What is predictive maintenance?
Businesses that operate with assets usually do preventive maintenance to keep their equipment running smoothly and reduce the need for costly repairs and replacements. Nonetheless, the increasing capabilities of AI enable predictive maintenance to use sensors to collect data about how your machinery is performing in real-time. Software systems such as APM Studio come in place to translate the collected data for customers. But what exactly does this mean? What kinds of machinery benefit from preventive maintenance, and how can you put these processes into place to increase business effectiveness? This article will answer all these questions and more to understand better what predictive maintenance means.
What is Predictive Maintenance?
As preventive maintenance, predictive maintenance you time and money by keeping machinery from breaking down. However, it goes beyond the AI data analysis software: Predictive maintenance predicts when a machine or system will break down based on usage patterns and other variables. It then automatically initiates a process to fix that issue before it occurs, thereby preventing downtime and unexpected failures. At UReason, several extensive algorithms have trained the APM Software to develop detection and prediction models for asset owners in various industries. This resulted in a predictive maintenance software that reduces downtime and reduces costs because of preventive maintenance, but more importantly, it works with alarm systems. It helps you prevent breakdowns before they occur—hence its name. Predictive comes from being able to forecast future problems through sensors and data analysis. When implemented successfully, predictive maintenance keeps machines up and running without costly downtime issues and helps prevent unexpected failures. UReason has gained experience implementing more than 300 projects in companies such as FOCUS-ON, NS, and Halliburton.
FOCUS-ON Case Study
FOCUS-ON is the joint-venture of SAMSON and KROHNE. Both frontrunners have combined forces to launch Focus 1. A smart combination of a control valve and a flow meter.
With the support of UReason and Ureason’s APM Studio, they were able to accelerate the development process of building a unique product with the integration of (embedded) diagnostic functions and artificial intelligence.
In which industries can predictive maintenance be applied?
Predictive maintenance applies to all business that uses mechanical equipment should consider implementing predictive maintenance procedures. However, industries, where machinery is mission-critical are more likely to benefit from preventive maintenance.
For example, many mining companies rely on keeping machinery running for more extended periods to profit. They often rely on repair or overhaul services rather than having their equipment replaced during their lifetime. Still, sometimes malfunctions occur in ways that cannot be predicted with current technology—predictive maintenance helps these businesses prevent major breakdowns by identifying problems early and solving them before they cause problems. In industries such as manufacturing, energy generation/distribution, and oil & gas exploration & production, predictive maintenance can keep expensive machinery from failing unexpectedly, saving hours of work time as well as thousands of dollars in repair costs. Other industries such as health care, food processing, or high-tech product development can also see huge benefits from preventive maintenance. The process to apply is by identifying one processor machine at your company that is prone to error, evaluating it carefully, coming up with a plan for preventive maintenance, and discovering some improvements.
How does predictive maintenance work?
Predictive maintenance is a process in which sensors are attached to an equipment’s various parts. The sensors then send information back to a computer that analyses the data and predicts when repairs are needed on specific components, allowing companies to schedule preventative maintenance rather than waiting for something to break down. IoT technology makes it possible to predict maintenance needs based on internet-connected sensors always monitoring machines. It will be increasingly important for businesses to implement IoT applications as workforce populations decline—heavy assets must be able to complete basic tasks independently. Predictive data models use all processed data (machine instructions, sensor reads) to train AI models to recommend what maintenance procedures should be done next.
What are the benefits of predictive maintenance?
Predictive maintenance refers to a range of activities and practices used to identify problems in manufacturing equipment before they result in costly downtime. It includes diagnostic information systems, condition monitoring tools and other data that help track equipment performance and pinpoint when something’s about to go wrong. The goal is not only to keep machines running but also to increase their productivity and efficiency.
With UReaon’s APM Studio; a reduction in downtimes, cost savings for unexpected breakdowns, and extended asset life are all major benefits of implementing a preventive maintenance program. Preventive maintenance keeps machines working correctly by ensuring that any problems are caught before they lead to costly downtime issues. This could result in 25% reduction of downtime of the assets. It’s important to understand though that preventive maintenance will not solve all issues with your equipment. However, when implemented successfully, Predictive Maintenance keeps machines up and running with a decrease of costly maintenance costs of 20% by preventing unexpected failures. Moreover, APM software provides companies with a real time overview of their assets lifetime which leads to longer asset life and significant reductions in machinery costs over time. Predictive maintenance can increase the durability of assets with 80%.