Abstract: Techniques for determining a decision to acquire units of an item to be inventoried may be provided. For example, a demand for an item may be simulated to determine a consumption of a capacity for inventorying the item. A discrepancy between the consumption of the capacity and the capacity may be determined. An opportunity cost associated with the capacity may be updated based at least in part on determining that the discrepancy fails a convergence criterion. The opportunity cost may indicate a value associated with using the capacity. The consumption of the capacity may be simulated based at least in part on the updated opportunity cost. A resulting discrepancy may be determined. If the resulting discrepancy meets the convergence criterion, the decision to acquire the units of the item may be generated based at least in part on the updated opportunity cost.

Abstract: In one embodiment, a system and method of predicting sale transaction conversion rate of an item operates through a search of information in response to a query over a network. The item can be included in a category of items. Information for other relevant items of the category is available through network query and historical data, among others. Respective information for the other items of the category is available to the method.

Abstract: Methods and systems for optimization of task execution are disclosed. A definition of a task is received. A plurality of parameter values for execution of the task are selected based on an execution history for a plurality of prior tasks performed for a plurality of clients. The plurality of parameter values are selected to optimize one or more execution constraints for the execution of the task. The execution of the task is initiated using one or more computing resources configured with the selected parameter values.

Abstract: Methods and systems are described for remotely monitoring a plurality of distributed remote storage devices. An example computer implemented method includes locally collecting monitoring data for one of the plurality of distributed remote storage devices, and periodically sending at least one of an aggregate of the locally recorded monitoring data and a summary of the locally recorded monitoring data to a remote location. The remote location includes at least one of another one of the plurality of distributed remote storage devices, at least one central server, and a set of the plurality of distributed remote storage devices.

Abstract: A system and method for planning and configuring the components of a modular computing system is provided. In some embodiments, the method for planning an implementation of a modular computing system comprises presenting a user interface at a display device, the user interface including a plurality of user-selectable objects, each of the user-selectable objects representing a component of the modular computing system. A user selection is received via a user input device. The user selection is from among the user-selectable objects and specifies one of an enclosure, an existing component, and a future component of the modular computing system. A representation of the specified one of an enclosure, an existing component, and a future component is displayed at a display device. The user selection is verified with respect to an implementation guideline. An indicator of whether the user selection meets the implementation guideline is displayed at the display device.

Abstract: Techniques described herein relate to the classification of fall events for PER (personal emergency response) devices. In one implementation, data relating to acceleration events that occurred at the PER devices may be received. The data relating to the acceleration events may be associated with indications of whether the acceleration events correspond to fall events of users of the PER devices. A classification model may be trained based on the data relating to the acceleration events and the indications of whether the data relating to the acceleration events corresponds to the fall events. The classification model may be transmitted to at least some of the PER devices to update a previous version of the classification model at the at least some of the PER devices.

Abstract: A bioreactor control system comprises a batch server for controlling a bioreactor system in response to a recipe, a batch software system for generating a control sequence for the bioreactor system via the batch server for implementing the recipe, and a recipe conversion system that inputs the recipe into the batch software system. Preferably, the recipe conversion system reads a word processor file containing the recipe and interprets styles applied to text in the word processor file as indicating equipment and phases of the recipe to the recipe conversion system. Generally, the bioreactor system includes one or more bioreactors and additional hardware to perform the upstream and downstream processing. The document properties of the word processor file containing the recipe are applied as header information for the recipe input into the batch software system.

Abstract: Mechanisms are provided for dynamically determining one or more automation levels for tasks of a workflow. The mechanisms receive a workflow from a source component and receiving context and state information for an environment in which the workflow is to be performed. One or more tasks and associated task attributes are identified in the workflow and applying one or more automation rules to the context and state information and the task attributes to generate one or more automation level settings from the one or more tasks. The one or more tasks are performed in the environment in accordance with the one or more automation level settings. The automation level settings specify a degree of automation to be used when performing the one or more tasks.

Abstract: Reflectance measurements indicative of light reflecting relative to solar module glass can be received. It can be determined whether the reflectance measurements are within tolerance for the solar module glass.

