Real-time Learning Temperature Control for Increased Throughput in LED Manufacturing

This Small Business Innovative Research (SBIR) Phase I project will demonstrate the feasibility of an innovative temperature control technology for Metal-Organic Chemical Vapor Deposition (MOCVD) process used in the fabrication of Multi-Quantum Well (MQW) LEDs. The proposed control technology has the strong potential to improve both throughput and performance quality of the manufactured LED. The color of the light emitted by an LED is a strong function of the substrate temperature during the deposition process. Hence, accurate temperature control of the MOCVD process is essential for ensuring that the LED performance matches the design specification. The Gallium Nitride (GaN) epitaxy process involves depositing multiple layers at different temperatures. Much of the recipe time is spent ramping from one process temperature to another, adding significant overhead to the production time. To increase throughput, the process temperature must transition over a range of several hundred degrees Centigrade many times with as little overshoot and undershoot as possible, in the face of several sources of process disturbance such as changing emissivities. Any throughput increase achieved by faster ramping must also satisfy the constraint of strict temperature uniformity across the carrier so that yield is not affected. SC Solutions is a leading supplier of embedded real-time temperature control technology for MOCVD systems used in LED manufacturing. SC’s Multiple Input Multiple Output (MIMO) temperature controllers use physics-based models to achieve the performance demanded by our customers. However, to meet DOE’s ambitious goals of cost reduction of LED products, a new generation of temperature controllers has to be developed. SC believes that the proposed control technology will be made feasible by the confluence of mathematical formulation as a convex optimization problem, new efficient and scalable algorithms, and the increase in computational power available for real-time control. In Phase I, SC Solutions will formulate a control system (open and closed-loop) which can steer the MOCVD heat transfer process from an uncertain initial state to as close as possible to a target state while maintaining control constraints and keeping the states (temperatures) within a desired range. Model errors and/or uncertain model parameters severely limit the performance. SC Solutions therefore propose a real-time, model- adaptation-with-learning strategy to overcome these limitations. SC Solutions would start with an initial physics- based model, use data to adapt model parameters to match system behavior, and perform real-time convex optimization using the updated model. In Phase 1, SC Solutions will thus demonstrate feasibility in simulation. In Phase II, SC Solutions will expand the capabilities of this method, e.g., to incorporate robustness, and implement the prototype controller on a commercial MOCVD system of our industrial partner. The proposed program for developing an innovative temperature controller for LED manufacturing process has the potential to reduce manufacturing costs by as much as 20%, and maintain U.S. leadership in the production of semiconductor manufacturing equipment. Commercial Applications and Other Benefits: The proposed program for developing an innovative temperature controller for epitaxial deposition of GaN for LED manufacturing process has the potential to reduce manufacturing costs by as much as 20%. This novel control technology will help maintain U.S. leadership in MOCVD equipment used for LED and other semiconductor applications. The reduction in manufacturing costs will help the LED market keep pace with DoE’s goals of reducing the price of LED lighting by a factor of ten over this decade.