SPC in service industry: case in teaching and learning process variability monitoring
Statistical Process Control (SPC) technique have long been developed and implemented for quality improvements in manufacturing process. However, it is not so developed in service industry and particularly in teaching and learning process. On the other hand, it is easier to monitor manufacturing...
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my.uthm.eprints.70162022-05-24T01:27:39Z http://eprints.uthm.edu.my/7016/ SPC in service industry: case in teaching and learning process variability monitoring Zolkepley, Z. Djauhari, M. A. Salleh, R. M. LB2331.7-2335.8 Teaching personnel Statistical Process Control (SPC) technique have long been developed and implemented for quality improvements in manufacturing process. However, it is not so developed in service industry and particularly in teaching and learning process. On the other hand, it is easier to monitor manufacturing industrial process than monitoring teaching and learning process. In the former, the sub-group size is small and constant while in the latter, it is large and non�constant. In this paper we focus on analyzing the disparity of teaching and learning process variability among classes in a Sekolah Menengah Kebangsaan using the improved generalized variance chart. For that purpose, the appropriate control limits will be developed such that it can be used for general sampling design. The result will be used to monitor the variability of teaching and learning process. A diagnostic tool will also be delivered to understand why, if any, a class is out-of-control. 2018 Conference or Workshop Item PeerReviewed text en http://eprints.uthm.edu.my/7016/1/P9918_94f616be4da36eb005c3daf2317cf94f.pdf Zolkepley, Z. and Djauhari, M. A. and Salleh, R. M. (2018) SPC in service industry: case in teaching and learning process variability monitoring. In: The Twenty Fifth National Symposium on Mathematical SciencesAt: Malaysia, 27-29 August 2017, Pahang. https://doi.org/10.1063/1.5041700 |
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LB2331.7-2335.8 Teaching personnel Zolkepley, Z. Djauhari, M. A. Salleh, R. M. SPC in service industry: case in teaching and learning process variability monitoring |
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Statistical Process Control (SPC) technique have long been developed and implemented for quality
improvements in manufacturing process. However, it is not so developed in service industry and particularly in teaching
and learning process. On the other hand, it is easier to monitor manufacturing industrial process than monitoring teaching
and learning process. In the former, the sub-group size is small and constant while in the latter, it is large and non�constant. In this paper we focus on analyzing the disparity of teaching and learning process variability among classes in a
Sekolah Menengah Kebangsaan using the improved generalized variance chart. For that purpose, the appropriate control
limits will be developed such that it can be used for general sampling design. The result will be used to monitor the
variability of teaching and learning process. A diagnostic tool will also be delivered to understand why, if any, a class is
out-of-control. |
format |
Conference or Workshop Item |
author |
Zolkepley, Z. Djauhari, M. A. Salleh, R. M. |
author_facet |
Zolkepley, Z. Djauhari, M. A. Salleh, R. M. |
author_sort |
Zolkepley, Z. |
title |
SPC in service industry: case in teaching and learning process variability monitoring |
title_short |
SPC in service industry: case in teaching and learning process variability monitoring |
title_full |
SPC in service industry: case in teaching and learning process variability monitoring |
title_fullStr |
SPC in service industry: case in teaching and learning process variability monitoring |
title_full_unstemmed |
SPC in service industry: case in teaching and learning process variability monitoring |
title_sort |
spc in service industry: case in teaching and learning process variability monitoring |
publishDate |
2018 |
url |
http://eprints.uthm.edu.my/7016/1/P9918_94f616be4da36eb005c3daf2317cf94f.pdf http://eprints.uthm.edu.my/7016/ https://doi.org/10.1063/1.5041700 |
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1738581564998025216 |
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13.160551 |