Adaptive process control for achieving consistent particles' states in atmospheric plasma spray process

The coatings produced by an atmospheric plasma spray process (APSP) must be of uniform quality. However, the complexity of the process and the random introduction of noise variables such as fluctuations in the powder injection rate and the arc voltage make it difficult to control the coating quality...

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Published in:SN applied sciences 2021-03, Vol.3 (3), p.294, Article 294
Main Authors: Guduri, B., Cybulsky, M., Pickrell, G. R., Batra, R. C.
Format: Article
Language:English
Subjects:
6. Interdisciplinary (general)
Adaptive control
Applied and Technical Physics
Chemistry/Food Science
Controllers
Design of experiments
Earth Sciences
Engineering
Environment
Finite volume method
Gas flow
Gases
Heat
Materials Science
Mathematical models
Plasma
Process control
Process controls
Production costs
Random variables
Research Article
Substrates
Velocity
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cited_by cdi_FETCH-LOGICAL-c363t-3b3ff649ff24f456aab6eb6c8d49620e45691da53fa20d74a921be98f87797023
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creator Guduri, B.
Cybulsky, M.
Pickrell, G. R.
Batra, R. C.
description The coatings produced by an atmospheric plasma spray process (APSP) must be of uniform quality. However, the complexity of the process and the random introduction of noise variables such as fluctuations in the powder injection rate and the arc voltage make it difficult to control the coating quality that has been shown to depend upon mean values of powder particles’ temperature and speed, collectively called mean particles’ states (MPSs), just before they impact the substrate. Here, we use a science-based methodology to develop a stable and adaptive controller for achieving consistent MPSs and thereby decrease the manufacturing cost. We first identify inputs into the APSP that significantly affect the MPSs and then formulate a relationship between these two quantities. When the MPSs deviate from their desired values, the adaptive controller is shown to successfully adjust the input parameters to correct them. The performance of the controller is tested via numerical experiments using the software, LAVA-P, that has been shown to well simulate the APSP.
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subjects 6. Interdisciplinary (general)
Adaptive control
Applied and Technical Physics
Chemistry/Food Science
Controllers
Design of experiments
Earth Sciences
Engineering
Environment
Finite volume method
Gas flow
Gases
Heat
Materials Science
Mathematical models
Plasma
Process control
Process controls
Production costs
Random variables
Research Article
Substrates
Velocity
title Adaptive process control for achieving consistent particles' states in atmospheric plasma spray process
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