Abstract: A method, system and computer readable medium are disclosed. The method, system and computer readable medium comprises providing a mathematically linked multi-step process for simultaneously determining operating conditions of a system or process that will result in optimum performance in both mean performance requirements and system robustness requirements. In a method and system in accordance with the present embodiment, the steps can be applied to any data array that contains the two coordinated data elements defined previously (independent variables and response variables), and for which a response prediction model can be derived that relates the two elements. The steps are applied to each row of the data array, and result in a predicted Cp response data set. In the preferred embodiment the array is a statistically rigorous designed experiment from which mean performance prediction models can be derived for each response evaluated. The data are applied to each row of the data array.

Abstract: The present invention provides a system and method for automatically generating reduced response data sets from complex scientific data via a response data handler (RDH) methodology, thereby eliminating non-systematic losses and oversights often associated with and resulting from the current practice while improving the overall integrity and confidence of the results typically sought in experimental practice.

Abstract: A method, system and computer readable medium are disclosed. The method, system and computer readable medium comprises providing a mathematically linked multi-step process for simultaneously determining operating conditions of a system or process that will result in optimum performance in both mean performance requirements and system robustness requirements. In a method and system in accordance with the present embodiment, the steps can be applied to any data array that contains the two coordinated data elements defined previously (independent variables and response variables), and for which a response prediction model can be derived that relates the two elements. The steps are applied to each row of the data array, and result in a predicted Cp response data set. In the preferred embodiment the array is a statistically rigorous designed experiment from which mean performance prediction models can be derived for each response evaluated. The data are applied to each row of the data array.

Abstract: The present invention provides a system and method for automatically deriving unique surrogate response data from experiment results in which inherent data loss occurs in a sufficient number of the samples to disallow quantitative effects estimation at the experimenter's desired level of confidence for statistical significance. In part, the unique surrogate response data sets of the present invention have four primary characteristics including: each is numerically analyzable; each may be more readily or directly obtained in which inherent data loss occurs; each provides a response value for an experiment trial; and each provides information on the effect of the change made to the process or system that would have been obtainable if the experiment samples had had no inherent data loss.

Abstract: A system for automating experimentation is disclosed. The system comprises an automated experimentation platform (AEP) for automating research, development, and engineering experimentation processes and work and a generalized exchange module (GEM) for automating data exchanges between the AEP and external software applications, devices, or the instrument control programs (ICPs) controlling the devices; a generalization of the exchange module enables all automated data exchanges to be generic. Through the use of the automated experimentation platform (AEP) and the generalized exchange module (GEM), the automation can be adapted to any targeted external software application, device or a devices' controlling software program.