Abstract: A method and system of optimizing a complex manufacturing process performed to achieve one or more processing objectives for the process and/or a component produced by the process. The system includes a graphical user interface, a process module, and an optimization module. The process module includes a training module, an empirical relationships database, an analytical equations database, a heuristic knowledge database, and a process models database. The graphical user interface is used to input one or more processing variables and constraints for the processing objective. The training module generates empirical relationships from the processing variable and empirical data obtained from the manufacturing process. The process module generates a process model that takes into consideration heuristic knowledge of the manufacturing process, empirical relationships, and optionally analytical equations relating to the manufacturing process.

Abstract: A method of extending advanced process control (APC) models includes constructing an APC model table including APC model parameters of a plurality of products and a plurality of work stations. The APC model table includes empty cells and cells filled with existing APC model parameters. Average APC model parameters of the existing APC model parameters are calculated, and filled into the empty cells as initial values. An iterative calculation is performed to update the empty cells with updated values.

Abstract: Described herein are methods, apparatuses, and systems for determining adaptive predictive algorithms for virtual metrology. In some embodiments, a computer implemented method identifies a plurality of predictive algorithms. The method determines when to use one or more of the plurality of predictive algorithms to predict one or more virtual metrology variables in a manufacturing facility.

Abstract: A method to evaluate, determine and optimize production parameters for a coating application of a UV cationic polymerizable coating system to a substrate is provided. The method is based on a simulation model which includes both shadow and dark cure processes. Both of an active center generation process and the active center diffusion process are mathematically described. In the model, the two processes are considered separately since they are driven by different fundamental phenomena and occur on different timescales. Evaluation or prediction of the effect of process variables on the curing of a cationic coating of a complex substrate according to the described method allows characterization and understanding of process variables which may save set-up costs and improve production efficiency.

Abstract: A method of constructing an optimized network simulation environment according to the present invention includes the steps of identifying communication equipment models for relaying a message to/from real equipments out of communication equipment models within a network model, as major models, calculating the order of abstraction priority for major models, performing batch-mode abstraction for non-major models, driving a simulation, determining whether a difference between a simulation execution time and an actual time spent is within an allowable delay value, performing adaptive abstraction for the major models, and evaluating a result of the simulation. If the method according to the present invention is used, a real-time simulation having fidelity and reliability for the function and operation of real equipments can be guaranteed.

Abstract: A wafer fabrication outcome, such as wafer yield or wafer lifetime, is predicted by excluding uncontrollable but measurable internal/external noises of a DOE system, and by rendering relations between wafer design variables and wafer outcome outputs to be more causal, as well as the relations between variances for each of the wafer design variables and the wafer outcome outputs. With the aid of a wafer fabrication outcome predicting model formed by the more causal relations, precision of predicting wafer outcomes can be raised, and performance of wafer fabrication can be thus raised as a result.

Abstract: A method for importing data from a first system into a second system includes receiving configuration information about data storage structures in the first and second systems and information about communicating with the first and second systems. Information to be used in creating an import configuration file is entered via a user interface. The import configuration file is for use in preparing the second system to receive data from the first system. Based on the information about data storage structures, the information about communicating with the first and second systems, and the information entered via the user interface, the import configuration file is created to prepare the second system to receive data from the first system. Based on the import configuration file, data is transferred from the first system into the second system.

Abstract: System(s) and method(s) are provided for adjustment and analysis of performance of a tool through integration of tool operational data and spectroscopic data related to the tool. Such integration results in consolidated data that enable, in part, learning at least one relationship amongst selected portions of the consolidated data. Learning is performed autonomously without human intervention. Adjustment of performance of the tool relies at least in part on a learned relationship and includes generation of process recipe parameter(s) that can adjust a manufacturing process in order to produce a satisfactory tool performance in response to implementation of the manufacturing process. A process recipe parameter can be generated by solving an inverse problem based on the learned relationship.

