A method includes identifying costs associated with different outcomes of a failure prediction algorithm. The algorithm is configured to predict one or more faults with at least one piece of industrial equipment. The different outcomes include both successful and unsuccessful predictions by the algorithm. The method also includes identifying a threshold value for the algorithm using the costs, where the threshold value is used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed. The method further includes providing the threshold value to the algorithm. The threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. In addition, the method can include generating a signal indicating whether maintenance is needed based on a comparison of an indicator value calculated using the algorithm and the threshold value.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: identifying costs associated with different outcomes of a failure prediction algorithm, the failure prediction algorithm configured to predict one or more faults with at least one piece of industrial equipment, the different outcomes including both successful and unsuccessful predictions by the failure prediction algorithm; identifying a threshold value for the failure prediction algorithm using the costs, the threshold value used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed; and providing the threshold value to the failure prediction algorithm; wherein the threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. 2. The method of claim 1, wherein the different outcomes of the failure prediction algorithm comprise: a true positive in which the failure prediction algorithm correctly predicts that maintenance of the at least one piece of industrial equipment is needed; a true negative in which the failure prediction algorithm correctly predicts that maintenance of the at least one piece of industrial equipment is not needed; a false positive in which the failure prediction algorithm incorrectly predicts that maintenance of the at least one piece of industrial equipment is needed; and a false negative in which the failure prediction algorithm incorrectly predicts that maintenance of the at least one piece of industrial equipment is not needed. 3. The method of claim 2, wherein identifying the threshold value comprises: identifying a cost breakeven baseline associated with the failure prediction algorithm; and identifying true positive rates relative to false positive rates for a classifier of the failure prediction algorithm. 4. The method of claim 3, wherein identifying the threshold value further comprises: identifying a point on the classifier's receiver operating characteristic (ROC) curve showing the true positive rates relative to the false positive rates, the identified point having a largest positive difference from the cost breakeven baseline; and identifying the threshold value using the identified point. 5. The method of claim 3, wherein the cost breakeven baseline is determined as a cost of repairing or replacing the at least one piece of equipment after the at least one piece of equipment has already experienced the one or more faults without prediction of the one or more faults. 6. The method of claim 1, further comprising: receiving equipment data associated with operation of the at least one piece of industrial equipment; calculating an indicator value based on the equipment data using a classifier of the failure prediction algorithm; comparing the indicator value to the threshold value; and generating a signal indicating whether maintenance is needed based on the comparison. 7. An apparatus comprising: at least one processing device configured to: identify costs associated with different outcomes of a failure prediction algorithm, the failure prediction algorithm configured to predict one or more faults with at least one piece of industrial equipment, the different outcomes including both successful and unsuccessful predictions by the failure prediction algorithm; identify a threshold value for the failure prediction algorithm using the costs, the threshold value used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed; and provide the threshold value to the failure prediction algorithm; wherein the at least one processing device is configured to select the threshold value such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. 8. The apparatus of claim 7, wherein the different outcomes of the failure prediction algorithm comprise: a true positive in which the failure prediction algorithm correctly predicts that maintenance of the at least one piece of industrial equipment is needed; a true negative in which the failure prediction algorithm correctly predicts that maintenance of the at least one piece of industrial equipment is not needed; a false positive in which the failure prediction algorithm incorrectly predicts that maintenance of the at least one piece of industrial equipment is needed; and a false negative in which the failure prediction algorithm incorrectly predicts that maintenance of the at least one piece of industrial equipment is not needed. 9. The apparatus of claim 8, wherein the at least one processing device is configured to: identify a cost breakeven baseline associated with the failure prediction algorithm; and identify true positive rates relative to false positive rates for a classifier of the failure prediction algorithm. 10. The apparatus of claim 9, wherein the at least one processing device is configured to: identify a point on the classifier's receiver operating characteristic (ROC) curve showing the true positive rates relative to the false positive rates, the identified point having a largest positive difference from the cost breakeven baseline; and identify the threshold value using the identified point. 11. The apparatus of claim 9, wherein the at least one processing device is configured to determine the cost breakeven baseline as a cost of repairing or replacing the at least one piece of equipment after the at least one piece of equipment has already experienced the one or more faults without prediction of the one or more faults. 12. The apparatus of claim 7, wherein the at least one processing device is configured to: receive equipment data associated with operation of the at least one piece of industrial equipment; calculate an indicator value based on the equipment data using a classifier of the failure prediction algorithm; compare the indicator value to the threshold value; and generate a signal indicating whether maintenance is needed based on the comparison. 13. A non-transitory computer readable medium containing instructions that, when executed by at least one processing device, cause the at least one processing device to: identify costs associated with different outcomes of a failure prediction algorithm, the failure prediction algorithm configured to predict one or more faults with at least one piece of industrial equipment, the different outcomes including both successful and unsuccessful predictions by the failure prediction algorithm; identify a threshold value for the failure prediction algorithm using the costs, the threshold value used by the failure prediction algorithm to identify whether maintenance of the at least one piece of industrial equipment is needed; and provide the threshold value to the failure prediction algorithm; wherein the threshold value is selected such that a net positive economic benefit is obtained from use of the threshold value with the failure prediction algorithm. 14. The non-transitory computer readable medium of claim 13, wherein the different outcomes of the failure prediction algorithm comprise: a true positive in which the failure prediction algorithm correctly predicts that maintenance of the at least one piece of industrial equipment is needed; a true negative in which the failure prediction algorithm correctly predicts that maintenance of the at least one piece of industrial equipment is not needed; a false positive in which the failure prediction algorithm incorrectly predicts that maintenance of the at least one piece of industrial equipment is needed; and a false negative in which the failure prediction algorithm incorrectly predicts that maintenance of the at least one piece of industrial equipment is not needed. 15. The non-transitory computer readable medium of claim 14, wherein the instructions that when executed cause the at least one processing device to identify the threshold value comprise: instructions that when executed cause the at least one processing device to: identify a cost breakeven baseline associated with the failure prediction algorithm; and identify true positive rates relative to false positive rates for a classifier of the failure prediction algorithm. 16. The non-transitory computer readable medium of claim 15, wherein the instructions that when executed cause the at least one processing device to identify the threshold value further comprise: instructions that when executed cause the at least one processing device to: identify a point on the classifier's receiver operating characteristic (ROC) curve showing the true positive rates relative to the false positive rates, the identified point having a largest positive difference from the cost breakeven baseline; and identify the threshold value using the identified point. 17. The non-transitory computer readable medium of claim 14, wherein the cost breakeven baseline is based on a cost of repairing or replacing the at least one piece of equipment after the at least one piece of equipment has already experienced the one or more faults without prediction of the one or more faults. 18. The non-transitory computer readable medium of claim 13, further containing instructions that, when executed by the at least one processing device, cause the at least one processing device to: receive equipment data associated with operation of the at least one piece of industrial equipment; calculate an indicator value based on the equipment data using a classifier of the failure prediction algorithm; compare the indicator value to the threshold value; and generate a signal indicating whether maintenance is needed based on the comparison.