Blog
Asset management and reliability go hand in hand. Check it out!
Maintenance is one of the pillars and main points of attention when it comes to industrial asset management, especially when it comes to managing maintenance costs. This is because it can be an ally, when thought of strategically, or a villain that can jeopardize a company’s financial health when not managed properly.
In fact, the way the Maintenance Manager manages processes has a positive (or negative) impact on the entire management chain. That’s why it’s important for companies to adopt a strategic stance and understand the direct relationship between maintenance and productivity. Since it is responsible for the availability of assets.
So, when properly applied, maintenance strategies can lead to gains in personal, operational and environmental safety, and raise awareness of compliance with organizational standards and guidelines.
Therefore, the maintenance strategy must be based on reliability studies aimed at maintaining the asset’s functionality and availability. Thus, applying the right strategies will have a positive effect on maintenance costs (OPEX) and will help assess the need to invest in CAPEX.
Capital Expenditure (CAPEX) is one of the ways to maintain or even expand the scope of a company’s operations. Examples include the construction of a new company, the acquisition of new assets, and so on, which represent investment and growth in assets.
On the other hand, Operational Expenditure (OPEX) is related to operating expenses, that is, routine activities such as maintaining equipment, paying employees, etc. In general, these expenses make up a significant percentage of the share of expenses and must therefore be strategically planned.
Typically, the financial resources allocated to maintenance (whether OPEX or CAPEX) are pre-established. Managers must therefore optimize these resources to “do more with less”, which is why it is essential to adopt effective maintenance strategies. Therefore, establishing the appropriate type according to the criticality of the asset, for instance, classifying it as A, B or C to establish priorities.
In other words, we already know the benefits of using preventive maintenance in asset management to avoid unplanned and emergency corrective actions. In fact, this strategy proves to be effective in most cases.
In order to maximize the optimization of resources, it is necessary to go a step further and apply the concept of Reliability. And one of the ways to do this is to maintain the asset’s functionality through Reliability Centered Maintenance (RCM), which provides a critical condition analysis.
This approach is a qualitative methodology of reliability engineering, whose main objective is to preserve the asset’s functions, maintaining availability and reflecting reliability. The idea is to develop an efficient maintenance program based entirely on the functionality of the system and equipment, and to use the correct maintenance strategies for each asset based on its operational context and criticality.
Thus, RCM makes it possible to reduce maintenance costs by prioritizing the system’s most important functions and adding maintenance activities that are strictly necessary for continuity, avoiding or removing unnecessary maintenance actions.
Initially, for RCM analysis, it is necessary to answer seven questions:
The answers to these questions provide elements that will help prioritize equipment and actions, that is, the execution of asset maintenance management. Once this is done, the decision tree can be set up.
We often don’t know where to start. This is why establishing a decision tree (or diagram) can make the process more practical. In other words, the decision tree is applied to define which of the plant’s representative assets needs to be analyzed, in addition to assessing maintenance costs, the risks of failure and the impact on production as a whole.
Thus, it is possible to accept the risk and not take any maintenance action, to prioritize those that are critical and avoid wasting effort. Check out a decision tree model:
From this, the RCM approach can be used to determine the correct tasks to avoid or minimize the possible failures and failure modes mapped. This makes asset management and maintenance plans more effective, increasing system availability and reducing business risks.
Do you want to know more about maintenance management? Learn about the role of the criticality matrix.
To effectively apply strategic management, it is necessary to obtain data from which the manager can make decisions. Therefore, the first step is to monitor assets and analyze this information.
The Dynamox solution offers vibration and temperature sensors that collect precise and continuous triaxial axis data. This information is also collected automatically (gateway) on a platform designed to support teams in their analysis and decision-making processes.
The use of the Dynamox solution helps to strategically plan asset management by offering tools that enable early identification of failures and maintenance planning. In fact, one of the elements available is the Decision-Making Assistant (DMA) tool, which optimizes the work of a predictive analyst through criticality alarms for the machine’s condition, trends and other parameters displayed on the dashboard. The dashboard also serves to establish priorities for decision-making by managers.
And how does it work? In practice, we can mention a real failure detection case at a paper mill, in which the loss of more than 70 tons of paper was avoided.
In this case, the paper machine dryer cylinder – a critical asset – showed signs of failure. The asset is monitored by Dynamox’s wireless vibration and temperature sensors. It is worth mentioning that the company also offers an automated detection system (DynaDetect). An alert signal was issued on the web platform and the technicians were notified of the changes in the vibration and temperature data captured by the sensors.
If corrective action were taken, the machine would have to be idle for an estimated 15 hours, mobilizing the technical team (man-hours) and affecting production for almost two shifts. By detecting the failure early on, it was possible to schedule maintenance actions on the asset at the right time, which was carried out in 6 hours. This saved 9 hours of machine downtime and the equivalent of 76.5 tons of paper not being lost.
Do you want to see the tools that allowed the failure to be detected? See the full case here.
Cases de sucesso
Casos reais de parceiros usando a Solução Dynamox
Não perca as novidades e atualizações da Dynamox