Data processing: generic control systems or specific application – Generic control system – apparatus or process – Optimization or adaptive control
Reexamination Certificate
2000-01-11
2002-11-05
Black, Thomas (Department: 2121)
Data processing: generic control systems or specific application
Generic control system, apparatus or process
Optimization or adaptive control
C700S109000, C700S032000
Reexamination Certificate
active
06477432
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
This invention relates to quality control systems for a manufacturing process and more particularly to inspection sampling methods and systems therefor.
2. Description of Related Art
U.S. Pat. No. 5,150,289 of Badavas for “METHOD AND APPARATUS FOR PROCESS CONTROL” shows a process control system. A statistical process control system provides asymmetrical nonlinear automatic closed-loop feedback control. The system applies to the control of equipment that responds to a controlled variable signal to vary a measurable characteristic of a process. The system uses an accumulated deviation of a measured subgroup means minus a target value, divided by the subgroup standard deviation, to modify the manipulated variable each time the accumulated value exceeds a decision interval above or below the target. The system permits the use of independent slack variables subtracted from the accumulated deviation to model the underlying process more closely. The system permits the use of independent alarm values and variable gains to permit greater process control.
U.S. Pat. No. 5,497,331 of Iriki et al. for “SEMICONDUCTOR INTEGRATED CIRCUIT DEVICE FABRICATION METHOD AND ITS FABRICATION APPARATUS” discloses a quality control system for a semiconductor manufacturing line. A semiconductor integrated circuit device fabrication technique improves the accuracy of element qualities by considering the influence of interaction of element quality parameters in the quality control of semiconductor fabrication processes and also by improving the product yield estimation accuracy to improve production efficiency. First, an initial value of a membership function is set. Then element quality parameters and a combined quality parameter are expressed by membership functions in fuzzy control in a semiconductor fabrication apparatus for automating fabrication by connecting a computer with measuring instruments and processors by communication devices. The combined quality parameters are fuzzy-inferred from the element quality parameters using these membership functions. Inference rules are adjusted by data of the actual processes. Membership functions of the obtained element quality parameters are converted into an element quality control standard, and the semiconductor integrated circuit device fabrication processes are controlled according to the standard.
U.S. Pat. No. 5,465,221 of Merat et al. for “AUTOMATED PROCESS PLANNING FOR QUALITY CONTROL INSPECTION” shows an automated process planning for quality control inspections. A computer is used for generating a part inspection plan for a coordinate measuring machine, in a feature-based rapid design system, having a Feature-Based Design Environment, an Episodal Associative Memory, Fabrication Planning, and an Inspection Plan, with features which include form features which define the form or shape of the part, manufacturing features, inspection features, and geometric and design features. An Inspection Plan includes interaction means wherein the inspector interacts with the system to guide it to a desired results and the inspector can define setups, measurement points, sequence for the points, and the via points. A learning process is included so that desired sequence input from the inspector is sent to discovery means to organize patterns and to define rules. This creates a self-improving expert system by recalling relevant past experiences, and learning from the desired sequence input from the inspector.
Commonly assigned U.S. Pat. No. 5,862,054 of Li for “PROCESS MONITORING SYSTEM FOR REAL TIME STATISTICAL PROCESS CONTROL” shows a method of monitoring for real time process control. The method monitors process parameters from multiple process machines to provide real time statistical process control (SPC). The implementation applied to ion implantation of wafers. The method has applicability where there are a number of process machines having a number of process parameters and close continuous sampling of data is required. The process parameters are collected on a single computer over a single network, and each parameter is analyzed and displayed separately for each process and process machine. Statistical variables like Cp and Cpk are calculated and presented on the computer screen along with graphs of the various parameters for a particular process machine. Data is aged out of the computer to an archival database under the control of a manufacturing information system and connected to a company wide network.
SUMMARY OF THE INVENTION
This invention teaches a statistical in-process quality control sampling system which adjusts the sampling rate dynamically.
There are many inspection steps defined in manufacturing process to find defects when the process is being tested for the first time. In addition, for a new product, a heavy burden of inspection work is also necessary. However, for a mature product, in order to save costs the inspection sampling rate may be reduced.
Objects of this invention are as follows:
1. Reduce inspection cost and keep high product quality.
2. Adjust the inspection sampling frequency by process stability dynamically.
3. Provide a systematic method for controlling the inspection sampling frequency.
In this invention, the stability of the process is considered to be a factor to be considered in selection of the appropriate sampling rate setting. A systematic management and operation method is also designed to guarantee that the dynamic sampling inspection steps are executed exactly as required for optimum performance.
Advantages of this invention are as follows:
1. The invention provides systematic setting of the sampling frequency rule based on process stability data to reduce inspection cost and keep high product quality.
2. This is a systematic method to manage the inspection operation.
In accordance with this invention, a system and method for managing quality control in a manufacturing plant for processing lots of work in process (WIP) for at least one product, comprises a manufacturing process which includes a manufacturing executive system (MES) which provides inspection data to a statistical process control (SPC) database, and an SPC analyzer for analyzing the inspection data and providing a sampling rate rule output to a sampling rate database. A server supplies the sampling rate rule to the MES. The MES tests a condition as to whether a lot of WIP should be sampled. If the condition is met, then provide an inspect control signal for inspection to the plant for inspecting the lot. If the condition is not met, then branch away from the control signal to provide an alternative control signal to pass on to the next process step in the plant. Preferably, the sampling rate rule is adjusted dynamically to adjust the sampling rate ratio. The SPC database stores the inspection data of products in the plant and the SPC analyzer provides analysis of the inspection sampling frequency of products in the plant; a sampling rate control under operator control for modification of the sampling rate rule in the sampling rate database. The server provides a background server function.
REFERENCES:
patent: 5150289 (1992-09-01), Badavas
patent: 5465221 (1995-11-01), Merat et al.
patent: 5497331 (1996-03-01), Iriki et al.
patent: 5761064 (1998-06-01), La et al.
patent: 5862054 (1999-01-01), Li
Chen Shun-An
Chu Constance Y.
Hsu Tzu-Jeng
Hsu Ying-Wei
Ackerman Stephen B.
Barnes Crystal J.
Black Thomas
Jones II Graham S.
Saile George O.
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