Abstract: A method and system for modifying a substrate, such a thin film, solar panel or the like detects error and/or variance and, if needed, re-optimizes the product design and/or process parameters on the fly, so that product can meet the product specification. This allows for methods and systems of process control that can adaptively change the product design in real time.

Abstract: A method and a system for optimization of parameters for a recovery boiler in a pulp mill are disclosed. An exemplary method is based on use of a first principle mathematical model to estimate parameters that are otherwise not measurable, to accurately control the performance of the recovery boiler. In addition, a method is disclosed to use estimated parameters of a recovery boiler to control and stabilize the processes downstream of the recovery boiler. A system is also disclosed to carry out a method for control and optimization of performance and operational parameters of a recovery boiler.

Abstract: Properties of an end product, such as paper, paperboard or board, are important for the user of the end product. To be able to manufacture an end product of desired quality, it is important to know what kind of paper pulp used for manufacturing the end product results in a particular kind of property of the end product. Embodiments provide a method and an apparatus for generating a model, which model connects at least one property of the end product with at least one property of the paper pulp. On the basis of the model, also the manufacturing process can be controlled.

Abstract: Methods and apparatus are disclosed herein. In some embodiments, methods of controlling process chambers may include predetermining a relationship between pressure in a processing volume and a position of an exhaust valve as a function of a process parameter; setting the process chamber to a first state having a first pressure in the processing volume and a first value of the process parameter, wherein the exhaust valve is set to a first position based on the predetermined relationship to produce the first pressure at the first value; determining a pressure control profile to control the pressure as the process chamber is changed to a second state having a second pressure and a second process parameter value from the first state; and applying the pressure control profile to control the pressure by varying the position of the exhaust valve while changing the process chamber to the second state.

Abstract: An exemplary embodiment of the present disclosure illustrates an automated mass production method, adapted for an automated mass production system in manufacturing at least an electronic device having a storage unit, the method includes steps of: determining a protocol type of the Auto Handler to select one of the agents; establishing a first communication protocol communication between the MP tool module and the selected agent; establishing a second communication protocol communication between the selected agent and the Auto Handler; the Auto Handler outputting a processing command to the selected agent; the selected agent converting the processing command into a MP tool module executable MP tool instruction; and the selected agent outputting the corresponding MP tool instruction to the MP tool module so as to have the MP tool module executed the MP tool instruction to automatically perform a corresponding mass production process to the electronic device.

Abstract: An energy-saving optimizing program works closely with conventional process simulation programs by applying energy saving paradigms embodied in script files that may review data inherent in the simulation program to identify possible energy-saving opportunities. When the script files identify a possible energy savings, they may interact with the simulation program to evaluate the savings potential and present the same to a user. In this way opportunistic energy savings may be provided even for processes that resist close form global optimization.

Abstract: A field device resident algorithm receives one or more diagnostic inputs and generates actionable service information. The algorithm(s) can be changed or updated after the manufacture of the field device. The actionable service information can be displayed locally or sent over a process control loop. A prediction engine can be employed to determine a period within which such service should be completed.

Abstract: Aspects of the subject matter described herein relate to analyzing data and providing recommendations regarding computing assets. In aspects, data is collected from computing assets and aggregated in a data repository. A data analyzer analyzes the data to determine problems associated with the computing assets. Work done to identify a problem with one computing asset may be used to identify problems with or provide recommendations for other computing assets controlled by the same or different entities. When a problem is identified in a computing asset, a recommendation may be proactively provided to an entity associated with the computing asset.

Abstract: A manufacturing executing system (MES) contains computing devices and software tools to control machines involved in a production process. The MES is configured to realize production requirements having at least one segment requirement. The MES further contains measures for a user to define whether a segment requirement is repeatable, and a database configured to store segment requirements. The database contains for each segment requirement: a dedicated area to store each segment requirement repeatability status; a dedicated area to store at least a current value of a parameter acquired during an execution of the segment requirement and representing the result of the execution of the segment requirement; and a dedicated area to store expected values of the parameter. Finally, the MES contains a coordinator operable to communicate with the database to access the segment requirement, and operable to determine whether the execution of a segment requirement has to be repeated.

