In the industrial field, corrective and preventive maintenance have played an essential role in guaranteeing the efficient operation of equipment and extending its useful life. 

However, thanks to technology advancements and the advent of Industry 4.0, we currently have better alternatives for process optimization. Enter predictive maintenance.

In this article, we will explain what predictive maintenance consists of, highlighting its main differences from other types of existing equipment protection. In addition, we will analyze its operation and the advantages it can provide to your industrial heating equipment.

What is Predictive Maintenance?

Predictive maintenance can be defined as a series of actions and measurements that are applied to anticipate equipment or machinery failures.

This approach can identify patterns that suggest system or process errors, allowing us to anticipate and act accordingly. This could include scheduling interventions to correct any problems that may arise, before addressing the problem becomes more expensive.

Differences Between Predictive, Preventive and Corrective Maintenance

Predictive maintenance differs from preventive and corrective maintenance by focusing on the early detection of equipment failure, with the aim of preventing unexpected damage, avoiding production stoppages and, consequently, resulting in greater efficiency and long-term cost savings.

Corrective maintenance, also known as ‘reactive maintenance’, involves repairing equipment after a failure.

Preventive maintenance is based on inspecting the equipment regularly to avoid breakdowns and to minimize wear and tear on furnaces, kilns, ovens, and dryers.

Each type of maintenance has its advantages and can be implemented alongside one another in order to optimize processes.

Find out about our NUTEC Bickley specialized technical services and keep your industrial heating equipment in the best condition.

How Does Predictive Maintenance Work?

This type of maintenance is based on the storage, monitoring, and analysis of data and quantifiable equipment variables in real time, such as temperature, vibration, and frequency, among others.

Remember that it is necessary at the outset to understand the processes thoroughly and identify which aspects need to be analyzed, to make this approach work. These aspects include:

• Temperature. Monitoring the temperature may reveal abnormal changes indicating possible overheating or component failure.
  
• Vibration. Unusual vibration may indicate machinery wear or imbalance, resulting in more severe damage if not addressed in time.
  
• Frequency. Analyzing particular patterns and behaviors can provide an insight into what may evolve into future potential problems.

Measurement & Detection Control Systems

Sensors and algorithms constitute the primary variable measurement and problem detection systems.

On the one hand, sensors play a fundamental role in predictive maintenance, as they can detect subtle changes in the equipment's performance, making it possible to identify potential failures before they occur.

At NUTEC Bickley, we have a vast catalog of recognized sensor and spare parts brands, allowing you to measure your equipment's required variables.

On the other hand, algorithms identify patterns and trends indicative of possible issues by processing large data amounts, allowing timely and planned interventions.

Factors influencing measurement time

The time it can take to measure variables during a predictive maintenance process depends on many internal and external factors. Below we address some of them.

External factors

• The process. Each industrial procedure has its characteristics and requirements. For example, constant and real-time monitoring might be required in a continuous process, while a specified intervals approach might be best in other situations.
  
• The product. Some products may require frequent or strict monitoring due to their nature and characteristics.
  
• The customer philosophy. Some customers may have stricter standards or request more frequent monitoring to ensure the quality and reliability of their products.

Internal Factors

• Capacity. Strategic planning and scheduling measurements may be necessary if the equipment is limited or employed for other processes.
  
• The availability of qualified personnel. Ensuring that qualified staff are available at the right time to interpret the data obtained is crucial.
  
  

Advantages of implementing Predictive Maintenance

Predictive maintenance offers a series of significant advantages. Some of them are as follows:

• Cost reduction. Predicting and preventing failures avoids costs associated with unplanned downtime and repairs.
  
• Increased uptime. By anticipating failures, you can maintain continuous production and minimize interruptions to your operation.
  
• Improved equipment lifespan. Fixing problems on time helps to avoid premature wear.

Conclusion

Predictive maintenance is a maintenance strategy that uses data and analytics to predict when equipment will fail. Identifying potential problems before they occur can help organizations optimize equipment efficiency, maximize the equipment’s useful lifespan, and reduce repair and replacement costs.

If you have experienced frustration by dedicating a large portion of your budget to solve unforeseen problems, suffered production losses, or faced difficulties meeting the delivery deadlines of your products, then predictive maintenance is an excellent option for your industry.


Don't let failures take you by surprise and negatively impact your company's performance. Contact us today and learn first-hand about the benefits of implementing regular predictive maintenance procedures.