Proving the Business Case for the Internet of Things

Asset managers should like Clockwork offering

Steve Rogerson
February 14, 2017
 
Texas-based Clockwork has introduced a predictive analytics platform for asset and fleet management. It incorporates machine learning, artificial intelligence and advanced analytics techniques.
 
This should let users develop more accurate, repeatable prognostics for use with condition based maintenance and predictive health management programmes. These can be linked to real-time approaches with longer-term predictive analytics for improved lifecycle management predictions to increase availability, reduce costs and increase profitability of valuable assets.
 
Predictive and prescriptive analytics are increasingly becoming staples in aerospace and defence, manufacturing, and energy industries, in which capital-intensive, strategic assets play an important role in the organisation's success. According to Gartner, by 2020 predictive and prescriptive analytics will attract 40 per cent of enterprises' net new investment in business intelligence and analytics.
 
With this platform, asset managers have a unified toolset to combine asset information from multiple sources, including real-time sensor data and historical data to create accurate, granular long-term predictions on future maintenance requirements and long-term demands on parts, processes and people.
 
Tools for evaluating alternative strategic business cases let users identify and test solutions to future problems, simulate results, and leverage comprehensive reporting to evaluate asset performance, uptime, utilisation and RoI.
 
"We see an increasing shift in organisations seeking to drive down costs and improve productivity of key assets by combining operational and historic data to unlock new insights," said Eric Newman, CEO of Clockwork. “This is especially true in organisations that want to leverage the industrial internet of things but struggle with making sense of the flood of data. This new release combines our proven high-fidelity predictive analytics with the ability to ingest, and make sense of, the massive streams of sensor data that these organisations have spent millions of dollars on. Historically, we have improved asset availability while saving our customers millions of dollars – and this latest release builds on this tradition."
 
Included in the release is a full-featured data flow modeller that enables multi-user collaboration support for modelling and analysis. Improved big data scalability supports larger data sets and increased granularity of simulation results.
 
There is AWS GovCloud hosting support for sensitive data and regulated workloads based on US government compliance requirements including ITar and FedRamp.
 
Enhanced lifecycle modelling capabilities allow for multi-location and multi-echelon maintenance systems to provide more accurate real-world models and simulations.
 
These features and enhancements aim to ensure that users can leverage the value of their real-time and historical data to achieve a comprehensive, holistic view of their strategic assets' future operational and maintenance demands.