Predictive maintenance is a topic we’re hearing more and more about, as it offers a simple way to leverage new technologies to optimize a company’s operations and production line in line with Industry 4.0.
To help you better understand what it entails, here are the five most frequently asked questions about predictive maintenance.
#1 Is My Business Too Small to Implement Predictive Maintenance?
There is no minimum or maximum size requirement for predictive maintenance. You can even use it to simply monitor your water heater at your vacation home if you’d like!
However, we recommend considering predictive maintenance if you have one or more critical pieces of equipment — such as a pump, a refrigeration system, a fan (risk of overheating), etc. If a breakdown is expensive, predictive maintenance is profitable.
#2 How Many Sensors Are Needed?
Once again, there’s no one-size-fits-all answer. The beauty of a predictive maintenance solution like the one offered by Soralink is that it’s 100% tailored to your needs.
We often recommend starting with the most critical assets to prove value quickly — an MVP (Minimum Viable Product) approach. Our trial offer includes sensors to monitor your most essential machines. That’s a good starting point if you want to truly experiment with machine learning and take full advantage of predictive maintenance.
#3 What Types of Data Can Predictive Maintenance Analyze?
Predictive maintenance allows for the monitoring of various factors. The most common are:
- Sound (ultrasound detection)
- Temperature
- Vibration (3-axis)
These three alone detect the majority of mechanical failures in rotating machinery such as motors, fans, and gearboxes.
#4 How Much Does It Cost?
First, consider the upfront cost. Some service providers require you to purchase the entire solution upfront, while others — like Soralink — offer a monthly subscription. The key advantage of a subscription model: you can start right away without a large capital investment.
To calculate the true cost of predictive maintenance, you need to be completely honest about what you’re currently paying in indirect maintenance costs:
- Production delays
- Overtime following a breakdown
- Rush shipping fees for repair parts
Since the goal of predictive maintenance is to eliminate these indirect costs, you’re very likely to come out ahead. Soralink’s customers report saving an average of 30% on their maintenance costs by switching to predictive maintenance. How much would that 30% savings amount to for your business?
#5 How Can Your Solution Predict Breakdowns and Malfunctions?
Predictive maintenance uses data to determine when a machine will require maintenance, before a breakdown occurs. Here’s how:
Data Collection
Sensors continuously collect real-time data on the performance and operating conditions of your equipment.
Data Analysis
The collected data is analyzed using advanced algorithms, machine learning, and artificial intelligence. This identifies trends or anomalies that may indicate potential future issues.
Alerts and Notifications
When predictive models detect an imminent risk of failure, alerts are generated for the maintenance team. This allows them to plan and perform the necessary maintenance before a failure occurs — reducing unplanned downtime and associated costs.
Continuous Optimization
Predictive maintenance models are continuously refined as new data is collected. This allows maintenance strategies to be optimized over time, maximizing equipment availability while minimizing costs.
When it comes to maintenance, there is no one-size-fits-all solution. However, the experts at Soralink would be happy to discuss your challenges and your specific situation to see how predictive maintenance can be applied to your business.