Assembly Line Test Parameter Substitution to Cut Cycle Time
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Solution Overview
Problem
Manufacturing time in assembly lines is inefficient due to redundant measurements, highly-correlated tests, and unnecessary testing processes, which can be optimized using data mining techniques to reduce cycle time and resource allocation.
Innovation Solution
Implementing data mining methods such as removing redundant tests, performing data cleaning and preprocessing, and substituting testing parameters with predictive models to streamline the manufacturing process, thereby identifying and eliminating unnecessary tests and optimizing test combinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive testing is performed on all products through the assembly line, then product quality and reliability are ensured, but manufacturing time and resource consumption increase significantly
Solution Approach 1:
The patent extracts and removes redundant tests from the assembly line testing process. By analyzing test correlations and identifying tests that do not contribute unique quality assurance value, the system eliminates unnecessary testing steps while preserving product quality through the remaining essential tests.
Solution Approach 2:
The patent merges highly correlated tests into single representative tests. When multiple tests measure similar quality attributes with high correlation, they are combined into one test that captures the essential quality information, reducing testing time while maintaining reliability.
2Measurement precision
If multiple redundant measurements and highly-correlated tests are performed, then measurement precision and quality assurance are improved, but device complexity and resource allocation increase
Solution Approach 1:
The patent identifies and removes redundant measurements and highly-correlated tests from the testing process. By analyzing measurement correlations and eliminating duplicate or overlapping tests, the system reduces testing complexity while preserving quality assurance through essential measurements.
Solution Approach 2:
The patent applies partial action by performing only the necessary subset of tests required for quality assurance. Instead of executing all possible tests, the system identifies and performs only those tests that provide unique quality information, eliminating excessive testing that adds complexity without improving precision.
3Reliability
If all tests are retained in the assembly line process, then comprehensive quality coverage is achieved, but productivity and manufacturing efficiency decrease
Solution Approach 1:
The patent extracts and eliminates tests that do not contribute to comprehensive quality coverage. By analyzing test correlations and identifying redundant quality checks, the system removes unnecessary tests while maintaining complete quality coverage through the optimized test set.
Solution Approach 2:
The patent changes the test portfolio parameters by removing redundant tests and keeping only essential ones. This parameter change in the testing process reduces the number of testing steps while maintaining quality coverage, thereby improving manufacturing efficiency and productivity.
Data Source
AI summary
Methods and systems of identifying a time reduction in a manufacturing time associated with a plurality of products. One system includes an electronic processor configured to receive training data. The electronic processor is also configured to determine a first set of testing parameters from the plurality of testing parameters to remove for the assembly line based on the training data and determine a second set of testing parameters to keep by removing the first set of testing parameters from the plurality of testing parameters. The electronic processor is also configured to determine a predictive model to replace the first set of testing parameters based on the training data associated with the second set of testing parameters, and automatically update a testing process for the assembly line to turn off the first set of testing parameters and use the predictive model in place of the first set of testing parameters.