Manufacturing

Predictive Analytics
for Manufacturing

Maximise utilisation and performance and minimize unscheduled downtime that can disrupt production, service and delivery.

In today’s fast paced market, manufacturing downtime and the release of substandard products can quickly damage your reputation and bottom line.

Version 1 helps asset-intensive organisations keep manufacturing processes, infrastructure and equipment running efficiently to maximise utilisation and performance and minimise costly, unscheduled downtime that can disrupt production, service and delivery.

Predictive Analytics for Manufacturing

Predictive modelling can assist organisations with keeping manufacturing processes, infrastructure and equipment running efficiently to maximise utilisation and performance and minimise costly, unscheduled downtime that can disrupt production, service and delivery.
Utilising Predictive maintenance allows companies to: 

  • Predict asset failure based on usage and wear characteristics
  • Estimate and extend component life
  • Increase return on assets, productivity and lifetime
  • Optimise maintenance, inventory, and resource schedules
  • Optimise assets for better availability, utilisation and performance
  • Prevent Downtime
  • Enhance operations and supply chain processes.

Primary Analytics Solutions for Manufacturing

Design the analytical solution that is best for your business. 

“Analytics gives us a method of assessing impact of factors that we may not be able to measure directly – so that we can do more with the data we already have, instead of making big investments in high-tech equipment.”

Matthiew Lirette-Gelinas, IBM Bromont

“We have already made huge progress in improving root cause identification, optimising operating conditions and reducing operational costs in specific processes.”

Eric Paradis, IBM Bromont

“Our turbines have an alarm built in by the manufacturer which is triggered 30 minutes before a major failure, but with our data, we can predict such an event 30 hours before it happens.”

Erez Daly, Israel Electric Corporation
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Manufacturing Case Studies

Manufacturing
Case Study

Case Study – Daimler Group

Manufacturing | Modeler

Daimler AG was looking for a way to maximize the number of flawlessly produced cylinder-heads by making targeted process adjustments. They also wanted to increase productivity and shorten the ramp-up phase of its manufacturing process. Using IBM SPSS software, Daimler is now able to analyse the plethora of data obtained in the production process and gain deep insights into the key factors that influence product quality.

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Discover More Industry-Specific Solutions

Version 1’s SPSS experts can consult and deliver a wide variety of analytics solutions across a broad range of industry sectors.  Find out more at the links below.

Arrange a free consultation to discuss your analytical needs, and identify the best solution for you.