The Power of Wireless Predictive Maintenance
Technology trends – wireless, cloud & machine learning – are transforming predictive maintenance models while reducing costs and complexity
Our lives are impacted by industrial machines every single day. In fact, everything from the food we eat to the fuel that powers our cars comes from factories. These factories have millions of machines that turn, churn, mix, grind, and transport things. In order to ensure maximize uptime, these industrial machines need to be maintained. Reliability engineers have employed different approaches ranging from reactive to preventive to predictive models over the years.
As an Industrial IoT startup, we’ve created an educational video that maps the benefits and limitations of the most commonly used maintenance models: reactive, preventive and predictive. The aim of this piece is to equip you with all the necessary information around maintenance models to determine an optimal maintenance mix. It also outlines how the emerging trends in wireless, cloud and artificial intelligence technologies are making Wireless Predictive Maintenance, or Wireless PdM, more affordable and scalable than ever. In fact, by leveraging Industrial IoT technologies, factories are changing their asset reliability approach and are transforming themselves forever.
Reactive Maintenance, often referred to as “Run-to-Failure,” is where maintenance is performed only after a machine fails. Although this is the most convenient option upfront, it is also the most unpredictable and expensive model in the long run.
These are some of the limitations of such an approach.
While a run-to-failure model can be feasible for maintaining machines of very low criticality, critical machinery requires a more thoughtful maintenance approach.
Preventive Maintenance, or PM, is a time-based model where maintenance is performed as per predefined repair schedules without considering the actual condition of a machine. With PM, routine maintenance, like greasing and realignment, typically occur on a monthly or quarterly basis. In comparison to the reactive model, PM can prolong equipment life cycles and provide better operational efficiency. However, it can still be a costly approach for several reasons.
The main drawback of Preventive Maintenance is that it involves blindly performing maintenance and repairs without knowing the true condition of the machines. In reality there are countless variables that need to be monitored to determine what a machine needs in order to operate efficiently.
Predictive maintenance, or PdM, involves the monitoring of machine condition to predict developing issues before they escalate. Most applications involve sensors to monitor parameters like vibration, temperature and ultrasound. There are several variations of PdM: Manual PdM, Wired PdM and Wireless PdM.
Also known as a walk-around program, Manual PdM requires the manual collection of sensor data using a data collector to monitor and analyze machine condition.
