In this special technology white paper, Predictive maintenance: How Data Can Increase Production, you’ll learn why predictive maintenance has become the holy grail for manufacturers trying to predict equipment maintenance needs just in time, thus ensuring that neither breakdowns nor maintenance will slow down production.
Predictive maintenance involves gathering targeted data for analysis, the results of which will help anticipate potential failures before they occur. Companies opt for this type of maintenance to avoid predictable incidents and repair equipment, assembly lines, or machinery with minimum impact on their operations.
Machine operators in particular will find that predictive maintenance quickly helps to reduce downtime. In fact, TIBCO Software has installed a sampling system for a semiconductor manufacturer that collects real-time data on events related to each item of equipment. A software engine learns the sequence of events and, in particular, the sequence that could lead to a problematic situation. As soon as it detects this pattern emerging, it triggers an alarm to let the maintenance teams know that this specific piece of equipment needs to be checked.
A predictive maintenance solution can cut overall maintenance costs by 20 to 30%. This takes into account the cost of the software and offsets it against the costs of all actions and resulting downtime avoided.
The white paper includes the following high level topics:
- Maintenance Made Easy With the Help of Data
- 10% Fewer Outages Bring an Annual Saving of USD 1.4 Million
- The Four Success Factors of Predictive Maintenance
- Kick-start With a POC
- Selecting the Right Tools to Avoid Incidents
- Data Scientist: The Architects of Predictive Maintenance
The Predictive maintenance: How Data Can Increase Production white paper is available for download in PDF from the insideAI News White Paper Library, courtesy of TIBCO Software Inc.
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