A computer implemented method comprising receiving one or more predictive maintenance models each defining a time-based probability of failure for one or more components, receiving current performance data for the components, defining a failure function for each component from a predictive maintenance model for the component and the current performance data for the component, the failure function defining the probability of failure of the component in each of a set of time periods, defining a value loss function for each component from the failure function for the component and a time-based component cost, the value loss function defining the expected value loss due to a planned replacement of the component in a given time period before the component fails or reaches its scheduled end-of-life, receiving data defining one or more factors that have an impact on the cost of a maintenance option.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method comprising: receiving one or more predictive maintenance models each defining a time-based probability of failure for one or more components, receiving current performance data for the components, defining a failure function for each component from a predictive maintenance model for the component and the current performance data for the component, the failure function defining the probability of failure of the component in each of a set of time periods, defining a value loss function for each component from the failure function for the component and a time-based component cost, the value loss function defining the expected value loss due to a planned replacement of the component in a given time period before the component fails or reaches its scheduled end-of-life, receiving data defining one or more factors that have an impact on the cost of a maintenance option, creating an optimization model for all components from the component failure functions, the value loss functions and the data defining one or more factors that have an impact on the cost of a maintenance option, the solutions to the optimization model representing the per time period effect of one or more maintenance options. 2. The computer-implemented method according to claim 1, further comprising: receiving data defining a maximum maintenance capacity per time period for all components and wherein the creating of the optimization model for all components defines maintenance options that do not exceed the maximum maintenance capacity per time period for all components. 3. The computer-implemented method according to claim 1, further comprising: receiving an input defining a set of desired optimization outcomes, each defined optimization outcome defining one or more factors to be optimized and wherein the creating of the optimization model for all components defines maintenance options that each provide optimization of each factor defined in a desired optimization outcome. 4. The computer-implemented method according to claim 1, further comprising: determining a preferred maintenance option with respect to a desired optimization outcome and outputting an illustration of the preferred maintenance option as a matrix of components against time periods plus the impact of the failure function for each component as a component cost. 5. The computer-implemented method according to claim 4, further comprising: outputting a selection of maintenance options and receiving an input defining a preferred maintenance option. 6. A system, comprising: a processor capable of performing a method comprising: receiving one or more predictive maintenance models each defining a time-based probability of failure for one or more components, receiving current performance data for the components, defining a failure function for each component from a predictive maintenance model for the component and the current performance data for the component, the failure function defining the probability of failure of the component in each of a set of time periods, defining a value loss function for each component from the failure function for the component and a time-based component cost, the value loss function defining the expected value loss due to a planned replacement of the component in a given time period before the component fails or reaches its scheduled end-of-life, receiving data defining one or more factors that have an impact on the cost of a maintenance option, creating an optimization model for all components from the component failure functions, the value loss functions and the data defining one or more factors that have an impact on the cost of a maintenance option, the solutions to the optimization model representing the per time period effect of one or more maintenance options. 7. The system according to claim 6, further comprising: receiving data defining a maximum maintenance capacity per time period for all components and when creating the optimization model for all components to define maintenance options that do not exceed the maximum maintenance capacity per time period for all components. 8. The system according to claim 6, further comprising: receiving an input defining a set of desired optimization outcomes, each defined optimization outcome defining one or more factors to be optimized and wherein creating the optimization model for all components defines maintenance options that each provide optimization of each factor defined in a desired optimization outcome. 9. The system according to claim 6, further comprising: determining a preferred maintenance option with respect to a desired optimization outcome and output an illustration of the preferred maintenance option as a matrix of components against time periods plus the impact of the failure function for each component as a component cost. 10. The system according to claim 9, further comprising: outputting a selection of maintenance options and receive an input defining a preferred maintenance option. 11. A computer program product for controlling a system, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: receive one or more predictive maintenance models each defining a time-based probability of failure for one or more components, receive current performance data for the components, define a failure function for each component from a predictive maintenance model for the component and the current performance data for the component, the failure function defining the probability of failure of the component in each of a set of time periods, define a value loss function for each component from the failure function for the component and a time-based component cost, the value loss function defining the expected value loss due to a planned replacement of the component in a given time period before the component fails or reaches its scheduled end-of-life, receive data defining one or more factors that have an impact on the cost of a maintenance option, create an optimization model for all components from the component failure functions, the value loss functions and the data defining one or more factors that have an impact on the cost of a maintenance option, the solutions to the optimization model representing the per time period effect of one or more maintenance options. 12. The computer program product according to claim 11, further comprising: program instructions to receive data defining a maximum maintenance capacity per time period for all components and wherein the instructions for creating of the optimization model for all components comprise instructions for defining maintenance options that do not exceed the maximum maintenance capacity per time period for all components. 13. The computer program product according to claim 11, further comprising: program instructions to receive an input defining a set of desired optimization outcomes, each defined optimization outcome defining one or more factors to be optimized and wherein the instructions for creating of the optimization model for all components comprise instructions for defining maintenance options that each provide optimization of each factor defined in a desired optimization outcome. 14. The computer program product according to claim 11, further comprising: program instructions to determine a preferred maintenance option with respect to a desired optimization outcome and outputting an illustration of the preferred maintenance option as a matrix of components against time periods plus the impact of the failure function for each component as a component cost. 15. A computer program product according to claim 14, further comprising: program instructions to output a selection of maintenance options and receiving an input defining a preferred maintenance option.