HanPHI: Advanced Pattern Recognition Solutions

Our intelligent predictive-modeling and health-indexing technologies make HanPHI a powerful solution that has significant benefits for system operations. Early warnings identify areas for predictive maintenance, reducing maintenance costs, unscheduled downtime, and equipment failures. With HanPHI, you can eliminate potential operational risks, extend equipment life cycles, and increase asset reliability, efficiency, and safety all within a limited budget. limitations to achieve operational excellence.

Real-World Savings From HanPHI

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Advanced pattern recognition solution

Unplanned downtime is a big draw on budgets and efficiency no matter what industry or field you’re in. In fact, many organizations report that downtime is a significantly burdensome source of revenue loss — often times the largest. When your machines and data sources fail, overhead costs can go through the roof while efficiency plummets through the floor.

Over recent years, four out of five U.S. companies say they’ve suffered from downtime in excess of several hours. This can cost an efficient organization more than a quarter of a million — and the worst part is that it’s completely avoidable. Not only does unplanned downtime affect cash flow, it can also wreak havoc on meticulously planned budgets that have to be adjusted midway through, and we all know how problematic and chaotic a cascading budget shift can be.

Thankfully, there’s a better way to optimize your equipment health rather than having to wait for your next period of downtime or build a buffer into your budget.

It’s called advanced pattern recognition, and it’s changing the way many institutions approach downtime. With an advanced pattern recognition solution, you’ll see the anomaly in the data long before it hits your bottom line. This gives you the ability to design maintenance strategies that prevent breakdowns before they have a chance to slow your production to a costly standstill.

Whether you’re seeking maintenance optimization, an improved search process to help identify maintenance priorities, decreased production costs, or strengthened data analysis capabilities, advanced pattern recognition software is quickly becoming a requirement for production plants and production sites that can’t afford one minute of money-burning downtime.

To learn more about how advanced pattern recognition solutions can help your organization, contact the advanced pattern recognition experts at HanAra Software. We’re ready and able to help you break through your limitations to achieve operational excellence.

Model Builder and Executer
The HanPHI Builder builds prediction models through a machine learning algorithm and advanced pattern recognition using historical, fault-free normal operation data. Users can retrain models based on time duration, resolution, and user-defined criteria to ensure an accurate prediction model.

Health Index
The health index is based on the difference between real-time data and the expected model data. The index is for the whole operation including selected major systems, equipment, and signals. The intuitive index from 0 to 100% gives any member in the organization a clear understanding of the current status of equipment or site. Learn More.

SuccessTree
The SuccessTree provides hierarchical groups of systems, subsystems, and signals to represent health status indices from the operations level to the individual sensor. The SuccessTree automatically tracks a signal with the lowest index affecting the overall index, enabling fast and effective root cause analysis. Learn More.

Early Warnings
HanPHI’s early detection provides early warning for preventing and reducing equipment failure. It provides indication of systems’ abnormalities to avoid equipment failure through planned outages. Learn More.

Advanced pattern recognition features

CUSTOMER STORIES

KOREA SOUTH-EAST POWER

Korea South-East Power Company (KOEN) is a major power generation company, providing approximately 10,000 megawatts of electricity at its 12 plants. KOEN generates electricity for metropolitan areas and southern Korea. KOEN generates approximately 10% of South Korea’s annual net electricity.

Since installing HanPHI in 2012, KOEN has proactively managed its plants. With HanPHI, KOEN has increased its annual electricity output and the lifecycle of its assets and decreased its maintenance costs, repair time, fuel usage, and unscheduled downtime.

THE UNIVERSITY OF TEXAS AUSTIN

To reduce unexpected equipment failures, unplanned maintenance activities, and outage time, UT Austin chose HanAra Software’s HanPHI™ solution as its condition-based predictive monitoring solution.

With the implementation of HanPHI, HanAra provided the UT Austin team with the information to simplify and speed-up the decision-making and maintenance process. With a centralized location for data and the capacity to utilize predictive maintenance, HanPHI also eliminates redundant and unnecessary maintenance and support costs.

KHNP

KHNP is the largest Korean electric power company, generating approximately 31.5% of the total generated electric power in Korea. KHNP operates 82 units, including solar, hydro, geothermal, bio, hydrogen, and more, with a total production capacity of 27,857 MW.

With growing increase in operational data available at plants, KHNP turned to HanPHI to ensure the technical safety of their facilities and to manage data at a centralized control and monitoring center.

HanPHI Use

Ways to use HanPHI

HanPHI provides a plant health index to give you early warnings of potential and hidden equipment failures. Since HanPHI is comparing real-time values to HanPHI expected values, it also alerts you of potential sensor issues, including mismapped sensors.

Ways to use HanPHI

The value of HanPHI is that it represents the current operating status of your equipment, systems, plant, and fleet. By using the historical normal, fault-free data to create models, you have a better understanding of how your equipment operates in your environment and in your process.

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