Predictive maintenance (PdM) monitors asset conditions and prevents failures from occurring. Find out how many types of PdM exist and what are the advantages
We know that there are different types of maintenance and that depending on the characteristics of the asset to be maintained, one will be chosen rather than another. As an alternative, you will opt for the combination of more than one type of maintenance.
Apart from choosing the most adequate type of maintenance, it is advisable to use a professional facility management software to improve the productivity of the maintenance processes and reduce the time and costs related to management.
Among the different maintenance types predictive maintenance stands out. Do we really know what it really consists of? When and how is it useful to implement it? Let’s find out in this article.
What is Predictive Maintenance?
Predictive maintenance, referred to as PdM, is a technique that monitors the performance and conditions of an asset and all its parts to be maintained. Through the analysis of the detected data, it identifies possible anomalies and/or defects so that it can correct them before the occurrence of any faults.
This type of maintenance was introduced in the 1990s and its main objective is to predict faults based on certain parameters and factors. Once the fault forecasting is carried out, maintenance managers are able to take the necessary measures to prevent the occurrence of expected faults.
As with any maintenance strategy, predictive maintenance also aims to:
- reduce the occurrence of failures and maximize uptime by improving asset reliability;
- optimize operating costs by reducing maintenance work;
- reduce maintenance costs and maximize production times.
Types of predictive maintenance
When we say “types of predictive maintenance”, we refer to the sectors in which this type of maintenance can act and the technologies used for each field of application. In fact, there is no single technology within this maintenance approach, but on the contrary, numerous control devices are used in relation to the technical aspect that must be monitored.
The main technologies used, corresponding to as many types of predictive maintenance, are listed below:
- Infrared thermography:
infrared thermographic analysis is a very widespread and versatile technology, especially because it allows a non-invasive analysis. This means that without affecting the property or parts of it, it is possible to detect temperatures above the norm. This in some cases may indicate a malfunction or a leakage.
- Sonic and ultrasonic acoustic monitoring:
through acoustic monitoring, maintenance personnel can detect a number of malfunctions such as the sounds of gas emissions, liquids or area leaks. In general, sonic technology is cheaper while ultrasonic technology is more expensive and is used for equipment, mechanics and electrical equipment that emit subtler sounds.
- Vibration analysis:
this type of analysis is particularly useful on machinery that emits specific vibrations based on the correct functioning of the components or not. When the components start to wear out, the vibration changes and a new type of vibration emerges. With constant monitoring, a qualified technician can compare the vibration model results and identify worn or malfunctioning components in advance, thus avoiding the occurrence of faults.
- Oil analysis:
oil analysis is an activity considered very effective in predictive maintenance. By checking the oil conditions of machinery and equipment, technicians can establish the presence of contaminants, determine viscosity, detect the presence of water, etc. The main advantage of oil analysis is that the initial test results serve as the basis for any new machinery and new maintenance.
How to establish a predictive maintenance program?
Clearly, every asset to be maintained will need a tailored maintenance program created, but below we indicate some essential steps of a predictive maintenance program that can serve as a guideline:
- Check budget availability:
before approving the maintenance program, it has to be feasible from the economic point of view. For this reason, it is essential to discuss with those professionals dealing with the financial aspects and with the client and verify that the program is economically sustainable.
- Identify critical assets:
this step is used to identify those resources that need predictive maintenance, because they are more expensive than others or more delicate.
- Create a database:
all available historical data can be useful for predictive analysis. This data, in fact, can be used to establish the possible failure modes to which the specific asset could be subjected. It could also be useful when developing a very first version of the predictive algorithms.
- Analyze and establish the failure modes:
once the critical assets are identified, they will be analyzed. For each one, an analysis of the most common failure modes will show when to act in order to avoid any downtime.
- Implement sensors and monitoring devices:
once the possible failure modes are spotted, you can act in order to prevent them. To do this, you just need to select the devices and technologies that are suitable for the specific case. We have seen some in the previous paragraph but the market offers constantly advancing solutions. Among the most advanced solutions, we find IoT technology that allows communication between machines, software solutions and cloud technology, helping to collect and analyze huge amounts of data.
- Developing predictive algorithms:
at this stage, specialists will develop predictive maintenance algorithms based on sensor measurements and other useful data collected.
Difference between preventive maintenance and predictive maintenance
The difference between preventive maintenance and predictive maintenance lies in the data analyzed.
While a predictive maintenance technician relies on monitoring and analyzing data from the actual and current conditions of the equipment in operation, preventive maintenance relies on historical, average, and statistical life expectancy data in order to predict when maintenance activities are necessary.
Advantages of predictive maintenance
Predictive maintenance has the double advantage of intervening before the failure occurs, but in the same way of doing so not too long before the intervention is actually necessary. In this way, it is possible to leverage the entire useful life of the asset or its components.
This, of course, brings several cost savings by reducing
- maintenance time;
- the production hours used for maintenance;
- the cost of spare parts and supplies.
It has also been shown that predictive maintenance programs increase their return on investment (ROI) by ten times thanks to a reduction of
- maintenance costs by 25-30%;
- faults by 70%-75%;
- downtime by 35% -45%.
The maintenance phase of an asset and its components is among the most demanding, long and sometimes even expensive.
Surely, making use of professional software is always useful, indeed indispensable, to ensure that the maintenance work gives efficient results. For this reason, I recommend that you try the facility management software yourself that will allow you to plan maintenance, track activities and manage problems in a single platform.