Abstract: Performance of a manufacturing tool is optimized. Optimization relies on recipe drifting and generation of knowledge that capture relationships among product output metrics and input material measurement(s) and recipe parameters. Optimized recipe parameters are extracted from a basis of learned functions that predict output metrics for a current state of the manufacturing tool and measurements of input material(s). Drifting and learning are related and lead to dynamic optimization of tool performance, which enables optimized output from the manufacturing tool as the operation conditions of the tool changes. Features of recipe drifting and associated learning can be autonomously or externally configured through suitable user interfaces, which also can be drifted to optimize end-user interaction.

Abstract: A tire measurement system includes a computer with various memory/media elements for storing raw and transformed tire measurement data (e.g., a data set of measured radial or lateral run-out values) as well as software in the form of computer-executable instructions, which are executed by a processor to filter selected run-out values within the obtained data set that spike above adjacent measurements, identify selected ones of the filtered run-out values that lie on a convex hull surrounding the entire set of values, and perform interpolation of the identified selected ones of the run-out values that lie on the convex hull to obtain a final data set of filtered run-out measurements. Similar steps can be performed on an inverted data set to better detect sidewall deformation features such as sidewall depressions.

Abstract: A method of generating a product recipe for execution by a batch process in an automated manufacturing environment, such the product recipe is associated with a plurality of actions, a set of transitions, and a set of parameters, and such that the plurality of actions define a plurality of logical levels including a phase level at which the batch process interacts with equipment, includes receiving a procedure definition specifying the plurality of actions, receiving a transaction definition specifying the set of transitions so that each one in the set of transitions is associated with two or more of the plurality of actions, and receiving the set of parameters. Receiving the set of parameters includes receiving at least one dynamic input parameter that resolves to a value without obtaining the value from the product recipe or an operator prompt associated at the phase level of the product recipe.

Abstract: A system and method for optimizing a process for refining lignocellulosic granular matter such as wood chips use a predictive model including a simulation model based on relations involving a plurality of matter properties characterizing the matter such as moisture content, density, light reflection or granular matter size, refining process operating parameters such as transfer screw speed, dilution flow, hydraulic pressure, plate gaps, or retention delays, at least one output controlled to a target such as primary motor load or pulp freeness, and at least one uncontrolled output such as specific energy consumption, energy split, long fibers, fines and shives. An adaptor is fed with measured values of matter properties and measured values of controlled and uncontrolled outputs, to adapt the simulation model accordingly. An optimizer generates a value of the target according to a predetermined condition on a predicted uncontrolled output parameter and to one or more process constraints.

Abstract: A method to enable wafer result prediction includes collecting manufacturing data from various semiconductor manufacturing tools and metrology tools; choosing key parameters using an autokey method based on the manufacturing data; building a virtual metrology based on the key parameters; and predicting wafer results using the virtual metrology.

Abstract: A method and system for optimizing modules of a steel manufacturing process includes a plurality of manufacturing modules for a manufacturing process. Each of the modules have a plurality of steps. The plurality of modules include at least an upstream module, a casting module, and a downstream module. Each of the plurality of modules have parameters, and include at least one variable event. The variable event is adjustable for optimization of the manufacturing process while the parameters are being maintained for each of the plurality of modules. A communication system is used for exchanging information between the modules while the manufacturing process is occurring to adjust the at least one variable event for optimizing the manufacturing process.

Abstract: A method to predict a distribution of material properties of a cast component. In one form, the method includes accepting at least one of dendrite arm spacing data and porosity data that have been previously determined, as well as accepting casting geometry data and structural analysis geometric data, calculating material properties of the casting based on one or both of dendrite arm spacing data and porosity data at each of the various nodes within the casting FEA or FD mesh and mapping the calculated material properties to the various nodes of the finished part FEA mesh. The method may be used as a basis for conducting fatigue or a related durability analysis on the component.

