5 Features to Look for in an Advanced Pattern Recognition Solution

In the in-demand industry of manufacturing, efficiency equals profitability. Since most factories and industrial plants rely on machines for their daily operations, they need to be in tiptop shape. But some companies still experience unplanned downtime. This unexpected breaking down of equipment may cost a company a whopping $ 260,000 per hour. 

Downtime significantly affects productivity and customer trust, which, in turn, decreases company profitability. It can be solved through software tools that diagnose the system and predict potential threats. Software such as an advanced pattern recognition solution can recognize probable faults, potential problems, and the overall status of equipment using a machine-learning algorithm.

While most companies have a designated team to handle machine maintenance, it cannot assure a hundred percent proficiency. No one can predict precisely when machines will break down. Sometimes, maintenance activities and routine inspections can be counterproductive. 

An advanced pattern recognition solution makes an accurate prediction by analyzing a massive amount of data. This process eliminates manual maintenance procedures and provides a highly precise outcome.

This breakthrough in manufacturing software has been around for several years. There are innovations and several versions that plant managers can choose from. If you are searching for this software for your organization, here are some features that you need to consider.

 

  • Early Warnings

 

Being proactive will save your company a lot of money. It would be costly and time-consuming to solve a problem after it has blown out of proportion. The advanced pattern recognition solution will alert appropriate personnel of potential faults before they happen.

The software will go through the whole operating system to detect possible mishaps. This process will give your maintenance team ample time to devise a plan to avoid having that dreaded downtime. The software will provide three levels of warning based on its severity. With this system, the company can plan their maintenance outages so as not to hamper daily operations.

 

  • Success Tree

 

This feature enables you to funnel your resources to areas with the highest priority. The success tree arranges all systems, subsystems, sensors, and signals into a logic tree pattern. This highly visual hierarchical model provides each part of the machine its health index. It allows users to pinpoint hotspots at once for further evaluation.

 

  • Health Index

 

This feature studies real-time data to come out with possible outcomes. The health index pertains to the actual and projected data. Every critical function of the machine, such as systems and signals, will be analyzed to come up with a rating from 0 to 100%. This rating can give stakeholders valuable insight into the health status of all equipment.

Knowing the performance level of each machine allows managers to make sound decisions and plans for optimum productivity.

 

  • Model Builder

 

Historical data refers to all information manually or automatically generated from an organization’s operations. This data is crucial in achieving the best conditions for the manufacturing systems. However, this data may not serve its purpose if it is not analyzed and organized. 

A manufacturing plant may not be able to keep up with the voluminous data that they receive every day. The software will enable you to use a machine-learning algorithm using historical data to build a predictive model.  

Machine downtime is a huge problem that needs a proactive solution such as a pattern recognition software. These features will allow you to choose the best one so your company can achieve maximum performance.

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About the Author: Prince Moga

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