5 Types of Maintenance Explained: Preventive, Predictive, Condition-Based and Risk-Based

Maintenance is an essential part of any industrial operation. It helps to ensure that machines and equipment are running smoothly and efficiently, and that any potential problems are identified and addressed before they become serious. There are several different types of maintenance, each with its own advantages and disadvantages. In this article, we'll take a look at the five main types of maintenance: preventive, predictive, condition-based, risk-based and corrective.

Preventive maintenance is the practice of regularly inspecting and servicing machines and equipment in order to detect and resolve problems before they occur. This type of maintenance is typically performed by technicians in charge of industrial maintenance before any failure or malfunction occurs. It involves inspecting spare parts, components, and machinery and equipment in order to reduce the risk of breakdowns. The digitization of industrial companies has provided many computer and technological solutions that allow technicians to effectively perform, monitor, track and plan preventive maintenance. The emergence of data processing and analysis solutions, as well as artificial intelligence, has allowed manufacturers to plan predictive maintenance based on the prediction of faults and breakdowns.

This type of industrial maintenance allows companies to anticipate problems by planning the necessary interventions and maintenance operations based on forecasts. In this way, it allows you to limit expenses caused by unexpected breakdowns, equipment downtime and production interruptions. Systematic preventive maintenance is based on the periodic inspection of different equipment, which allows maintenance technicians to collect the necessary information on the different components of the production line and effectively prevent breakdowns and repair costs. Conditional preventive maintenance consists of monitoring the key parameters and indicators of the operation of the property and implementing the necessary corrective actions to anticipate any failure or malfunction. There are many emerging computer tools available to automate this type of industrial maintenance. Therefore, technicians and maintenance workers can simplify and facilitate their work by opting for the digitization of industrial maintenance processes.

Risk-based maintenance (RBM) consists of using a risk assessment methodology to assign scarce maintenance resources to the assets that carry the greatest risk in the event of a failure (remembering that risk = probability x consequence).Predictive maintenance (PDM) is a type of industrial maintenance that uses data analysis techniques such as machine learning to predict when a machine or piece of equipment will fail or require servicing. This allows companies to plan ahead for any necessary repairs or replacements before they become necessary. Until recently, predictive maintenance was essentially synonymous with condition-based maintenance. However, with the emergence of artificial intelligence, the much lower costs of equipment sensors (IIoT) and machine learning, a difference is clearly emerging between predictive maintenance (PDM) and condition-based maintenance (CBM).Finally, corrective maintenance is used when a machine or piece of equipment has already failed or malfunctioned.

This type of maintenance involves repairing or replacing faulty components in order to restore the machine or equipment to its original working condition. It is typically used as a last resort when all other types of maintenance have failed. In conclusion, there are five main types of industrial maintenance: preventive, predictive, condition-based, risk-based and corrective. Each type has its own advantages and disadvantages, so it's important to consider which type is best suited for your particular needs before making a decision.

Julia Hirliman
Julia Hirliman

Typical pop culture buff. Award-winning internet guru. Typical tv maven. Total internet fanatic. Incurable internet geek. Freelance music ninja.

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