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www.us-
tech.com Overcoming the Challenges of Implementing Predictive Maintenance By Thomas Müller, Director of Sales and Marketing — EMEA, Shiratech P
redictive maintenance of assets in the field can help operators of industrial equipment to significantly reduce downtime and related
losses. From the equipment provider’s standpoint, predictive maintenance raises the opportunity to build closer, service-based relationships with cus- tomers and to eliminate the relatively high costs of emergency repairs. Maintenance activities can be planned more
efficiently, any deteriorating components identi- fied in advance and remedial work scheduled to take place when the machine is least active, like during the night or between shifts, to minimize the impact on operations. If replacement parts are needed, these can be ordered in time, at favorable purchase and delivery rates, and the service team can prepare in advance to carry out the work.
Implementation Challenges Cloud services are readily available to ana-
lyze equipment health data, such as vibration, temperature or audible indicators. Using such methods as pattern analysis and threshold moni- toring, machine-learning artificial intelligence (AI) applications can assess the health of components,
Plug-and-play condition monitoring can help companies quickly deploy predictive equipment maintenance within an overall
digital-transformation strategy.
such as bearings or mechanical structures. A rising temperature trend, or matching an
iCOMOX equipment monitoring modules.
Any combination of inertial, acoustic, magnetic, pressure, and temperature sensing may be required, with signal processing and local intelli- gence to filter and aggregate the data. However, integrating these various elements
to create a robust solution capable of withstanding the harshness of an industrial environment demands significant engineering effort. In addition
audio or vibrational signature, for example, can be used to detect impending failure, generate an alert and even predict the time that the failure is likely to occur. Implementing predictive de pends on the abil-
ity to remotely monitor equipment condition fre- quently and accurately. Dedicated sensors must be attached to equipment in the field to capture data.
to sensor design competencies, skills in edge com- puting, wireless communication and networking are also required.
Intelligent Condition Monitoring A plug-and-play platform that contains the
required sensors and signal-chain components, as well as processing and wireless network connectiv- ity already built-in can help bypass the intrinsic low-level engineering challenges. This allows the project to be focused on the data science that drives service creation. The Shiratech iCOMOX intelligent condition
monitoring box offers a solution. As an open embedded sensor-to-cloud platform, built around an ARM®-based application processor, iCOMOX integrates two low-noise, low-power, three-axis accelerometers for vibration sensing, a 16-bit tem- perature sensor, a magnetic field sensor, and a MEMS microphone that has high dynamic range, low distortion and flat frequency response for excellent performance in diagnostics applications. The device also contains an IEEE 802.15.4e
communication SoC that leverages SmartMesh™ IP to support robust and scalable communications over extended distances in tough industrial envi- ronments. Shiratech also has a SmartMesh IP gateway
that provides sensor-to-cloud connectivity. Alter - natively, iCOMOX can function as a standalone sensor if required. More than 4,000 iCOMOX units have been shipped to date. Even with a box like this, the solution is not complete without the engineering support needed
Continued on next page
June, 2020
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21241 S. Western Ave. Suite 140 Torrance, CA 90501 Phone: (310) 540-7310 Fax: (310) 540-7930
23785 Cabot Blvd. Suite 306
Hayward, CA 94545 Tel: 510-293-0580 Fax: 510-293-0940
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