Abstract: An apparatus for detecting a rare situation in a process described by a plurality of parameters, the apparatus comprising: a parameter value inputter, for inputting values of at least two interrelated parameters of the plurality of parameters, the interrelated parameters constituting at least one cluster, and a rare situation detector for detecting a rare situation according to an alert policy, the alert policy being based at least on an output value of an alert model, the alert model configured to provide the output value as a function of the input parameter values of parameters constituting the at least one cluster.

Abstract: A method, system, and medium of modeling and/or for controlling a manufacturing process is disclosed. The method includes the steps of identifying one or more input parameters that cause a change in output characteristics, defining global nodes using estimated maximum and minimum values of the input parameters, and defining a mathematical equation that calculates a predicted output characteristic for each node. The method also includes the steps of receiving at least one empirical data point having one or more input parameter values and at least one empirical output value and adjusting the predicted output values at the nodes based on a difference between the at least one empirical output value and the predicted output characteristic calculated using the mathematical equation based on the one or more input parameter values.

Abstract: An apparatus for the analysis of a process having parameter-based faults includes: a parameter value inputter configured for inputting values of at least one process parameter, a fault detector, configured for detecting the occurrence of a fault, a learning file creator associated with the parameter value inputter and the fault detector, configured for separating the input values into a first learning file and a second learning file, the first learning file comprising input values from a collection period preceding each of the detected faults, and the second learning file comprising input values input outside the collection periods, and a learning file analyzer associated with the learning file creator, configured for performing a separate statistical analysis of the first and second learning files, thereby to assess a process status.

Abstract: A method, system, and medium of modeling and/or for controlling a manufacturing process is disclosed. The method includes the steps of identifying one or more input parameters that cause a change in output characteristics, defining global nodes using estimated maximum and minimum values of the input parameters, and defining a mathematical equation that calculates a predicted output characteristic for each node. The method also includes the steps of receiving at least one empirical data point having one or more input parameter values and at least one empirical output value and adjusting the predicted output values at the nodes based on a difference between the at least one empirical output value and the predicted output characteristic calculated using the mathematical equation based on the one or more input parameter values.

Abstract: An apparatus for the analysis of a process having parameter-based faults includes: a parameter value inputter configured for inputting values of at least one process parameter, a fault detector, configured for detecting the occurrence of a fault, a learning file creator associated with the parameter value inputter and the fault detector, configured for separating the input values into a first learning file and a second learning file, the first learning file comprising input values from a collection period preceding each of the detected faults, and the second learning file comprising input values input outside the collection periods, and a learning file analyzer associated with the learning file creator, configured for performing a separate statistical analysis of the first and second learning files, thereby to assess a process status.

Abstract: An apparatus for the analysis of a process having parameter-based faults includes: a parameter value inputer configured for inputting values of at least one process parameter, a fault detector, configured for detecting the occurrence of a fault, a learning file creator associated with the parameter value inputer and the fault detector, configured for separating the input values into a first learning file and a second learning file, the first learning file comprising input values from a collection period preceding each of the detected faults, and the second learning file comprising input values input outside the collection periods, and a learning file analyzer associated with the learning file creator, configured for performing a separate statistical analysis of the first and second learning files, thereby to asses a process status.

Abstract: A strategic method for process control wherein the method includes, for a predetermined process juncture, the steps of: (A) defining an interconnection cell having associated therewith (i) at least one set of input data or at least one set of process control parameters, and (ii) at least one set of output data; (B) assigning at least one boundary value to at least one set of the sets associated with the defined interconnection cell; (C) using the assigned at least one boundary value, forming a plurality of discrete respective set combinations, and (D) for the interconnection cell, processing data from the plurality of respective formed set combinations into respective corresponding data record clusters. The strategic method for process control is a continuation-in-part of a Knowledge-Engineering Protocol-Suite, (U.S. patent application Ser. No. 09/588,681 filed on 7 Jun.

Abstract: A method, system, and medium of modeling and/or for controlling a manufacturing process is disclosed. The method includes the steps of identifying one or more input parameters that cause a change in output characteristics, defining global nodes using estimated maximum and minimum values of the input parameters, and defining a mathematical equation that calculates a predicted output characteristic for each node. The method also includes the steps of receiving at least one empirical data point having one or more input parameter values and at least one empirical output value and adjusting the predicted output values at the nodes based on a difference between the at least one empirical output value and the predicted output characteristic calculated using the mathematical equation based on the one or more input parameter values.

Abstract: An apparatus for the analysis of a process having parameter-based faults includes: a parameter value inputter configured for inputting values of at least one process parameter, a fault detector, configured for detecting the occurrence of a fault, a learning file creator associated with the parameter value inputter and the fault detector, configured for separating the input values into a first learning file and a second learning file, the first learning file comprising input values from a collection period preceding each of the detected faults, and the second learning file comprising input values input outside the collection periods, and a learning file analyzer associated with the learning file creator, configured for performing a separate statistical analysis of the first and second learning files, thereby to asses a process status.

