Equipment manufacturers, engineering, procurement and construction (EPC) companies, and power and process plant owners and operators for waste and recrycling commonly face the challenge of keeping their fleet, machinery, and other assets working efficiently, while also reducing the cost of maintenance and time-sensitive repairs.
Considering the aggressive time-to-market required for industrial products and services, it is crucial to identify the cause of potential faults or failures before they have an opportunity to occur. Emerging technologies like the Internet of Things, big data analytics, and cloud data storage are enabling more vehicles, industrial equipment, and assembly robots to send condition-based data to a centralized server, making fault detection easier, more practical, and more direct.
By proactively identifying potential issues, waste and recycling companies can deploy their maintenance services more effectively and improve equipment up-time. The critical features that help to predict faults or failures are often buried in structured data, such as year of production, make, model, warranty details, as well as unstructured data such as maintenance history and repair logs.
By using artificial intelligence models to identify anomalous behavior the information derived from the equipment sensors can be turned into meaningful and actionable insights for proactive maintenance of assets, thereby preventing incidents that result in asset downtime or accidents. Commonly known as predictive maintenance, this added intelligence enables organizations to forecast when or if functional equipment will fail so that its maintenance and repair can be scheduled before the failure occurs.
The Market: North America Tops Market Share
Due to higher spending by recycling companies looking to optimize operating costs and increase profitability, North America will continue to be the biggest market for predictive maintenance solutions. With an estimated market share of 31.67%, North America is expected to grow its predictive maintenance solutions at a CAGR of 24.5%, maintaining its lead from 2017 through 2022. Key players include Bosch, GE, Hitachi, Honeywell and Rockwell Automation, just to name a few.