A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process
Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocatin...
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| Autor*in: |
Khodaygan, S. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer-Verlag London Ltd. 2017 |
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| Übergeordnetes Werk: |
Enthalten in: The international journal of advanced manufacturing technology - Springer London, 1985, 94(2017), 9-12 vom: 27. Sept., Seite 3963-3978 |
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| Übergeordnetes Werk: |
volume:94 ; year:2017 ; number:9-12 ; day:27 ; month:09 ; pages:3963-3978 |
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| DOI / URN: |
10.1007/s00170-017-1054-y |
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OLC2026113440 |
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| 520 | |a Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. | ||
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| 650 | 4 | |a Error reduction | |
| 650 | 4 | |a Uncertainty analysis | |
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| 650 | 4 | |a Optimal design | |
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10.1007/s00170-017-1054-y doi (DE-627)OLC2026113440 (DE-He213)s00170-017-1054-y-p DE-627 ger DE-627 rakwb eng 670 VZ Khodaygan, S. verfasserin aut A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd. 2017 Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. Geometric process capability Error reduction Uncertainty analysis Locating error Optimal design Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 94(2017), 9-12 vom: 27. Sept., Seite 3963-3978 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:94 year:2017 number:9-12 day:27 month:09 pages:3963-3978 https://doi.org/10.1007/s00170-017-1054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 94 2017 9-12 27 09 3963-3978 |
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10.1007/s00170-017-1054-y doi (DE-627)OLC2026113440 (DE-He213)s00170-017-1054-y-p DE-627 ger DE-627 rakwb eng 670 VZ Khodaygan, S. verfasserin aut A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd. 2017 Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. Geometric process capability Error reduction Uncertainty analysis Locating error Optimal design Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 94(2017), 9-12 vom: 27. Sept., Seite 3963-3978 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:94 year:2017 number:9-12 day:27 month:09 pages:3963-3978 https://doi.org/10.1007/s00170-017-1054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 94 2017 9-12 27 09 3963-3978 |
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10.1007/s00170-017-1054-y doi (DE-627)OLC2026113440 (DE-He213)s00170-017-1054-y-p DE-627 ger DE-627 rakwb eng 670 VZ Khodaygan, S. verfasserin aut A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd. 2017 Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. Geometric process capability Error reduction Uncertainty analysis Locating error Optimal design Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 94(2017), 9-12 vom: 27. Sept., Seite 3963-3978 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:94 year:2017 number:9-12 day:27 month:09 pages:3963-3978 https://doi.org/10.1007/s00170-017-1054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 94 2017 9-12 27 09 3963-3978 |
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10.1007/s00170-017-1054-y doi (DE-627)OLC2026113440 (DE-He213)s00170-017-1054-y-p DE-627 ger DE-627 rakwb eng 670 VZ Khodaygan, S. verfasserin aut A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd. 2017 Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. Geometric process capability Error reduction Uncertainty analysis Locating error Optimal design Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 94(2017), 9-12 vom: 27. Sept., Seite 3963-3978 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:94 year:2017 number:9-12 day:27 month:09 pages:3963-3978 https://doi.org/10.1007/s00170-017-1054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 94 2017 9-12 27 09 3963-3978 |
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10.1007/s00170-017-1054-y doi (DE-627)OLC2026113440 (DE-He213)s00170-017-1054-y-p DE-627 ger DE-627 rakwb eng 670 VZ Khodaygan, S. verfasserin aut A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag London Ltd. 2017 Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. Geometric process capability Error reduction Uncertainty analysis Locating error Optimal design Enthalten in The international journal of advanced manufacturing technology Springer London, 1985 94(2017), 9-12 vom: 27. Sept., Seite 3963-3978 (DE-627)129185299 (DE-600)52651-4 (DE-576)014456192 0268-3768 nnns volume:94 year:2017 number:9-12 day:27 month:09 pages:3963-3978 https://doi.org/10.1007/s00170-017-1054-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_70 GBV_ILN_2018 GBV_ILN_2333 AR 94 2017 9-12 27 09 3963-3978 |
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A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process |
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Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. © Springer-Verlag London Ltd. 2017 |
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Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. © Springer-Verlag London Ltd. 2017 |
| abstract_unstemmed |
Abstract Imprecise productions with low quality are produced by the incapable manufacturing processes. Prediction of the process capability in the design stage plays a key role to improve the product quality. In this paper, a new method is proposed to optimally reduce the locating error by allocating the minimum adjustments of locators. To quantify the precision of the manufacturing process, a proper tool that is called the geometric capability ratio (GCR) of the manufacturing process is introduced. First, based on a part fixture model, the relationship between the locating error and its sources is developed. Then, using the proposed geometric capability ratio, the manufacturing process capability is evaluated to achieve a specific desired level. If the process is incapable, the locating error should be essentially reduced. To improve the precision and accuracy of the final product, the error reduction procedure is developed as an optimal design problem. The formulated optimization problem can be efficiently solved by an evolutionary algorithm for constrained global optimization such as genetic algorithm method. The method is developed for the uncertainty analysis based on three approaches: the direct method, the worst case, and the statistical approaches. The proposed method is illustrated using a case study, and the computational results are compared to the obtained results from Monte Carlo and CAD simulations. © Springer-Verlag London Ltd. 2017 |
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A method for optimal reduction of locating error with the minimum adjustments of locators based on the geometric capability ratio of process |
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