Maintenance testing

Abstract: A maintenance and management method of equipment for production operations, comprising: obtaining machinery component defect data by inspecting the equipment; performing countermeasures and inspections based on these data; obtaining defect frequency data and inspection standards data, classifying the defects of the equipment by importance; repeating an overall inspection based on the defect frequency data until the defect frequency data of all defect locations have lowered to a standard value or lower; then, producing operating standards data based on inspection standards data; and performing maintenance and management by individually feeding back the operating standards data to each operator, and a maintenance and management support system used for performing the method. The above maintenance and management method changes the forced deterioration of equipment to natural deterioration and standardizes the skill and knowledge level of each operator about the production machinery. Therefore, the service life of machinery components is extended and the time and cost necessary for maintenance and management can be reduced.

Abstract: Success of manufacturing companies largely depends on reliability of their products. Scheduled maintenance is widely used to ensure that equipment is operating correctly so as to avoid unexpected breakdowns. Such maintenance is often carried out separately for every component, based on its usage or simply on some fixed schedule. However, scheduled maintenance is labor-intensive and ineffective in identifying problems that develop between technician's visits. Unforeseen failures still frequently occur. In contrast, predictive maintenance techniques help determine the condition of in-service equipment in order to predict when and what repairs should be performed. The main goal of predictive maintenance is to enable pro-active scheduling of corrective work, and thus prevent unexpected equipment failures.

Abstract: A pre-emptive maintenance system for performing maintenance and process assurance on run-critical equipment employs an intrinsic health monitor that includes a number of sensors that are used with an operating equipment or machine to generate a set of intrinsic physical signatures that are products of the primary performance characteristics of the operating equipment These signatures are nonfunctional parametrics that are consistent and reliable indicators of the normal operation of the equipment and statistical norms are set during an initial learning mode using neural processors and the outputs from the sensors Thereafter, the sensor outputs are monitored and analyzed using the statistical norms to predict the probabilities of future failures of the operating equipment By using the intrinsic health monitor an advance in the field of equipment maintenance and process assurance is provided in the approach to maintenance being a pre-emptive procedure