Predictive Maintenance

Increase equipment lifetime and control maintenance operations costs in the manufacturing industry with artificial intelligence adoption in real time

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What is AI based Predictive Maintenance?

Engineer controlling industrial machine using a tablet with control panel interface

AI-driven predictive maintenance is a solution that uses complex machine learning algorithms and deep learning to reliably predict potential equipment failures 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.

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.

Features

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 in real time.

Trends & correlation

identify complex relationships between process parameters and the condition of asset health with artificial intelligence and machine learning advanced analytics.

Seamless integration

integrate TT PSC's AI based predictive maintenance solution with any existing systems and enable automated monitoring and detection of operational patterns to maximize equipment uptime and maintain critical assets by avoiding potential failures.

Real-Time Monitoring & Alerts

create alerts indicating the remaining useful life of assets based on AI and machine learning 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.

Predictive maintenance is based on machine learning and artificial intelligence- benefits for maintenance work

Increased OEE and equipment lifetime

Maximized Equipment Uptime

Reduced maintenance costs

Better Spare parts inventory planning

Avoid and minimise unplanned downtime

Enhanced the power of safety

Screenshots

Analizuj ogromne ilości danych z zasobów, systemów i czujników w celu wykrycia nieprawidłowego działania

Proaktywne wykrywanie problemów związanych z procesem produkcyjnym i awariami sprzętu

Lepsza kontrola jakości procesów dzięki zastosowaniu uczenia maszynowego

Want to know more?

We want to be sure we understand your needs and can help you.

Don't hesitate to contact us and tell about your needs.

Take proactive steps to effectively predict issues and save costs

This powerful tool helps you reduce downtime and maintenance issues by providing AI based predictive maintenance insights and machine learning predictive analytics.

It keeps an eye on maintenance operations, estimates asset performance, and ensures equipment effectiveness with advanced analytics.