average compliance, average utilization, average productivity, minimum productivity and total productivity of all compatible measurements inside hardware groups or measurement groups.

The same requirements apply to trend panels as analytics panels. Trend panels for compliance and utilization require measurements with a threshold. Utilization and productivity panels require measurements that output binary values, while the rest require scalar values. Group trend panels have similar requirements and all compatible measurements in the group must also share a time zone.

:We designed our industrial sensor system from the ground-up to be simple to deploy and use,” said Sam Cece, founder and CEO of Swift Sensors. “Our next generation sensors and bridges, using the latest IoT technology from Silicon Labs, will double our wireless communication distance and our battery life, driving mainstream adoption in our industrial markets.”

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