Predictive Maintenance to avoid damage to industrial machinery

August 19, 2020
Predictive Maintenance to avoid damage to industrial machinery

Predictive maintenance management for industrial machinery as a more cost effective solution.

It can be said that predictive maintenance is the most effective way to avoid permanent damage to critical industrial equipment.

A maintenance plan will necessarily contemplate the best maintenance strategy, depending on the criticality of the machinery or even the engineering team experience and maintenance approach of the industry in question.

This is because there are situations in which it can be more cost effective to run to failure to repair.

Of course, these situations should be properly addressed in the maintenance plan.

There are advantages and disadvantages of the different maintenance strategies: from running to failure to preventive and predictive or reliability based maintenance.


Some authors consider predictive maintenance within the preventive maintenance approach.

This happens because interventions identified by predictive maintenance techniques are performed during scheduled preventive maintenance shutdowns.

One of the advantages is optimization of available resources.

In the classical model of preventive maintenance, an intervention is estimated within a given period of time for certain machinery, and this time is often defined by the OEM (Original Equipment Manufacturer) or based on industry or engineering experience.

There are several techniques of predictive maintenance, such as: vibration analysis, oil analysis, ferro graphy, thermography, ultrasound, statistical analysis of time series based on the machine or component condition, etc.

The objective is to monitor the condition of the asset to anticipate potential failures and correct identified problems before the machinery fails, ensuring its availability.

It is known that availability of a given machine is defined by its ability to be in proper conditions to perform a production task over a given period of time.

So, predictive maintenance techniques bring assertiveness to intervene, schedule and replace components only when necessary. This reduces the demand for spare parts.

In summary, increasing availability of industrial machinery, scheduling interventions to optimize man hours and spare parts needs, becomes a strategic source of efficiency.

Ensuring the continuity and quality of production, efficiently using the available resources while also increasing the safety and security, will certainly promote profitability.


Some of the potential hazards for maintenance personnel include:

  • Work by himself;
  • Work on machinery above ground level, or to connect electricity, air and water;
  • Access machines from the sides or back;
  • The need toenter confined spaces of large equipment;
  • Being stuck in equipment due to poor insulation of energy sources or presence of these sources;
  • Moving heavy machinery parts when changing setup or during repairs;
  • Deactivate or remove normal security systems to access machine mechanisms;
  • Exposure to oil leakage, toxic gases, explosives, dust, soot and others;
  • Exposure to heated surfaces, heat generation, vibration and excessive noise.

Safety and security standards define how to deal with mechanical and electrical hazards. Industries shall comply with it’s requirements.

The contribution of predictive maintenance techniques, which work with failure prevention and promote intervention before failures occur, have the positive effect of contributing both to workers safety and to avoid environmental risks.


Ensuring the reliability of industrial machinery is the way to ensure constant production flow.

A maintenance strategy based on running to failure can significantly reduce the productive capacity of an industry. It makes it difficult to measure the cost of production breakdowns.

Unplanned downtime willlead to reliability loss, production capacity and ultimately in customer loss due to inability to timely deliver orders.

Reliability-Based Maintenance (RBM) is based on continuous monitoring of the equipment condition and this is where predictive maintenance comes in.

The use of predictive techniques allows maximizing the asset life cycle by extending the life of original components, thus reducing the consumption of spare parts.


The technological trends of industry 4.0 are paving the way for important advances in predictive maintenance, if not a complete revolution. Among the key trends behind the changes are:

Wireless connectivity: Bluetooth low energy communication allows data stored on wireless devices to be easily read by smartphones or tablets. It is also possible to send data to the cloud via Wi-Fi.

Availability of cheap sensors: Sensors are becoming cheaper and MEMS (micro-electro-mechanical-systems) are more available than ever before.

Cloud Computing: Cloud computing has become robust, secure and inexpensive, allowing industries to increase data storage as needed.

Artificial Intelligence: Artificial Intelligence technologies are increasingly widespread and will be a great aid in the analysis of data collected by sensors.

DynaPredict is an industry 4.0 solution that integrates these technological advances into a wireless data logger. It produces a true “movie” of the machine condition, for the time your company deems appropriate. Learn more!

Download the brochure for free and get to know the products, applicability and benefits it will provide you.

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