Proving its accuracy and reliability by providing a prediction of time and cause of failure, as well as maintenance suggestions
“We replaced the insulating oil at an optimal time due to guardione®’s prediction and early detection of potential risk ensuring stable plant operations.”
[Account’s Facility Maintenance Engineer]
Account Overview
This account is one of South Korea's four largest oil refining firms.
Challenge
The transformer is by far the most essential asset of all oil refinery power facilities, in terms of power supply. When working with a client who had experienced several unexpected failures of their transformers in the past, we were looking for new measures to maintain their facilities due to the limitations in existing management methods.
Project
The client was considering implementing an automatic predictive diagnostics solution for key facilities as part of its Digital Transformation project, and onepredict was the candidate for its transformer facilities.
Prior to the actual implementation, multiple tests were conducted on key features, namely diagnostics and precision of prediction, and the details of which are as follows.
1.Identifying failure and normal operation through the analysis of past DGA data, without the information on the failure status of each transformer.
2. For faulty transformers, accurately predicting the time of unexpected failure using pre-failure DGA data.
3. Verifying performance through a comparison of solution-suggested failure causes and repair measures with those of actual cases.
Result
Guardione® solution successfully passed the verification process.
1. Not only did guardione® solution accurately identify the normal transformer facility among various data, but it also predicted the time of failure for transformers with unexpected past failures.
2. Following the solution’s official implementation, a potential malfunction was diagnosed on a particular transformer, for which replacement of the insulation oil was suggested.
3. Just a few weeks later, failure issue occurred with the same transformer, calling for a sudden insulation oil replacement, once again proving guardione® solution's diagnostics and prediction reliability.
4. The client continues to use guardione® solution through a licensing agreement that was concluded the following year, after seeing first-hand its predictive diagnostics and maintenance suggestion capabilities.
Proving its accuracy and reliability by providing a prediction of time and cause of failure, as well as maintenance suggestions
“We replaced the insulating oil at an optimal time due to guardione®’s prediction and early detection of potential risk ensuring stable plant operations.”
[Account’s Facility Maintenance Engineer]
Account Overview
This account is one of South Korea's four largest oil refining firms.
Challenge
The transformer is by far the most essential asset of all oil refinery power facilities, in terms of power supply. When working with a client who had experienced several unexpected failures of their transformers in the past, we were looking for new measures to maintain their facilities due to the limitations in existing management methods.
Project
The client was considering implementing an automatic predictive diagnostics solution for key facilities as part of its Digital Transformation project, and onepredict was the candidate for its transformer facilities.
Prior to the actual implementation, multiple tests were conducted on key features, namely diagnostics and precision of prediction, and the details of which are as follows.
1.Identifying failure and normal operation through the analysis of past DGA data, without the information on the failure status of each transformer.
2. For faulty transformers, accurately predicting the time of unexpected failure using pre-failure DGA data.
3. Verifying performance through a comparison of solution-suggested failure causes and repair measures with those of actual cases.
Result
Guardione® solution successfully passed the verification process.
1. Not only did guardione® solution accurately identify the normal transformer facility among various data, but it also predicted the time of failure for transformers with unexpected past failures.
2. Following the solution’s official implementation, a potential malfunction was diagnosed on a particular transformer, for which replacement of the insulation oil was suggested.
3. Just a few weeks later, failure issue occurred with the same transformer, calling for a sudden insulation oil replacement, once again proving guardione® solution's diagnostics and prediction reliability.
4. The client continues to use guardione® solution through a licensing agreement that was concluded the following year, after seeing first-hand its predictive diagnostics and maintenance suggestion capabilities.