Predictive maintenance is focused on predicting tomorrow’s condition based on today’s data in order to avoid unplanned maintenance and reduce overall maintenance costs.
At its core, it measures asset health through integrated technology applications for the early detection of component failures.
Improve your asset maintenance strategy using best-in-class methods, processes, and technical applications.
Explore our solutions below:
Accelerating digital transformation across your facility to improve asset uptime, bolster safety and increase customer satisfaction at the lowest possible costs.
Providing talent augmentation for your short and long term maintenance and reliability engineering projects.
Need help sourcing and retaining your human capital? Our team of talent specialists can quickly provide strong candidates to fill your skills gaps.
Uplift your teams’ skills. We offer a wide range of certified training curriculum that is oriented to industrial applications for reliability professionals and experts in predictive maintenance in all types of industrial environments.
At I-care, our proven predictive maintenance technologies, services, and diverse asset management solutions ensure industrial machines around the world are more productive, safer, and environmentally friendly.
We service thousands of customers in all major industry sectors including Chemicals, Food, Energy, Materials, Oil and Gas and Pharmaceutical
We are engineers, data scientists, and business leaders driven to improve our client’s asset management performance. Come join us.
Explore our offices and countries where we support our clients.
At I-care, we know maintenance and reliability and are happy to share our knowledge, insights and industrial happenings to assist you on your improvement journey. We welcome you to explore:
Whitepapers
Videos: PdM Expert Talks and Solutions Insights
Success Stories
Technical Case Studies
News and Events
In this whitepaper, you will learn:
What is I-DNA and how it quantifies time domain events such as impacts, bearing and gear defects, slipping, rubbing, severe sliding, mechanical friction, and electrical arcing.
How non-intrusive vibration analysis may be further improved by using sonic and ultrasonic stress wave analysis to detect, quantify, and characterize evidence of tribosystem functionality.
How this stress wave analysis technique extends vibration from mechanical to tribo-mechanical condition monitoring, thereby covering important gaps between vibration and oil analyses.
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