Machine learning can generate massive business value for semiconductor manufacturers at every step of their operations, from predicting chip defects to optimizing the inventory management and shipping scheduling. PredictNow.ai’s solutions are designed to avoid replacing the existing and well-trusted manufacturing formulas. Instead, we use machine learning to improve and correct the output of these formulas.
Machine learning can learn from past sensor data and previous manufacturing failures to predict probability of failure in real time.
Corrective AI can compute the optimal cycle time by learning from past inputs and corresponding cycle times, given fab details, real-time factors, and other constraints.
Machine learning automatically learns from past inputs and corresponding outputs to create a function that adjusts the production control in real-time to correct for expected defects.
We will work with your process engineers and existing data to develop a larger, more detailed dataset that can be used to incorporate all the relevant data in the manufacturing process, enabling more accurate predictions. Our proprietary CPO technique will then be applied with this expanded dataset to optimize the manufacturing processes with effective machine learning optimizations.
First, both parties tentatively agree on a proposed collaboration and sign a Mutual NDA.
Next, a 3-month Proof of Concept project is negotiated and initiated. Objectives to be outlined in a non-binding Letter of Intent.
Afterwards, PredictNow.ai researchers will conduct a proof of concept project to prove the effectiveness of the project.
Lastly, PredictNow.ai and the client sign a contract for a minimum of one year duration.
To inquire about starting a Proof of Concept with PredictNow.ai or if you have any questions, please fill out the contact form below and we’ll get back to you as soon as possible.