Overcoming implementation challenges in predictive equipment maintenance
Author : Thomas Mueller | EMEA Director of Sales & Marketing | Shiratech
01 July 2020
Shiratech iCOMOX_580x280
As a powerful element within the industrial IoT (Internet of Things), predictive maintenance of industrial assets in the field can help operators of equipment such as such as turbines, refrigerators, machine tools and HVAC (heating, ventilation & air conditioning) to avoid downtime-related losses.
This article was originally featured in EPDT's H2 2020 IoT & Industry 4.0 supplement, included in the July 2020 issue of EPDT magazine [read the digital issue]. Sign up to receive your own copy each month.
As Thomas Mueller, EMEA Director of Sales & Marketing at Industry 4.0 solution provider, Shiratech tells us, plug-and-play condition monitoring can help companies quickly deploy predictive equipment maintenance within an overall digital transformation strategy…
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 good 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 (artificial intelligence) 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.
Shiratech iCOMOX boxed_580x280
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.
Shiratech’s 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 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. The product is a smart predictive maintenance solution that can boost industrial productivity and enhance safety.
iCOMOX also contains an IEEE 802.15.4e communication SoC that leverages Smart-Mesh 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, and more than 4,000 iCOMOX units have been shipped to date.
Engineering a solution
But 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 newly opened 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. 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 engineering experts at Shiratech’s main office in Israel, and to the wider global network of Shiratech technical centres, to provide a continuous 24/7 service to clients.
Summary
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 to 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.
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