ZUPANČIČ, Rok ;SLUGA, Alojzij . Economic Design of Control Charts. Strojniški vestnik - Journal of Mechanical Engineering, [S.l.], v. 54, n.12, p. 855-865, august 2017. ISSN 0039-2480. Available at: <https://www.sv-jme.eu/sl/article/economic-design-of-control-charts/>. Date accessed: 20 dec. 2024. doi:http://dx.doi.org/.
Zupančič, R., & Sluga, A. (2008). Economic Design of Control Charts. Strojniški vestnik - Journal of Mechanical Engineering, 54(12), 855-865. doi:http://dx.doi.org/
@article{.,
author = {Rok Zupančič and Alojzij Sluga},
title = {Economic Design of Control Charts},
journal = {Strojniški vestnik - Journal of Mechanical Engineering},
volume = {54},
number = {12},
year = {2008},
keywords = {control charts; quality control; economic design; statistical process control; },
abstract = {Control charts are widely used in industry for monitoring and controlling manufacturing processes. They should be designed economically in order to achieve minimum quality control costs. In this paper, an economic design of Shewhart control charts for process mean is proposed that takes into account various parameters. Standards for sample size within statistical process control do not exist due to high diversity of modern production. In the proposed economic model process-mean shift is assumed as random variable. This is a better approximation of the real world, than the models that assume process-mean shift as a constant value. Probability density function is used for description of processmean shift. The optimum sample size is computed on base of loss function, regarding to constraints of particular production process. The comparison of optimum sample sizes assuming process-mean shift as a constant value versus random variable is presented.},
issn = {0039-2480}, pages = {855-865}, doi = {},
url = {https://www.sv-jme.eu/sl/article/economic-design-of-control-charts/}
}
Zupančič, R.,Sluga, A. 2008 August 54. Economic Design of Control Charts. Strojniški vestnik - Journal of Mechanical Engineering. [Online] 54:12
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Zupančič, Rok, & Alojzij Sluga. "Economic Design of Control Charts." Strojniški vestnik - Journal of Mechanical Engineering [Online], 54.12 (2008): 855-865. Web. 20 Dec. 2024
TY - JOUR AU - Zupančič, Rok AU - Sluga, Alojzij PY - 2008 TI - Economic Design of Control Charts JF - Strojniški vestnik - Journal of Mechanical Engineering DO - KW - control charts; quality control; economic design; statistical process control; N2 - Control charts are widely used in industry for monitoring and controlling manufacturing processes. They should be designed economically in order to achieve minimum quality control costs. In this paper, an economic design of Shewhart control charts for process mean is proposed that takes into account various parameters. Standards for sample size within statistical process control do not exist due to high diversity of modern production. In the proposed economic model process-mean shift is assumed as random variable. This is a better approximation of the real world, than the models that assume process-mean shift as a constant value. Probability density function is used for description of processmean shift. The optimum sample size is computed on base of loss function, regarding to constraints of particular production process. The comparison of optimum sample sizes assuming process-mean shift as a constant value versus random variable is presented. UR - https://www.sv-jme.eu/sl/article/economic-design-of-control-charts/
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author = {Zupančič, R., Sluga, A.},
title = {Economic Design of Control Charts},
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volume = {54},
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year = {2008},
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TY - JOUR AU - Zupančič, Rok AU - Sluga, Alojzij PY - 2017/08/21 TI - Economic Design of Control Charts JF - Strojniški vestnik - Journal of Mechanical Engineering; Vol 54, No 12 (2008): Strojniški vestnik - Journal of Mechanical Engineering DO - KW - control charts, quality control, economic design, statistical process control, N2 - Control charts are widely used in industry for monitoring and controlling manufacturing processes. They should be designed economically in order to achieve minimum quality control costs. In this paper, an economic design of Shewhart control charts for process mean is proposed that takes into account various parameters. Standards for sample size within statistical process control do not exist due to high diversity of modern production. In the proposed economic model process-mean shift is assumed as random variable. This is a better approximation of the real world, than the models that assume process-mean shift as a constant value. Probability density function is used for description of processmean shift. The optimum sample size is computed on base of loss function, regarding to constraints of particular production process. The comparison of optimum sample sizes assuming process-mean shift as a constant value versus random variable is presented. UR - https://www.sv-jme.eu/sl/article/economic-design-of-control-charts/
Zupančič, Rok, AND Sluga, Alojzij. "Economic Design of Control Charts" Strojniški vestnik - Journal of Mechanical Engineering [Online], Volume 54 Number 12 (21 August 2017)
Strojniški vestnik - Journal of Mechanical Engineering 54(2008)12, 855-865
© The Authors, CC-BY 4.0 Int. Change in copyright policy from 2022, Jan 1st.
Control charts are widely used in industry for monitoring and controlling manufacturing processes. They should be designed economically in order to achieve minimum quality control costs. In this paper, an economic design of Shewhart control charts for process mean is proposed that takes into account various parameters. Standards for sample size within statistical process control do not exist due to high diversity of modern production. In the proposed economic model process-mean shift is assumed as random variable. This is a better approximation of the real world, than the models that assume process-mean shift as a constant value. Probability density function is used for description of processmean shift. The optimum sample size is computed on base of loss function, regarding to constraints of particular production process. The comparison of optimum sample sizes assuming process-mean shift as a constant value versus random variable is presented.