From keys and kitchen appliances to suspension bridges and planes, metal production is responsible for so many things in our world. It is impossible to imagine our industry without it. But behind all the stainless steel fridges there are metal production and processing machines – CNC machines, press brakes, and plate rolls. 

Ensuring that these machines work properly ensures that our economy runs smoothly.

This is why predictive maintenance in the metal industry is so crucial from cutting costs, improving productivity, and reducing downtime.

Predictive maintenance

First, let’s see what predictive maintenance is.

Predictive maintenance is a technique that uses data collecting from machinery and equipment and advanced analytics to prevent downtime and chances of a breakdown

There is not a singular technology that enables predictive maintenance. Rather it encompasses different condition-monitoring technologies and tools to get data on the state of the machinery and determine how well it is performing.

Depending on the industry the tools and techniques change. For some, it is various temperature and humidity sensors, for others it’s tracking the energy consumption, or measuring the vibrations.

It is important to remember that in metal processing and production there are both:

  • Mechanical changes
  • Chemical changes

This means that monitoring the production process gets more complicated than in other industries. Which in turn, makes IoT and AI the best ally for proper predictive maintenance solutions.

What are the advantages of predictive maintenance in the metal industry?

metal industry Zerynth advantages to predictive maintenance

According to a McKinsey study, predictive maintenance usually decreases between 30% to 50% of equipment downtime in industries. Not a small percentage. And the cost saving is evident for the metal industry, where any type of downtime negatively affects not only the product itself but also all the correlating processes, as well as other industries which depend on metal.

The same study states that predictive maintenance can increases machine life by 20 to 40 percent. Furthermore, with the current chip shortage, and the supply chain problems, predictive maintenance is helping companies get insight into when they need to order important replacement parts.

Another important aspect, especially these days, is how predictive maintenance can enable energy saving. Running inefficient machines can cost you more than you think – and proper monitoring can pinpoint where you can cut down on energy consumption (and costs). For example, simple bearing wear can cause the machine to spend more energy than an optimally working one.

So, again, the impact on productivity and costs is more than clear.

Here’s a list of the main benefits:

  • Reduction in maintenance costs
  • Reduced downtime
  • Direct impact on the OEE
  • Increased productivity
  • Lower energy costs
  • Better production planning
  • Increased workplace safety

Prevention of machine downtime

A good place to start is the road to reduce downtime to identify the most common reason it happens:

  • Human error
  • Equipment breakdown
  • Unavailable resources

This is why real-time visibility of the processes on the shop floor is vital for preventing downtime. Again, we circle back to the fact that IoT solutions are the thing to turn to. In other words – a data-driven approach.

With an appropriate IoT solution a company can easily track assets, resources, and the machinery, and get all the important information in the right time. All you need to do is install the right sensors on the assets and machines and place all the data dashboards. This way the shop floor manager can make better-informed decisions, and notice certain patterns that indicate upcoming downtime or breakdown of machinery.

Monitoring production in harsh environments

Metal processing is a harsh environment to work in, especially if it involves metal melting, smelting, and casting.

There are numerous dangers for workers in the metal industry – from high temperatures and chemical evaporating in the air, to heavy equipment.

But the condition of the machinery needs to be considered as well. For example, both the metal materials that are being processed and the machinery is in danger of corrosion. These factors should be monitored if you want to reduce the level of corrosion in the shop floor:

  • High temperature
  • Temperature changes
  • Chemical processes

In any case, having reliable equipment means having a safer work environment.

Conclusion

With predictive maintenance you can identify potential machinery and equipment breakdown, and avoid more complex, and costly problems. If you don’t know where to start, contact our team.