Technological advances have sparked interest of operational excellence companies during the few last years and have created has a new era in assets management. This is the impression of a majority of executives and managers whose businesses are based on the asset maintenance. They consider the possibility of using and analyzing extensive amounts of data as a great opportunity nowadays to increase efficiency and improve asset maintenance operations.
According to a study carried out by Ernst & Young, operational excellence could lead to a 43% reduction in operational costs in sectors such as oil and gas. It could also reduce the number of security incidents. Operational excellence applied in asset management would give organizations the benefits for a greater asset integrity, and be an improvement in the planning and execution of maintenance activities. It could reduce critical bugs by 50 percent.
Recent innovations are contributing towards more preventive, rather than corrective activity, in asset maintenance. The most notorious are the following. On one hand, large amounts of data can be currently collected due to IoT and M2M devices. On the other hand, there has been a growth in data processing capacities due to Big Data platforms. And lastly, there has been an improvement in data insight discovery provided by advanced analytical techniques. Together, these three innovations can help companies and public organizations assure the asset´s reliability, increase their availability, their lifetime value and improve their safety. In the end, the clear business benefits of these aspects can contribute to reducing costs in the maintenance of equipment, which demonstrats that new technologies can offer real and tangible benefits.
Furthermore, factors such as ambient temperature, humidity level or vibration excess have a marked effect on the machine´s performance. The collection and correlation of operational and environmental data provides a clearer picture of the machine´s performance, allowing to predict the maintenance requirements of each piece of equipment. If we think that prevention is always better and cheaper than repairing, this could lead to big savings in asset maintenance costs.
But which companies can benefit from these innovations? The answer is: many of them. The number of beneficiaries is large considering the wide range of assets involves, such as transformers, pumps, wind turbines, panels, pipes and vehicles. The risks associated with malfunction or inactivity are immense, so a reliable maintenance strategy is a priority not only for essential sectors such as energy, transport or the public sector, but also others such as the manufacturing sector. In an IDC survey on manufacturing companies, 38 percent of respondents acknowledged that their maintenance operations are reactive, focused on fixing failures instead of preventing them.
However, there are strong indications that this is changing. Such a change will revolutionize how companies will offer asset maintenance services over the next few years. It will be based on a more preventive approach and therefore more proactive.
Companies like elevator giant Tyssenkrupp Elevator AG have already begun working on this new strategy, striving to make their maintenance work be more predictive and dynamic. By using this strategy, they can identify the elements of an elevator that need to be repaired or replaced before unplanned interruptions of the service. To do this, the company had to update its processes, and train more than 20,000 technicians. Additionally, it had to modify its contracts with customers to incorporate this new way of offering elevator maintenance services.
Maintenance strategies and maturity. Source: ARC Advisory Group
The automatization of preventive maintenance represents a great advancement, but this is not the final goal. Prescriptive maintenance is the next big step forward in the evolution of asset management. Prescriptive maintenance systems use advanced algorithms to evaluate multiple variables and identify the greatest maintenance planning in order to get the best reliable results. This means moving forward with preventive maintenance by incorporating intelligence into the process and improving efficiency in maintenance operation planning. Prescriptive solutions allow companies to maximize and optimize equipment activity, as well as material and human resource productivity.
The benefits of Applied Analytics are clear. For example, the equipment’s half-life increases due to serious faults. But it also helps us to have a greater understanding of the assets, which provides us with the essential information we need to prevent equipment breakdown. The improved knowledge of maintenance activity allows us to know in advance what materials we will need to carry out the maintenance task the number of team members needed, the skills of the work-team and how long we will need to repair it. All of this information can be obtained through Predictive and Prescriptive Advanced Analytics solutions. These solutions automatically generate automatically smart maintenance planning and resources allocation to reduce costs, minimize risk and improve efficiency of the complete process.
In order to illustrate the business case, let me present an example. Let us suppose that a pump component starts to vibrate more than usual or that the machine sound changes the frequency of its pitch. This could indicate that something unusual is happening with your equipment.
The sensor can detect that change and the data analysis provides an assessment based on predictive faults models (using the manufacturer´s documentation, historical data of the equipment and the performance of other similar equipment). It predicts that there will be a breakdown in the next 36 hours. This gives the maintenance team the opportunity to schedule the repair according to the available labor force and send the operator with appropriate skills to repair the machine with the necessary tools and the spare parts needed for the replacement.
Therefore, the use of solutions based on Advanced Analytical models will allow us to maximize the asset´s activity time (avoiding the inactivity time of the pump not planned) and also minimize the number of times maintenance teams need to act on the pump. In addition, the system can automate the maintenance scheduling. That means, we could optimize the operational planning and develop an optimal work plan to minimize the operational cost of maintenance. Ontegrity, a company that provides air-condition maintenance services is an example about the companies just are have adopted such a strategy.
Nowadays the insight hidden inside data will allow companies that apply advanced solutions to detect patterns and trends that can guide them in the development of the most efficient and effective maintenance plans. The future of the maintenance operations aims at a more preventive and personalized treatment of assets.