4 types of Industrial Maintenance
The types of industrial maintenance are used in order to ensure good equipment performance, production flow, and machine life.
It is through them and the technological advances that it becomes possible to avoid major inconveniences during operational failures and negative financial impact.
In addition, proper asset management ensures operational excellence, employee physical integrity, and competitiveness.
Among the industrial maintenance models, we have:
Corrective maintenance is also known as breakdown maintenance, referring to repairs that are performed on a machine or equipment that has stopped working.
The components of a machine can fail at any time, and for this reason, this type of industrial maintenance is usually the most expensive for the company, both for the replacement of the equipment and for the production stoppage.
However, depending on the criticality level of the machine, it is interesting to apply it. Equipments with a low level of utilization in which their downtime does not negatively affect production are good examples.
Machine control does not exist when corrective maintenance is implemented.
When predictive techniques are applied, the industry can perform planned corrective maintenance, where it is possible to identify the loss in machine performance and schedule its repair at a more opportune time. In this case, a change in the strategy to Predictive maintenance is already identified.
- does not involve costs related to condition monitoring and preventive maintenance;
- the machines are not subject to maintenance.
- unknown production time;
- secondary breakdowns and catastrophic failures;
- production losses;
- high repair costs;
- lack of machine control.
Preventive maintenance, also called time-based maintenance, is maintenance that follows a previous planning, based on defined time intervals or according to a pre-established criterion.
The objective of this industrial maintenance is to reduce the risks of machinery failures or drops in performance. As the name implies, the idea is damage containment, saving materials, parts, and labor through planning.
It is one of the models used in the industry and is effective in preventing failures related to the aging of the equipment and it’s common for machines under manufacturer’s warranty.
Bearings, defective gears, mechanical and electrical failures in motors are examples of potential failures, that is, they appear in the asset at an early stage and may evolve.
In such cases, preventive maintenance is an option.
The technician makes a plan to repair the equipment, so that it does not affect production and is able to bring the equipment back to the expected performance.
- increase in the useful life of the machinery;
- reduction of unforeseen failures;
- reduced energy consumption;
- flexibility for planned interventions;
- reduced risk of catastrophic failures;
- less production losses;
- greater control of warehousing and spare parts costs.
- Medium to long term economy;
- there is still a risk of downtime;
- damage to parts due to excessive maintenance;
- increase in the cost of spare parts.
Predictive maintenance uses techniques and instruments to monitor the machine’s condition or health, its performance, and potential failure indicators in order to perform timely maintenance at the lowest possible cost.
In it, the equipment is constantly monitored and there is the possibility of identifying random failures that represent 80% of the patterns. The use of sensors for data collection is carried out during the machine’s operation.
The DynaLoggers, Dynamox’s wireless vibration and temperature monitoring sensors, are examples of cutting-edge technology used by Industry 4.0 for predictive maintenance.
Improving predictive analysis techniques, the use of machine learning is another technology used by Dynamox.
Using artificial intelligence, the system analyzes the condition of the monitored components and identifies those that are in critical condition, suggesting which is the nature of the defect.
These results are shown in automated detection dashboards, becoming another tool to help the entire maintenance team identify anomalies, prioritize maintenance orders, and make decisions.
During the pandemic, predictive maintenance became an ally when it came to remote monitoring and distancing through analysis by means of sensors.
Monitoring the health of the equipment by continuous sample logging has kept the sectors running, reliable, and productive.
- unscheduled production losses are reduced;
- optimization of available resources;
- anticipates potential failures;
- extends the useful life of the machines;
- eliminates unnecessary revisions;
- substantial increase in employee safety;
- technology with accessible cost.
- requirement of trained professionals for data analysis;
- commitment from industry managers.
Finally, prescriptive maintenance refers to the concept where data can be analyzed to predict when failure events will occur, but also recommending actions to be taken.
This type of industrial maintenance raises the quality of production, identifying, even months in advance, critical points that can generate extra costs with the machines.
It is considered a natural evolution of predictive maintenance, for going further in its analysis. And unlike preventive maintenance, it is not based on a schedule that aims to cover failures. Its implementation is associated with ISO 55000, aimed at asset management.
The analysis and measurements take place remotely, within the configured parameters, and the technician has little need to do on-site checks.
The system itself has artificial intelligence, which learns to predict the patterns that precede each type of failure from information continuously fed from the Corrective and Predictive Maintenance history.
After this analysis, the system decides for maintenance or continued operation. This process optimizes the technicians’ time in the field, related to the adjustment and repair of assets.
Prescriptive maintenance has shown positive results, establishing itself as one of the most promising new digital technologies in Industry 4.0.
This kind of technology is what makes Industry 4.0 constantly evolving, improving and making industrial maintenance service even more efficient.
Faced with the economic crisis scenario caused by the coronavirus pandemic, digital technology for prescriptive maintenance has gained even more importance. In a McKinsey survey of 400 companies from various countries and sectors, 94% of them say that 4.0 technology helped them not to interrupt their operation; while 56% say it was crucial in responding to the crisis.
- data collected;
- optimized equipment reliability;
- extended machine life span;
- significant financial impact, since it favors cost reduction;
- suggests punctual actions based on the possibilities (shows how it is and how to avoid a certain situation from occurring).
- requires planning and high investment in equipment and software;
- requires trained professionals with additional training;
- requires a change in philosophy at all levels.
Based on the advantages and disadvantages of each type of industrial maintenance, have you decided which one is most suitable for your company? Continue your research with this incredible success story.