An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels

Predictive process control (PPC) is the use of predictive, physical models as the basis for process control [1]. In contrast, conventional control algorithms utilize statistical models that are derived from repetitive process trials. PPC employs in-process monitoring and control of manufacturing pro...

Full description

Bibliographic Details
Main Author: Ely, George Ray
Format: Others
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/2152/ETD-UT-2010-05-1204
id ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2010-05-1204
record_format oai_dc
spelling ndltd-UTEXAS-oai-repositories.lib.utexas.edu-2152-ETD-UT-2010-05-12042015-09-20T16:55:21ZAn analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodelsEly, George RayMetamodelingWeldingPredictive process controlResidual stressPredictive process control (PPC) is the use of predictive, physical models as the basis for process control [1]. In contrast, conventional control algorithms utilize statistical models that are derived from repetitive process trials. PPC employs in-process monitoring and control of manufacturing processes. PPC algorithms are very promising approaches for welding of small lots or customized products with rapid changes in materials, geometry, or processing conditions. They may also be valuable for welding high value products for which repeated trials and waste are not acceptable. In this research, small-lot braze-welding of UNS C22000 commercial bronze with gas metal arc welding (GMAW) technology is selected as a representative application of PPC. Thermal models of the welding process are constructed to predict the effects of changes in process parameters on the response of temperature measurements. Because accurate thermal models are too computationally expensive for direct use in a control algorithm, metamodels are constructed to drastically reduce computational expense while retaining a high degree of accuracy. Then, the feasibility of PPC of welding applications is analyzed with regard to uncertainties and time delays in an existing welding station and thermal metamodels of the welding process. Lastly, a qualitative residual stress model is developed to nondestructively assess weld quality in end-user parts.text2010-10-27T21:32:26Z2010-10-27T21:32:38Z2010-10-27T21:32:26Z2010-10-27T21:32:38Z2010-052010-10-27May 20102010-10-27T21:32:39Zthesisapplication/pdfhttp://hdl.handle.net/2152/ETD-UT-2010-05-1204eng
collection NDLTD
language English
format Others
sources NDLTD
topic Metamodeling
Welding
Predictive process control
Residual stress
spellingShingle Metamodeling
Welding
Predictive process control
Residual stress
Ely, George Ray
An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
description Predictive process control (PPC) is the use of predictive, physical models as the basis for process control [1]. In contrast, conventional control algorithms utilize statistical models that are derived from repetitive process trials. PPC employs in-process monitoring and control of manufacturing processes. PPC algorithms are very promising approaches for welding of small lots or customized products with rapid changes in materials, geometry, or processing conditions. They may also be valuable for welding high value products for which repeated trials and waste are not acceptable. In this research, small-lot braze-welding of UNS C22000 commercial bronze with gas metal arc welding (GMAW) technology is selected as a representative application of PPC. Thermal models of the welding process are constructed to predict the effects of changes in process parameters on the response of temperature measurements. Because accurate thermal models are too computationally expensive for direct use in a control algorithm, metamodels are constructed to drastically reduce computational expense while retaining a high degree of accuracy. Then, the feasibility of PPC of welding applications is analyzed with regard to uncertainties and time delays in an existing welding station and thermal metamodels of the welding process. Lastly, a qualitative residual stress model is developed to nondestructively assess weld quality in end-user parts. === text
author Ely, George Ray
author_facet Ely, George Ray
author_sort Ely, George Ray
title An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
title_short An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
title_full An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
title_fullStr An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
title_full_unstemmed An analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
title_sort analysis of the feasibility of predictive process control of welding applications using infrared pyrometers and thermal metamodels
publishDate 2010
url http://hdl.handle.net/2152/ETD-UT-2010-05-1204
work_keys_str_mv AT elygeorgeray ananalysisofthefeasibilityofpredictiveprocesscontrolofweldingapplicationsusinginfraredpyrometersandthermalmetamodels
AT elygeorgeray analysisofthefeasibilityofpredictiveprocesscontrolofweldingapplicationsusinginfraredpyrometersandthermalmetamodels
_version_ 1716820995096969216