Abstract: A method for controlling at least one characteristic of a product of an industrial batch process. The method comprising the steps of creating a hierarchical knowledge tree describing the process. Following the creation of a knowledge tree a learning process occurs. This leads to the creation of a global model. During the execution of a batch process, the global model is applied to dynamically target subsequent phase parameters based on already executed phases.

Abstract: A method and apparatus for providing early fault detection and alert generation in a multi-parameter process is provided. The method comprises defining a multi-dimensional space, each dimension representing a parameter of the process; applying an analysis of the process to the space in order to define regions of high and low probability of occurrence; measuring and mapping parameter values onto the space; and generating an alert whenever a parameter value is mapped into a region of low probability. The method and apparatus are also useful for identifying the cause of faults, adjusting the process to avoid faults and predicting a process-specific maintenance schedule.

Abstract: A Knowledge-Engineering Protocol-Suite is presented that generally includes methods and systems, apparatus for search-space organizational validation, and appurtenances for use therewith. The protocol-suite includes a search-space organizational validation method for synergistically combining knowledge bases of disparate resolution data-sets, such as by actual or simulated integrating of lower resolution expert-experience based model-like templates to higher resolution empirical data-capture dense quantitative search-spaces. Furthermore, from alternative technological vantages, the suite relates to situations where this synergetic combining is beneficially accomplished, such as in control systems, command control systems, command control communications systems, computational apparatus associated with the aforesaid, and to quantitative modeling and measuring tools used therewith.

Abstract: In an automatic decision-making system, a method and a tool for the reduction of the dimension of data mining, which is automatically coupled to an empirical predictor of the system. The method includes a qualitative modeling of the interrelations between various objects whose attributes are relevant to a score made by the predictor according to which decisions are made, wherein this relevancy is determined by an input of a domain expert to the problem in hand. The model is called a Knowledge-Tree and its conclusions are represented by a graphical symbolization called the Knowledge-Tree map. Data mining, which follows the construction of the Knowledge-Tree map regards only datasets which are associated with logical and validated branches of the knowledge tree. Because the expert input which reduces the dimension of data mining was completed prior to data mining, interception by human reasoning is not needed after data mining and the decision making process can proceed automatically.

Abstract: A method of modeling a monitorable stage in a process is provided.

Abstract: A method and system to enhance yield in multi-process manufacturing. The method comprising the translation of a performance parameter of a product into input variables to operate tools carrying our cooperating processes which built a structural element which determines the performance parameter, wherein the individual tools are process controlled. The method further comprising the integration of process control of individual separate processes or of stages in a process, into a combined and comprehensive (modular) process control in which the process parameters of a process are enslaved to accomplish the target output of the final process. Hence target output values of intermediate processes are dynamically reassigned during the manufacturing with respect to their initially designed values, in accordance with the output of their cooperating processes.

Abstract: A method, system, and medium of modeling and/or for controlling a manufacturing process is disclosed. The method includes the steps of identifying one or more input parameters that cause a change in output characteristics, defining global nodes using estimated maximum and minimum values of the input parameters, and defining a mathematical equation that calculates a predicted output characteristic for each node. The method also includes the steps of receiving at least one empirical data point having one or more input parameter values and at least one empirical output value and adjusting the predicted output values at the nodes based on a difference between the at least one empirical output value and the predicted output characteristic calculated using the mathematical equation based on the one or more input parameter values.

Abstract: Apparatus for control of a complex process, said process being described by a plurality of input variables, a plurality of intermediate variables and a plurality of output variables having relationships therebetween such that ones of said inputs and said intermediate variables effect respectively different output variables, each of said output variables having a target, said apparatus comprising an optimizer for finding an optimum value for respective ones of said input and intermediate variables to maximize a summed convergence of said output variables to said targets.

Abstract: A method and apparatus for providing early fault detection and alert generation in a multi-parameter process is provided. The method comprises defining a multi-dimensional space, each dimension representing a parameter of the process; applying an analysis of the process to the space in order to define regions of high and low probability of occurrence; measuring and mapping parameter values onto the space; and generating an alert whenever a parameter value is mapped into a region of low probability. The method and apparatus are also useful for identifying the cause of faults, adjusting the process to avoid faults and predicting a process-specific maintenance schedule.

Abstract: A method for controlling at least one characteristic of a product of an industrial batch process. The method comprising the steps of creating a hierarchical knowledge tree describing the process. Following the creation of a knowledge tree a learning process occurs. This leads to the creation of a global model. During the execution of a batch process, the global model is applied to dynamically target subsequent phase parameters based on already executed phases.

Abstract: Apparatus for control of a complex process, said process being described by a plurality of input variables, a plurality of intermediate variables and a plurality of output variables having relationships therebetween such that ones of said inputs and said intermediate variables effect respectively different output variables, each of said output variables having a target, said apparatus comprising an optimizer for finding an optimum value for respective ones of said input and intermediate variables to maximize a summed convergence of said output variables to said targets