A quality determination device includes an acquisition unit for acquiring a drive current during tapping, from a motor provided in a machine tool that performs tapping, and a determination unit for determining acceptance or rejection of a screw hole formed by the tapping, based on the drive current, an electric power of the motor obtained from the drive current, or a torque of the motor obtained from the drive current.

A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.

A manufacturing system is disclosed herein. The manufacturing system includes one or more stations, a monitoring platform, and a control module. Each station of the one or more stations is configured to perform at least one step in a multi-step manufacturing process for a component. The monitoring platform is configured to monitor progression of the component throughout the multi-step manufacturing process. The control module is configured to dynamically adjust processing parameters of each step of the multi-step manufacturing process to achieve a desired final quality metric for the component.

A solar concentrating system and installation has a plurality of solar collectors configured for receiving, reflecting, and concentrating radiation in a focal point. The solar concentrating system and installation increases the efficiency of current solar concentrating systems, such as those based on linear Fresnel collectors, by reducing focal distances and increasing the effective surface of the system.

Automated real-time risk-based regulatory process monitoring and controls are integrated to automation control systems. This allows for a flexible production process that allows continuous process verification. Data integrity is improved by evaluating the effectiveness of existing controls and by continually testing process accuracy and validity.

A method of detecting and classifying anomalies during semiconductor processing includes executing a wafer recipe a semiconductor processing system to process a semiconductor wafer; monitoring sensor outputs from a sensors that monitor conditions associated with the semiconductor processing system; providing the sensor outputs to models trained to identify when the conditions associated with the semiconductor processing system indicate a fault in the semiconductor wafer; receiving an indication of a fault from at least one of the models; and generating a fault output in response to receiving the indication of the fault.

The present invention teaches a process of measuring and grinding tools in can/cylindrical body production, allowing reduced production downtime, reduced cost and a predictive tool wear capability, which process allows more accurate stocking of tool inventory by means of tracking individual tools in use and providing advanced diagnostics to the tool room. This includes not just out-of-spec alarms from QA but also predictive alarms regarding cans produced by each tool, in-spec can weights and wall thicknesses, information on tool sizes being used in production, tools in inventory, pulled from inventory and other stock balancing information. The invention further teaches a system of equations for prioritizing grinding to maintain optimum tool inventory levels.

A method for monitoring process instances that are being executed and for eliminating process anomalies in the process instances is provided. In a monitoring step, a sensor, using a sensor definition, monitors a process log with respect to a process anomaly described in the sensor definition, and detects process instances or processes that have the process anomaly described in the sensor definition. In a correction step, for a process instance detected in the monitoring step, the process anomaly is eliminated at the runtime of the process instance.

A manufacturing process system comprises any number of assembly stations and test stations, a model unit, and any number of final products is provided. Any of a sample test method and the statistical distribution monitoring method performed by the model unit is configured to monitor the model quality after it is deployed and reduce potential unnecessary costs, such as warranty claim costs as a result of sending bad units to the customers, and rework costs as a result of predicting a good part as bad and wasting additional testing efforts on the bad parts. Further, both methods are configured to maximize the probability of detecting hazardous issues, while having control of the false alarm rate.

A system, computer program product and a method for detecting manufacturing process defects, the method may include: obtaining multiple edge measurements of one or more structural elements after a completion of each one of multiple manufacturing phases; generating spatial spectrums, based on the multiple edge measurements, for each one of the multiple manufacturing phases; determining relationships between bands of the spatial spectrums; and identifying at least one of the manufacturing process defects based on the relationships between the bands of the spatial spectrums.