Preventive and Predictive Maintenance in the Processing Industries Through Data Orchestration Analytics

Preventive and Predictive Maintenance in the Processing Industries Through Data Orchestration Analytics
Preventive and Predictive Maintenance in the Processing Industries Through Data Orchestration Analytics

Preventive and predictive maintenance tap the true power of digital twin creation, big data analysis, and dynamic asset management. Yet for many companies in manufacturing, and more specifically in the processing industry, there is still a gap, and managing the maintenance of machines and equipment asks for a disruptive move.

The Waylay data orchestration and analytics platform has been successfully applied across many branches of the processing industries, such as oil and gas, refined chemicals, power generation, and steel production. All Waylay powered solutions have one thing in common: insights through intelligent information processing.

This is enabled from a shift in paradigm, away from the rigid, so-called ‘automation pyramid’ (ISA-95) towards a more service-oriented structure, which defies the former boundaries. It has been enabled through wireless technology, which lowers the sensor provisioning costs. At the same time, we realise that industrial assets become more and more intelligent, creating an abundance of data that shouts out to be orchestrated and analysed. This is where Waylay comes in and plays a key role.


Tapping into multiple data sources

The Waylay orchestration platform makes it easy to bring together different data sources, be it from newly installed industrial IoT gateways, or from more traditional OT systems, such as DCS (Distributed Control Systems), MES (Manufacturing Execution Systems), EAM (Enterprise Asset Monitoring), or from machine log files. Through its patented Bayesian Inference Network (read more about the power of our rule engines here), Waylay is able to weigh multiple, potentially contradicting pieces of information, analyze the data, and trigger insightful actions.


 

Develop data analytics solutions rapidly using the low-code Waylay rule designer

To bring those different data streams together, Waylay has created a visual, intuitive drag-and-drop user interface, that allows a domain expert with no coding experience, to quickly configure business logic, and deploy tasks. It also enables software developers to be significantly faster in developing end-to-end solutions, bringing down the cost of development as well as the TCO (total cost of ownership), and resulting in a faster time to market.

Focussing more narrowly on concrete use cases and examples, Waylay can be applied to validate adherence to a specified set of processing parameters (Temperature, Pressure of utilities) to ensure the correct operation of equipment, as well as monitor, through the application of data analytics, if for instance, the vibration measurements suggest imminent equipment failure. For this, Waylay has a set of tools available, such as the option to include the execution of machine learning models, directly in the Waylay rules (read more about BYOML (Bring your Own Machine Learning) here).

The Waylay solution is not only applied to industrial equipment, but also to the (intermediate) product itself. Using Waylay Machine Learning, by application of advanced algorithms, to model product quality parameters that otherwise have to be verified post-mortem (according to a sampling plan, which often defines hourly sampling intervals), leading to increased product scrap rates and thereby lower yield.

Waylay will not replace an operator’s existing QM (Quality Management) infrastructure. Rather, the implementation of Waylay’s solution should be considered as a valuable addition, that allows the near real-time inline calculation of product parameters, enabling quicker intervention, no longer uniquely relying on post laboratory analysis.


Acting on outcomes

The success of any data analytics project depends on the detection quality, as well as the actionability of the outcome. Waylay offers dashboards for operators or maintenance engineers, where end-users can create their own business rules that lead to alerts, but also goes beyond the "eye-on-the-glass" approach by SMS, call or email notifications, or by interfacing with 3rd party systems, such as a CMMS (Computerized Maintenance Management System), or a business analytics service (eg Power BI), that can consume the Waylay Alarm Service.


Conclusion

The Waylay solution has been successfully applied in various areas within the processing industries, reducing unplanned machine and production outages by up to 53% and increasing manufacturing output by up to 4.5%. Contact us at contact@waylay.io to learn more about your potential savings and to get a product demonstration.

About The Author


Joshua Scharnweber works at Waylay as a Sales Engineer. He is passionate about applying the latest IoT technology to real world customer problems. Following his Chemical Engineering studies at The University of Edinburgh, he also worked on processing industry / plant automation at B.Braun Melsungen and Konica Minolta.

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