Plug-and-play iCOMOX help companies quickly deploy predictive equipment maintenance as part of a digital transformation strategy, reducing maintenance costs, increasing the OEE (Overall Equipment Effectiveness) and saving money as a result.
As a powerful element within digital transformation, predictive maintenance of assets in the field can help operators of industrial equipment such as such as turbines, refrigerators, machine tools, and HVAC to avoid downtime-related losses. From the equipment provider’s standpoint, predictive maintenance raises the opportunity to build closer, service-based relationships with customers and eliminate the relatively high costs of emergency repairs.
Maintenance activities can be planned more efficiently, any deteriorating components identified in advance, and remedial work scheduled to take place at a time the equipment is least active such as at night or in between shifts to minimise the impact on the customer’s operations. If replacement parts are needed, these can be ordered in time, at favourable purchase and delivery prices, and the service team can prepare in advance to carry out the work.
Implementation Challenges
Cloud services are readily available to analyse equipment-health data, such as vibration, temperature, or audible indicators. Using techniques such as pattern analysis and threshold monitoring, machine-learning AI applications can assess the health of components such as motor bearings or mechanical structures. A rising temperature trend, or matching an audio or vibrational signature, for example, can be used to detect impending failure, generate an alert, and even predict the time the failure is likely to occur.
Implementing predictive maintenance depends on the ability to remotely monitor equipment condition, frequently and accurately. Dedicated sensors must be attached to equipment in the field, to capture the data needed. Any combination of inertial, acoustic, magnetic, pressure, and temperature sensing may be required, with signal processing and local intelligence 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 to sensor design competencies, skills in edge computing, 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 embedded processing and wireless network connectivity already built-in can help bypass the intrinsic low-level engineering challenges and let the project focus on the data science that drives service creation. The Shiratech iCOMOX intelligent condition monitoring box offers an ideal solution.
As an open embedded sensor-to-cloud platform built around an Arm®-based application processor, iCOMOX integrates two low-noise, low-power 3-axis accelerometers for vibration sensing, a 16-bit temperature 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.
iCOMOX 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 environments. Shiratech also has a SmartMesh IP gateway that provides sensor-to-cloud connectivity. Alternatively, iCOMOX can operate as a standalone sensor if required. More than 4000 iCOMOX units have been shipped to date.
Engineering a Solution
Even with a box like this, the solution is not complete without the engineering support needed to configure and implement complete end-to-end condition monitoring. Shiratech’s European technical and sales office near Frankfurt in Germany provides easy access to the required services including tailored design and manufacturing of integrated hardware and software solutions. The services available also include supply-chain management, Design for Manufacture (DFM), and production and logistics expertise.
Together, they enable customers to enjoy faster turnaround and shorter time to completion for their projects. The team in Germany is also closely connected to experts at the main office in Israel, and the wider global network of Shiratech technical centres, to provide continuous 24/7 service to clients. In other words: iCOMOX is the right tool to ensure your machines keep running.
Conclusion
Predictive maintenance based on intelligent equipment-condition monitoring enables companies to minimise waste and avoidable costs. Success requires skills in embedded hardware design, edge computing, Industrial Internet of Things (IIoT) connectivity, and cloud-based data analysis to come together to capture, pre-process, and analyse sensor data – and thus derive accurate insights into machine health and correctly anticipate maintenance needs.
Shiratech’s iCOMOX module, IIoT gateway, and technical services can simplify implementation, providing a faster route to reaping the rewards of digital transformation. It helps manufacturers increase up time, reduce maintenance costs and improve factory yield, therefore saving money.