Abstract: An etching control system controls exposure of a silicon workpiece to a spontaneous etchant. The system determines an amount of material to be removed from the silicon workpiece, based on metrology information corresponding to the silicon workpiece. An estimated etch time duration is determined for removing the amount of the material upon exposing the silicon workpiece to the spontaneous etchant for the estimated etch time duration. In some embodiments, the system monitors a change in mass of the silicon workpiece caused by exposure of the silicon workpiece to the spontaneous etchant to determine when the amount of the material has been removed from the silicon workpiece. Exposure of the silicon workpiece to the spontaneous etchant is stopped when the change in the mass of the silicon workpiece indicates that the amount of the material has been removed.

Abstract: Disclosed herein is a semiconductor manufacturing device including, a chamber, a sensor, a sticking probability calculating section, an acting section, and a control section.

Abstract: The present disclosure discloses a supply chain management system that can estimate manufactured item delivery times at a facility, manufactured item costs or prices, and dynamically control supply chain performance.

Abstract: Disclosed are various embodiments of a self healing andon system. One embodiment of the present disclosure includes a system comprising at least one server. The system further includes logic executed on the at least one server that retrieves a defect history associated with a vendor and at least one product from an inbound shipment from a memory. The at least one product is stocked in a materials handling facility, and the defect history is associated with a specified time period. The at least one server extracts at least one inventory defect from the defect history in a computer system and calculates an inventory defect rate. The at least one server imposes remedial measures if the inventory defect rate exceeds a specified threshold of the inventory defect rate.

Abstract: Computerized scheduling methods and computerized scheduling systems according to exemplary embodiments. A computerized scheduling method may be stored in a memory and executed on one or more processors. The method may include defining a main multi-machine scheduling problem as a plurality of single machine scheduling problems; independently solving the plurality of single machine scheduling problems thereby calculating a plurality of near optimal single machine scheduling problem solutions; integrating the plurality of near optimal single machine scheduling problem solutions into a main multi-machine scheduling problem solution; and outputting the main multi-machine scheduling problem solution.

Abstract: A method for designing a formed sheet-metal part using a computing system is described. The method typically includes performing a numerical simulation of the forming process and computing a local property variable associated with points of the part. Problem zones of the sheet-metal part are identified based on the numerical simulation, and a visual representation of the sheet-metal part, in which problem zones are identified, is displayed. Information about a problem zone, such as status of the problem zone and the problem zone's unique identifier, are visually displayed.

Abstract: A fabrication processing system is used to produce copper indium gallium selenide (CuIn1-xGaxSe2 or CIGS) thin film solar cells, more particularly to a fabrication processing system CIGS of thin film solar cells, equipped with real-time analysis facilities for profiling the elemental components of CIGS thin film using laser-induced breakdown spectroscopy. The system provides a process control system for determining whether abnormalities are present or not by measuring a physical and chemical properties on a continuous production process lines of CIGS thin film solar cell in real time, and performs a production and quality management at the same time by providing a feedback to CIGS fabrication process.

Abstract: Methods and production control systems are presented in which design of experiments are performed in situ and produce model parameter estimates that relate actuator set points to any number of response variables, and the model is periodically updated based on these designed experiments and used as the basis for determining actuator set points.

Abstract: The invention provides a systems and methods for creating Double Pattern (DP) structures on a patterned wafer in real-time using Dual Pattern Contact-Etch (DPCE) processing sequences and associated Contact-Etch-Multi-Input/Multi-Output (CE-MIMO) models. The DPCE processing sequences can include one or more contact-etch procedures, one or more measurement procedures, one or more contact-etch modeling procedures, and one or more contact-etch verification procedures. The CE-MIMO model uses dynamically interacting behavioral modeling between multiple layers and/or multiple contact-etch procedures. The multiple layers and/or the multiple contact-etch procedures can be associated with the creation of lines, trenches, vias, spacers, contacts, and gate structures that can be created during Double Patterning (DP) procedures.

