Abstract

This paper focuses on the technological development of core temperature estimation algorithm of multi-layer metal plates. It applies new control technology in the field of real time monitoring of semiconductor producing processes. To achieve real time core temperature estimation in semiconductor equipment processes, this paper will follow the order of: system description, model derivation, parameter identification, and design of a robust core temperature observer of multi-layer metal plates, which will then be cross validated with experimental data. In the metal heating system model proposed in this paper, external cooling is considered as an unknown interference. Since the system contains an unknown interference, the sliding mode observer (SMO) will use the equivalent conversion technique to tackle with the uncertainty. In order to improve the degree of freedom and flexibility in the design of the gain matrix, and considering the effects of parameter identification uncertainty, this paper introduces the multi-objective linear matrix inequality (LMI) in the design of the sliding mode observer to suppress the impacts of the non-matching uncertainty on the system and to reduce the gain matrix which also satisfies the convergence requirement of the designer. In terms of algorithm implementation, the parameters of the thermally processed multilayer plate model are first identified through the minimum difference filter (MDF), the data is then filtered offline, and lastly, the model parameter is derived using the least square (LS) method. The filtering technology can greatly improve the accuracy of parameter identification and improve the SMO estimation precision. Finally, the experimental data of the actual semiconductor machine and the estimation from the proposed method verifies the usefulness of the SMO in core temperature estimation of multi-layer metal plate heating systems.

Highlights

  • In the process of semiconductor manufacturing, the heater uses heat transmission to heat up industrial products to meet the requirements of the manufacturing process

  • This research focuses on the research and development of the core temperature estimation for semiconductor metal multi-layer boards

  • This method belongs to the research of new control technology applied to the real-time monitoring of semiconductor thermal processes

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Summary

INTRODUCTION

In the process of semiconductor manufacturing, the heater uses heat transmission to heat up industrial products to meet the requirements of the manufacturing process. In order to reach the final goal of smart semiconductor manufacturing in this study, several technical indicators will need to be established: A. physical system model derivation, B. system parameter identification, C. temperature characteristic curve experimental comparison, D. establishment of equation of system state, and E. design of a SMO. In this work, the related LMI formulation skills will be integrated into the robust observer design This particular study focuses on the thermal manufacturing process of semiconductor metal multi-layer boards and realizes the design of a highly robust core temperature SMO. 2) Effectively suppressing the influence of unknown external factors on the temperature estimation by making effective use of the structure limitations of the gain matrix in the design of the SMO. Of turning design problems into LMIs. Section 5 includes the numerical simulation results of the observer for system temperature estimation.

DISCRIPTION OF METAL HEATING SYSTEM
MATHEMATICAL MODELING
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PROBLEM FORMAULATION
SLIDING MODE OBSERVER DESIGN
QUADRATIC STABILITY ANALYSIS
PROOF OF THE EXISTENCE OF SLIDING MOTION
LINEAR MATRIX INEQUALITY REPRESENTATION OF SYSTEM CONTROL PROBLEMS
NUMERICAL SIMULATIONS
EXPERIMENTAL VERIFICATION AND ANALYSIS
SYSTEM IDENTIFICATION
DESCRIPTION OF REDUCED-ORDER MODEL
SLIDING MODE OBSERVER DESIGN AND
THE RESULT AND DISCUSSION OF TEMPERATURE
CONCLUSION
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