This is an empirical study on the application of SPC techniques for monitoring and detecting variation in the quality of locally produced tobacco in Nigeria. The result provides base evidence for intervention in the quality behavior of the heavily automated tobacco production process in which slight undetected deviation can result in significant wastes. An observational study was carried out within the primary manufacturing department of the tobacco company. The study analysis was conducted using descriptive statistics, goodness of fit test and SPC charts.. These charts were constructed and examined for significant variation in expected output quality as well as the capability of the process. The goodness of fit test and SPC identified CTQs that were approximately normally distributed and out of process control across periods of observations. These deviations were not evident with the summary data or its presentation on the histogram. Subsequently, the out of control process charts were transformed to in-control charts by repetitive elimination of out-of-control instances. At this state, it was observed that the process was only capable of meeting specification for the dust level for all capability measures. These results illustrate a proof of SPC for process monitoring and product quality improvement.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 9, Issue 4) |
| DOI | 10.11648/j.ajtas.20200904.16 |
| Page(s) | 127-135 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2020. Published by Science Publishing Group |
Critical-to-Quality, Goodness of Fit, Process Capability, Process Improvement
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APA Style
Adepeju Opaleye, Oladunni Okunade, Taiwo Adedeji, Victor Oladokun. (2020). Quality Characterisation and Capability Assessment of a Tobacco Company. American Journal of Theoretical and Applied Statistics, 9(4), 127-135. https://doi.org/10.11648/j.ajtas.20200904.16
ACS Style
Adepeju Opaleye; Oladunni Okunade; Taiwo Adedeji; Victor Oladokun. Quality Characterisation and Capability Assessment of a Tobacco Company. Am. J. Theor. Appl. Stat. 2020, 9(4), 127-135. doi: 10.11648/j.ajtas.20200904.16
AMA Style
Adepeju Opaleye, Oladunni Okunade, Taiwo Adedeji, Victor Oladokun. Quality Characterisation and Capability Assessment of a Tobacco Company. Am J Theor Appl Stat. 2020;9(4):127-135. doi: 10.11648/j.ajtas.20200904.16
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Download@article{10.11648/j.ajtas.20200904.16,
author = {Adepeju Opaleye and Oladunni Okunade and Taiwo Adedeji and Victor Oladokun},
title = {Quality Characterisation and Capability Assessment of a Tobacco Company},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {9},
number = {4},
pages = {127-135},
doi = {10.11648/j.ajtas.20200904.16},
url = {https://doi.org/10.11648/j.ajtas.20200904.16},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20200904.16},
abstract = {This is an empirical study on the application of SPC techniques for monitoring and detecting variation in the quality of locally produced tobacco in Nigeria. The result provides base evidence for intervention in the quality behavior of the heavily automated tobacco production process in which slight undetected deviation can result in significant wastes. An observational study was carried out within the primary manufacturing department of the tobacco company. The study analysis was conducted using descriptive statistics, goodness of fit test and SPC charts.. These charts were constructed and examined for significant variation in expected output quality as well as the capability of the process. The goodness of fit test and SPC identified CTQs that were approximately normally distributed and out of process control across periods of observations. These deviations were not evident with the summary data or its presentation on the histogram. Subsequently, the out of control process charts were transformed to in-control charts by repetitive elimination of out-of-control instances. At this state, it was observed that the process was only capable of meeting specification for the dust level for all capability measures. These results illustrate a proof of SPC for process monitoring and product quality improvement.},
year = {2020}
}
TY - JOUR T1 - Quality Characterisation and Capability Assessment of a Tobacco Company AU - Adepeju Opaleye AU - Oladunni Okunade AU - Taiwo Adedeji AU - Victor Oladokun Y1 - 2020/06/17 PY - 2020 N1 - https://doi.org/10.11648/j.ajtas.20200904.16 DO - 10.11648/j.ajtas.20200904.16 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 127 EP - 135 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20200904.16 AB - This is an empirical study on the application of SPC techniques for monitoring and detecting variation in the quality of locally produced tobacco in Nigeria. The result provides base evidence for intervention in the quality behavior of the heavily automated tobacco production process in which slight undetected deviation can result in significant wastes. An observational study was carried out within the primary manufacturing department of the tobacco company. The study analysis was conducted using descriptive statistics, goodness of fit test and SPC charts.. These charts were constructed and examined for significant variation in expected output quality as well as the capability of the process. The goodness of fit test and SPC identified CTQs that were approximately normally distributed and out of process control across periods of observations. These deviations were not evident with the summary data or its presentation on the histogram. Subsequently, the out of control process charts were transformed to in-control charts by repetitive elimination of out-of-control instances. At this state, it was observed that the process was only capable of meeting specification for the dust level for all capability measures. These results illustrate a proof of SPC for process monitoring and product quality improvement. VL - 9 IS - 4 ER -
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