A Simple Approach for Monitoring Business Service Time Variation
Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normal...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/238719 |
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| author | Su-Fen Yang Barry C. Arnold |
| author_facet | Su-Fen Yang Barry C. Arnold |
| author_sort | Su-Fen Yang |
| collection | DOAJ |
| description | Control charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA variance chart (EWMA-AV chart) and an asymmetric EWMA mean chart (EWMA-AM chart) based on two simple statistics to monitor process variance and mean shifts simultaneously. Further, we explore the sampling properties of the new monitoring statistics and calculate the average run lengths when using both the EWMA-AV chart and the EWMA-AM chart. The performance of the EWMA-AV and EWMA-AM charts and that of some existing variance and mean charts are compared. A numerical example involving nonnormal service times from the service system of a bank branch in Taiwan is used to illustrate the applications of the EWMA-AV and EWMA-AM charts and to compare them with the existing variance (or standard deviation) and mean charts. The proposed EWMA-AV chart and EWMA-AM charts show superior detection performance compared to the existing variance and mean charts. The EWMA-AV chart and EWMA-AM chart are thus recommended. |
| format | Article |
| id | doaj-art-a32c0842b12c418a84627c3c30eab5b9 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-a32c0842b12c418a84627c3c30eab5b92025-02-03T06:06:26ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/238719238719A Simple Approach for Monitoring Business Service Time VariationSu-Fen Yang0Barry C. Arnold1Department of Statistics, National Chengchi University, Taipei 116, TaiwanDepartment of Statistics, University of California, Riverside, CA 92521, USAControl charts are effective tools for signal detection in both manufacturing processes and service processes. Much of the data in service industries comes from processes having nonnormal or unknown distributions. The commonly used Shewhart variable control charts, which depend heavily on the normality assumption, are not appropriately used here. In this paper, we propose a new asymmetric EWMA variance chart (EWMA-AV chart) and an asymmetric EWMA mean chart (EWMA-AM chart) based on two simple statistics to monitor process variance and mean shifts simultaneously. Further, we explore the sampling properties of the new monitoring statistics and calculate the average run lengths when using both the EWMA-AV chart and the EWMA-AM chart. The performance of the EWMA-AV and EWMA-AM charts and that of some existing variance and mean charts are compared. A numerical example involving nonnormal service times from the service system of a bank branch in Taiwan is used to illustrate the applications of the EWMA-AV and EWMA-AM charts and to compare them with the existing variance (or standard deviation) and mean charts. The proposed EWMA-AV chart and EWMA-AM charts show superior detection performance compared to the existing variance and mean charts. The EWMA-AV chart and EWMA-AM chart are thus recommended.http://dx.doi.org/10.1155/2014/238719 |
| spellingShingle | Su-Fen Yang Barry C. Arnold A Simple Approach for Monitoring Business Service Time Variation The Scientific World Journal |
| title | A Simple Approach for Monitoring Business Service Time Variation |
| title_full | A Simple Approach for Monitoring Business Service Time Variation |
| title_fullStr | A Simple Approach for Monitoring Business Service Time Variation |
| title_full_unstemmed | A Simple Approach for Monitoring Business Service Time Variation |
| title_short | A Simple Approach for Monitoring Business Service Time Variation |
| title_sort | simple approach for monitoring business service time variation |
| url | http://dx.doi.org/10.1155/2014/238719 |
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