Use of neural network to model X-ray photoelectron spectroscopy data for diagnosis of plasma etch equipment

Kim, Byungwhan; Kim, Jeong; Choi, Seongjin

doi:10.1016/j.eswa.2009.03.004

Cited by 5 publications

(3 citation statements)

References 10 publications

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“…For fault diagnosis of the Tennessee-Eastman benchmark process, a hierarchical neural network based on fuzzy clustering method has been designed . Other nonlinear process monitoring methods related to principal curves and neural networks have also been developed recently. − …”

Section: State-of-the-art Of Data-based Process Monitoringmentioning

confidence: 99%

Review of Recent Research on Data-Based Process Monitoring

Song

Gao

2013

Ind. Eng. Chem. Res.

859

438

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Data-based process monitoring has become a key technology in process industries for safety, quality, and operation efficiency enhancement. This paper provides a timely update review on this topic. First, the natures of different industrial processes are revealed with their data characteristics analyzed. Second, detailed terminologies of the data-based process monitoring method are illustrated. Third, based on each of the main data characteristics that exhibits in the process, a corresponding problem is defined and illustrated, with review conducted with detailed discussions on connection and comparison of different monitoring methods. Finally, the relevant research perspectives and several promising issues are highlighted for future work.

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Section: State-of-the-art Of Data-based Process Monitoringmentioning

confidence: 99%

Review of Recent Research on Data-Based Process Monitoring

Song

Gao

2013

Ind. Eng. Chem. Res.

859

438

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“…To achieve equilibrium between the tracking error and the chattering, an ASMC based on the bipolar sigmoid function is proposed, 26,27 which can be derived from equation (6).…”

Section: Asmc Based On Bipolar Sigmoid Functionmentioning

confidence: 99%

“…ð27Þ where u 1 is the control law (6), u 2 is the internal controller (26), and > 0 is a small constant, as illustrated in Figure 6.…”

Section: Asmc Based On Hyperbolic Tangent Functionmentioning

confidence: 99%

Robust control of the A-axis with friction variation and parameters uncertainty in five-axis CNC machine tools

Zhao

Shi

2014

Proceedings of the Institution of Mechanical Engineers, Part C:

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A-axis is an essential assembly in the five-axis CNC machine tools, and its positioning precision directly affects the machining accuracy and surface quality of the parts. Considering the influence of parameters perturbation and uncertain cutting force on the control precision of the A-axis, a nonlinear dynamics model of the A-axis system is established, which reveals the relationships among the drive torque, the load torque, the motion direction and the system parameters. Then, two adaptive sliding mode controllers (ASMC) are designed. The first one is based on the bipolar sigmoid function, which can adjust the switching gain and the boundary layer thickness adaptively, then, equilibrium between the tracking error and the chattering can be achieved. The second one is a compound adaptive controller constituted by the traditional sliding mode controller (TSMC) and an internal controller that is based on the hyperbolic tangent function. When the state trajectory comes into the boundary layer, the TSMC will be replaced by the internal controller, thus, the adaptive controller can continuously switch between these two controllers, which can effectively eliminate the high-frequency chattering in the TSMC. Stability of these two controllers is guaranteed by the Lyapunov theory. Experimental results demonstrate the effectiveness and feasibility of the proposed ASMC, which can smooth the input chattering and reduce the tracking error by 16.62% and 21.44%, respectively.

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Wavelet-coupled backpropagation neural network as a chamber leak detector of plasma processing equipment

Kim

Kwon

2011

Expert Systems with Applications

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Use of neural network to model X-ray photoelectron spectroscopy data for diagnosis of plasma etch equipment

Cited by 5 publications

References 10 publications

Review of Recent Research on Data-Based Process Monitoring

Review of Recent Research on Data-Based Process Monitoring

Robust control of the A-axis with friction variation and parameters uncertainty in five-axis CNC machine tools

Wavelet-coupled backpropagation neural network as a chamber leak detector of plasma processing equipment

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