Abstract: A method for controlling a cutting tool in a CNC machine and a device using the method receives contours of workpieces generated by a first measuring machine, inputs the first contour parameters into a calculation model to output first compensation values of the cutting tool, the calculation model being a time sequences model established according to contour sets of the workpieces, and the contour sets include at least one historical contour of the workpieces. The device further determines whether the first compensation values of the cutting tool are greater than, equal to or smaller than a preset value, and sends the first compensation values of the cutting tool to a machine.

Abstract: A method for controlling a cutting tool in a CNC machine and a device using the method receives contours of workpieces generated by a first measuring machine, inputs the first contour parameters into a calculation model to output first compensation values of the cutting tool, the calculation model being a time sequences model established according to contour sets of the workpieces, and the contour sets include at least one historical contour of the workpieces. The device further determines whether the first compensation values of the cutting tool are greater than, equal to or smaller than a preset value, and sends the first compensation values of the cutting tool to a machine.

Abstract: A method for controlling and adjusting a machining parameter of a processing machine detects and acquires information of workpieces during processing, and calculates an error compensation depending on the detected information and a mathematical model. The error compensation is compared with a first preset value and a determination made as to whether the error compensation is greater than a first preset value. The machining parameter is adjusted when the error compensation is not greater than the first preset value, the processing machine can be stopped if greater. An apparatus, and a non-transitory computer readable medium for controlling the machining parameter are also disclosed.

Abstract: A thermal process system. The thermal process system comprises a thermal processor, a metrology tool, and a controller. The thermal processor performs a thermal process as defined by a heating model to form a film on a wafer surface. The metrology tool, interfaced with the thermal processor, inspects thickness of the film. The controller, coupled with the thermal processor and the metrology tool, generates the heating model of the thermal processor and calibrates the heating model according to a preset slope coefficient matrix and the measured thickness.

Abstract: A thermal process system. The thermal process system comprises a thermal processor, a metrology tool, and a controller. The thermal processor performs a thermal process as defined by a heating model to form a film on a wafer surface. The metrology tool, interfaced with the thermal processor, inspects thickness of the film. The controller, coupled with the thermal processor and the metrology tool, generates the heating model of the thermal processor and calibrates the heating model according to a preset slope coefficient matrix and the measured thickness.

Abstract: A lithographic apparatus for forming a patterned resist layer and a method for forming a microelectronic product both employ a lithographic exposure tool controller designed to: (1) receive input data for at least one non-environmental variable that influences an exposure dose when forming a patterned resist layer from a blanket resist layer while employing a lithographic exposure tool; and (2) determine the exposure dose for forming the patterned resist layer from the blanket resist layer while employing the input data. The apparatus and method provide for forming the microelectronic product with enhanced dimensional control.

Abstract: A method and a system for analyzing a semiconductor manufacturing process includes a semiconductor manufacturing process that can generate sets of input and output data. Principal components are generated from the set of input data, and a set of principal component score data are determined based on the principal components. A relationship between the sets of input and output data is determined from the principal component score data and the output data. The system includes at least one storage device and a processor. The storage device stores input data and output data from the semiconductor manufacturing process. The processor is coupled to the storage device. The processor determines principal components from the input data, a set of principal component score data based on the principal components, and a relationship between the input and output data from the principal component score data and the output data.

Abstract: A multiple run by run process is described. A plurality of tools and a plurality of products to be run on the tools are provided. A desired recipe is calculated for each product on each tool based on a previous recipe used for each product on each tool and deviation of a parameter from a target value. Thereafter, the plurality of products is run on the plurality of tools. The desired recipe is updated after each run of each tool.

Abstract: A multiple run by run process is described. A plurality of tools and a plurality of products to be run on the tools are provided. Tool effects and product effects on a parameter are identified for each tool and each product. A desired recipe is calculated for each product on each tool based on the tool effects and product effects identified. Thereafter, the plurality of products is run on the plurality of tools. The desired recipe is updated after each run of each tool. Tool aging is calculated after each run of each tool based on the desired recipe used.

Abstract: A multiple run by run process is described. A plurality of tools and a plurality of products to be run on the tools are provided. Tool effects and product effects on a parameter are identified for each tool and each product. A desired recipe is calculated for each product on each tool based on the tool effects and product effects identified. Thereafter, the plurality of products is run on the plurality of tools. The desired recipe is updated after each run of each tool. Tool aging is calculated after each run of each tool based on the desired recipe used.