Backed by big data, advanced simulations, the Internet of Things (IoT), deep learning, and predictive analysis, Artintech SMPax™ can save millions of dollars by helping experts see the trouble coming. Our Artificial Intelligent systems will predict the possibility of maintenance requirements and help you perform appropriate actions before anything goes wrong.
Intelligent Diagnostic Analysis
Imagine an intelligent system, capturing all of symptoms of defected parts and pieces, and with a high precision, tells you what is not as expected. A pipeline, an engine, or an infrastructure, would have unnoticed defects, resulting in larger damages. It is usually cheaper to do necessary maintenance jobs as soon as a small defect is detected compared to the when the problem turns to a larger damage or in some cases disaster. Using the power of simulation and machine learning, IoT devices and sensors will enable SMPax™ to diagnose smallest fraction and provide maintenance experts with detail diagnostic reports.
While it is good to know what might go wrong soon, it is even better to know what to do to prevent it from happening.
Prescriptive analysis, backed by advanced simulations, machine learning and artificial intelligence, and modern IoT sensor, will provide you with that kind of insight. The reports will provide maintenance experts with guidelines what to do and when to do so, to minimize the possibility of small defects turning to large problems and in-necessary hiccups in your operations.
Explore Artintech SMPax™ Smart Maintenance
Why Artintech SMPax™?
Artintech SMPax™ is a cloud based system. It means that you have safe full access to your system from anywhere in the world and all of the events, movements, changes, and updates, are instantaneously synchronized throughout the system.
Artintech SMPax™ Smart Maintenance accepts and provides API, CSV, and direct connectivity. It means that you connect this system to your other related or legacy systems in the existing processes.
Artintech SMPax™ allows your experts to see the problem before it happens. Intelligent systems, trained by real data and massive advanced simulations, connected to IoT sensors, are all you need to reduce the cost of maintenance to minimum and prevent all damages and disasters.