The Experts below are selected from a list of 312 Experts worldwide ranked by ideXlab platform

Vidosav D Majstorovic - One of the best experts on this subject based on the ideXlab platform.

  • multistage Manufacturing Process Control robust to inaccurate knowledge about Process noise
    Cirp Annals-manufacturing Technology, 2017
    Co-Authors: Dragan Djurdjanovic, Yibo Jiao, Vidosav D Majstorovic
    Abstract:

    Abstract A method for robust Control of quality errors in a multistage Manufacturing Process (MMP) is formulated, guaranteeing the product quality even under the worst-case scenario of uncertainties in the knowledge of noise characteristics. Simulations based on the error flow models in automotive cylinder head machining and lithography overlay Processes show that the new robust Control method increasingly outperforms the traditional stochastic Control approach as uncertainties in the knowledge of Process noise characteristics increase. It is also shown that Controlling MMP quality, while ignoring inaccuracies in the noise model could make quality even worse than if no Control is used.

Christopher A. Harrison - One of the best experts on this subject based on the ideXlab platform.

  • Semiconductor Manufacturing Process Control and monitoring: A fab-wide framework
    Journal of Process Control, 2006
    Co-Authors: S. Joe Qin, Gregory Cherry, Richard Good, Jin Wang, Christopher A. Harrison
    Abstract:

    The semiconductor industry has started the technology transition from 200 mm to 300 mm wafers to improve Manufacturing efficiency and reduce Manufacturing cost. These technological changes present a unique opportunity to optimally design the Process Control systems for the next generation fabs. In this paper we first propose a hierarchical fab-wide Control framework with the integration of 300 mm equipment and metrology tools and highly automated material handling system. Relevant existing run-to-run technology is reviewed and analyzed in the fab-wide Control context. Process and metrology data monitoring are discussed with an example. Missing components are pointed out as opportunities for future research and development. Concluding remarks are given at the end of the paper.

Ren-cheng Jin - One of the best experts on this subject based on the ideXlab platform.

  • A new fuzzy neural network with fast learning algorithm and guaranteed stability for Manufacturing Process Control
    Fuzzy Sets and Systems, 2002
    Co-Authors: Yunfei Zhou, Ren-cheng Jin
    Abstract:

    In this paper, a new fuzzy neural network (FNN) is presented for Manufacturing Process Control. It is different from the conventional FNN in its structure, learning algorithm and stability analysis method. Firstly, it utilizes the input and output layer to on-line fine-tune scaling factors. It can also use the hidden layers to realize the fuzzification, fuzzy inference, defuzzification and tune parameters such as membership functions, fuzzy Control rules dynamically. Secondly, a new combining learning algorithm (CL) which combines the gradient-based error back-propagation algorithm (EBP) with similar Newton (SN) algorithm is proposed in order to improve the convergence speed and release computational burden during the learning Process. Lastly, a convergence condition for determining the stability of FNN is established. Physical experiments for Manufacturing Process Control are implemented to evaluate the effectiveness of the proposed scheme.

Dragan Djurdjanovic - One of the best experts on this subject based on the ideXlab platform.

  • multistage Manufacturing Process Control robust to inaccurate knowledge about Process noise
    Cirp Annals-manufacturing Technology, 2017
    Co-Authors: Dragan Djurdjanovic, Yibo Jiao, Vidosav D Majstorovic
    Abstract:

    Abstract A method for robust Control of quality errors in a multistage Manufacturing Process (MMP) is formulated, guaranteeing the product quality even under the worst-case scenario of uncertainties in the knowledge of noise characteristics. Simulations based on the error flow models in automotive cylinder head machining and lithography overlay Processes show that the new robust Control method increasingly outperforms the traditional stochastic Control approach as uncertainties in the knowledge of Process noise characteristics increase. It is also shown that Controlling MMP quality, while ignoring inaccuracies in the noise model could make quality even worse than if no Control is used.

S. Joe Qin - One of the best experts on this subject based on the ideXlab platform.

  • Semiconductor Manufacturing Process Control and monitoring: A fab-wide framework
    Journal of Process Control, 2006
    Co-Authors: S. Joe Qin, Gregory Cherry, Richard Good, Jin Wang, Christopher A. Harrison
    Abstract:

    The semiconductor industry has started the technology transition from 200 mm to 300 mm wafers to improve Manufacturing efficiency and reduce Manufacturing cost. These technological changes present a unique opportunity to optimally design the Process Control systems for the next generation fabs. In this paper we first propose a hierarchical fab-wide Control framework with the integration of 300 mm equipment and metrology tools and highly automated material handling system. Relevant existing run-to-run technology is reviewed and analyzed in the fab-wide Control context. Process and metrology data monitoring are discussed with an example. Missing components are pointed out as opportunities for future research and development. Concluding remarks are given at the end of the paper.