Process Parameter Analysis for Input-Output Variation Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing manufacturing processes struggle to account for fluctuations in input values and unstable properties of subjects during product manufacturing, which can affect end product quality, particularly in cases where fluctuations are difficult to specify or control.
Innovation Solution
A critical process parameter analysis method and device that evaluate the degree of variation in system inputs and outputs for each motion in a manufacturing process, identifying critical process parameters through control difficulty and response variability indices to specify candidates affecting important quality characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If device-controlled motions are used in manufacturing process, then manufacturing precision is improved, but fluctuation in input values cannot be completely controlled leading to instability
Solution Approach 1:
The patent implements feedback by evaluating the degree of variation in system inputs and outputs for each motion, then using this evaluation to specify critical process parameters. This feedback mechanism allows the system to identify and control parameters that exhibit fluctuation, thereby improving input value stability while maintaining manufacturing precision.
Solution Approach 2:
The patent changes parameters by introducing motion parameters and evaluating their degree of variation. By analyzing how each motion parameter affects system input and output stability, the system identifies critical parameters that need control, transforming the approach from fixed device control to dynamic parameter-based control.
2Manufacturing precision
If critical process parameters are specified based on risk assessment and multivariate experiment, then manufacturing precision is improved, but fluctuation and instability in system input and output are not taken into consideration
Solution Approach 1:
The patent transitions from traditional risk assessment and multivariate experiment to a parameter-based evaluation approach. By introducing motion parameters and evaluating their degree of variation on system inputs and outputs, the method identifies critical process parameters that account for both quality characteristics and fluctuation stability.
Solution Approach 2:
The patent implements feedback by continuously evaluating the degree of variation in system inputs and outputs for each motion. This evaluation feeds into the critical process parameter specification, ensuring that parameters exhibiting fluctuation are identified and controlled, thereby improving reliability without sacrificing manufacturing precision.
3Ease of operation
If device control is used to execute motions, then ease of operation is improved, but complete control of input values is impossible leading to instability
Solution Approach 1:
The patent changes the control approach by introducing motion parameters and evaluating their degree of variation. Instead of relying solely on device control, the system analyzes how each motion parameter affects system input stability, identifying critical parameters that require special attention to maintain reliability while preserving ease of operation.
Solution Approach 2:
The patent implements feedback by evaluating the degree of variation in system inputs for each device-controlled motion. This feedback mechanism allows the system to identify where device control is insufficient and where additional parameter control is needed, thereby improving input value stability without compromising ease of operation.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
An object is to specify a critical process parameter candidate in a manufacturing process for manufacturing a product. A critical process parameter analysis method of an aspect of this invention includes: a variation evaluation step (S2,S3) of evaluating, for each of motions in a manufacturing process of a product, (a) a degree of variation in a system input being input into a subject system from an outside of the subject system according to a motion parameter set to execute each motion and (b) a degree of variation in a system output being output from the subject system in response to each motion, the subject system being a subject of the motions; and a critical process parameter candidate specifying step (S4) of specifying a critical process parameter candidate based on a result of evaluating, for each motion, the degrees of the variations in the system input and in the system output.