Asset-intensive industries rely on reactive maintenance which can cause unplanned downtime, negatively impacting customers and finances. While preventative maintenance has helped, predictive maintenance using data from sensors and systems can further improve uptime, productivity, and performance. Predikto's cloud-based predictive analytics software called MAX ingests diverse data sources to calculate accurate predictions for asset failures. It provides lead time for actions to prevent downtime with over 90% accuracy. This improves operations and reduces inventory and maintenance costs for customers.

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Asset-intensive industries
(Transportation, Oil & Gas, Metals,
etc.) rely upon reactive or scheduled
maintenance; unplanned downtime (or
even scheduled, which may not be
actually needed) can adversely impact
customers and financial performance.
While companies introduced more
effective preventive maintenance
measures over the years, there is
strong evidence that new predictive
maintenance capabilities make an
even greater difference to improving
uptime, productivity, manufacturing
quality, and operational performance.
With the growth of the Industrial IoT
(Internet of Things), plant equipment,
and even vehicles, are entering a new
era of use designed to connect to
other devices & systems to share
information. Organizations generate
large volumes of data (AKA “Big
Data”) from equipment sensors,
maintenance systems, and other
disconnected sources, but until
recently these operational systems
lacked the ability to predict future
events, like asset failures. As
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experience continues to show, there is
a missing link to operations and
executives in combining all of this
relevant data and turning into
actionable intelligence for the people
to whom it matters most.
Predikto, a Cloud-based, predictive
analytics software company, has
developed a unique solution to
maximize the accuracy of automated
predictions for your organization.
Through the development of MAX, an
intuitive, machine learning engine, we
have delivered a product to rapidly
ingest large amounts of data from
diverse sources to calculate highly
accurate predictions for complex
problems and to deliver actionable
solutions quickly.
Our Time-To-Value concept buffers
everything that has been created
through the Predikto solution,
providing customers the acceptable
amount of lead-time to react to
adverse situations and preventing
unanticipated downtime. Multiple,
sophisticated algorithms are used in
analyzing customer’s exact data to
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provide companies the best outcome
available. With accuracies above the
90% mark, our customers are
experiencing significant
improvements within their
operations, based on data that is
already being gathered within the
organization.
Who has time for unplanned failures
and downtime? Do you really need
tens of millions in MRO inventory? Is
yours increasing? Consider Predikto
and our SaaS-based, ready to use
solution and improve your company’s
performance by taking action and
seeing results in weeks, not months.
Predictive Analytics for Asset Maintenance
22%increased uptime
at a
CPG plant
$13Mof savings per year by
reducing false-alarm trips
for a major rail carrier
90%accuracy predicting
battery failure for a
Tier 1 supplier
11%improvement on
manufacturing yield
for a steel company
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info@predikto.com
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