One of the biggest integrated circuit manufacturers needed a solution for inspecting production line failures before they occur. As product quality and production yields are more important than ever before, the IC vendor had to decrease the losses due to defects and increase the yield from its existing production facilities. Due to its high investment, high risk, and complicated processes involving silicon wafer production, the manufacturer had chosen to use Machine Learning (ML) solutions.
Use of Qualitest’s machine learning-guided solution for manufacturing to predict item defects ahead of time. The solution provided a prediction modeling environment that decreases time to production sustainably while ensuring accurate and stable prediction models for different manufacturing objectives.
For most modeling tasks, the process has four main phases.
The first phase is uploading the data and performing data exploration, and the second phase is applying predictive algorithms that automatically create an optimized prediction model out of more than 840 options.
The third phase is analyzing prediction KPIs and validating the model. The fourth phase is implementing the solution into a company’s production environment.
The company partnered with Qualitest to use its Machine Learning solution. The final model included three main components:
(a) Predictive failure for each production line.
(b) Root causes report for each production line.
(c) A dashboard for seamlessly presenting alerts to stakeholders.
For the predictive failure component, a dedicated prediction model was created. The model was fed with 250 expletory variables. Our auto machine learning tool distilled the significant features that contributed the most. It optimized the inner algorithm settings to secure the highest level of model performance.
Qualitest used complex data streams from multiple lines and product categories. The main model of predictive maintenance was built based on machine learning models ensemble. The next phase included the use of root cause analysis combined with prediction modeling for each line. Optimized alert timing was applied for each product. The model components are now part of the company’s production environment.
Qualitest ‘AI-powered Machine Learning Predictive Analytics solution’ proved to be fast, easy to use, and accurate when applied to complex data. The solution will enable the company to expand sales for each POS and increase operational efficiency while ensuring POS satisfaction.
