_Predictive Maintenance solution

Increase equipment lifetime and control maintenance operations costs in the manufacturing industry with AI adoption

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_Business challenges

High maintenance costs
Maintenance activities consume a significant portion of most industrial companies' budgets - labor, equipment, and spare component costs, or ongoing costs. They significantly increase operating costs and reduce profit margins if they are not managed effectively.
Lack of profound process understanding
Understanding the correlations resulting from the machines, materials, parameters, or practices used in a process must be supported by proper analytical techniques and historical data.
Machine failure and unplanned stoppages out of control
Traditional maintenance methods fail to effectively predict and prevent the occurrence of critical breakdowns on production lines, which can result in uncontrolled increases in financial and time costs, but also in risks to worker safety.
Strive to maximize the efficiency of machines on the production line
Unexpected failures on the production lines are a consequence of a lack of sufficient manufacturing process analysis. Analyze and control real-time data to monitor the machinery's performance, optimize and improve efficiency, and consequently predict and prevent asset failures.

_What is AI based Predictive Maintenance?

Predictive maintenance solutions with meaningful insights
AI-driven predictive maintenance is a solution that uses complex machine learning algorithms and deep learning to reliably predict potential equipment failure before it happens and supports asset reliability.
Deliver actionable insights in manufacturing operations by harnessing sensor data. This approach empowers classical reactive and preventive maintenance models with AI-based machine learning technology that leverages historical assets and process data to make more accurate and intelligent decisions.

_Machine learning-based predictive maintenance benefits for maintenance teams

Increased OEE and equipment lifetime
Maximized Equipment Uptime
Reduced maintenance costs
Better Spare parts inventory planning
Avoid unplanned downtime
Enhanced safety


Smarter maintenance decisions
our advanced machine learning algorithms analyze data from all sources, identify anomalies, and predict failures before they occur - by training data helps your maintenance teams make the right decisions for optimum maintenance.
Trends & correlation
identify complex relationships between process parameters and the condition of asset health with artificial intelligence advanced analytics.
Seamless integration
integrate TT PSC’s predictive maintenance solution with any existing systems and enable automated monitoring and detection of operational patterns to maximize equipment uptime and maintain critical assets.
Real-Time Monitoring & Alerts
create alerts indicating the remaining useful life of assets based on AI technology and be able to continuously be monitoring of machine performance on the shop floor.
Prevent equipment failures
define and detect critical points on the production line and get real-time recommendations long before issues and unplanned downtime occur to support maintenance schedules.


_Take proactive steps to effectively predict issues and save costs

This powerful tool helps you avoid costly downtime and maintenance issues by providing predictive insights. It keeps an eye on maintenance operations, estimates asset performance, and ensures equipment effectiveness.


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