Abstract: A method and a system control a manufacturing process of a plant via a MES system. The MES system is provided with a catalogue of a tool model, the catalogue of the tool model contains tool entities and tool methods on the tool entities. The tool entities contain engineering-time tool entities and run-time tool entities and the tool methods contain engineering-time tool methods and run-time tool methods. At engineering time or at run time, via a tool manager, the tool model catalogue is exposed and information on the tool model data is stored in a database. At engineering time, the specific engineering-time tool entities are defined by invoking engineering-time tool methods. At run time the specific tool entities are instantiated into run-time tool objects and the manufacturing process is controlled relative to physical plant tools by invoking the run-time tool methods on the run-time tool objects.

Abstract: Methods and apparatus for automated validation of semiconductor process steps are provided herein. In some examples, a method for validating a semiconductor process recipe includes: selecting a rule set describing an operating window for a semiconductor process tool; checking parameter values defined by steps in the semiconductor process recipe against limit-checking rules of the rule set to produce first results; determining step types from the steps in the semiconductor process recipe using step definition rules of the rule set to produce second results; checking transitions between the step types against step transition rules of the rule set to produce third results; and generating, using the computer, validation data for use of the semiconductor process recipe with the semiconductor process tool based on the first, the second, and the third results.

Abstract: According to various embodiments, a biofuel production system includes a plurality of parallel-operated fermenters, a cooling tower water system configured to supply cooling water to the plurality of parallel-operated fermenters, a chiller water system configured to supply chiller water to the plurality of parallel-operated fermenters, and a cooling system coupled to the plurality of parallel-operated fermenters, the cooling tower water system, and the chiller water system. The cooling system controls the flow rates of the cooling water and the chiller water to the plurality of parallel-operated fermenters based upon temperatures of fermentation products of the fermenters.

Abstract: For application to analog, mixed-signal, and custom digital circuits, a system and method to extract circuit-specific process/environmental corners that is yield-aware and/or specification-aware. Simulation data from previous Monte Carlo-based verification actions can be re-used.

Abstract: A scheduler system obtains a basic model of a manufacturing process for the production of one or more products. The basic model is based on a first set of data collected at a point in time from a plurality of tools used to manufacture the one or more products. The system incorporates a second set of data, which is collected from the plurality of tools after the first set of data, into the basic model to generate a comprehensive model of the manufacturing process. The second set of data reflects a current state of a factory. The system evaluates a plurality of scheduling policies using the comprehensive model and selects an optimal scheduling policy from the plurality of scheduling policies based on the comprehensive process model evaluation to achieve a manufacturing objective.

Abstract: A method performed by one or more computer processors imports data from a machinery monitoring system into a control system. The machinery monitoring system is a system that measures machine measurement parameters of a machine, and the control system is a system that controls processes in which the machine performs a function. The method includes accessing a first knowledge base containing information about communicating with the machinery monitoring system, and accessing a second knowledge base containing information about communicating with the control system. The method also includes extracting configuration information from the machinery monitoring system via a communication bus. Information is entered by a user for use in creating an import configuration file, which file is used in preparing the control system to receive data from the machinery monitoring system. The entering of information is performed via a user interface operatively connected to the one or more computer processors.

Abstract: A method comprises computing respective regression models for each of a plurality of failure bins based on a plurality of failures identified during wafer electrical tests. Each regression model outputs a wafer yield measure as a function of a plurality of device performance variables. For each failure bin, sensitivity of the wafer yield measure to each of the plurality of device performance variables is determined, and the device performance variables are ranked with respect to sensitivity of the wafer yield measure. A subset of the device performance variables which have highest rankings and which have less than a threshold correlation with each other are selected. The wafer yield measures for each failure bin corresponding to one of the selected subset of device performance variables are combined, to provide a combined wafer yield measure. At least one new process parameter value is selected to effect a change in the one device performance variable, based on the combined wafer yield measure.

Abstract: A method of generating capacity, production and inventory plans, over a designated planning horizon, which will optimize, with respect to a designated performance index, the operations of one or more bulk product blending and packaging plants and a specified number, ranging from zero to a certain count, of distribution centers while meeting key operating constraints. Also decision making tools and computer implemented programs for performing the method.