Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Multi-disciplinary Studies | en_US |
| dc.creator | Yen, Kin | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/1579 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Performance analysis of quality control charts in monitoring precision manufacturing process | en_US |
| dcterms.abstract | This report presents and analyzes an approach for implementing statistical process control charts in monitoring precision manufacturing process. Average run length comparisons are made among the Shewhart x chart with supplementary runs rules, the cumulative sum (CUSUM) chart, and the exponentially weighted moving average (EWMA) chart. The results of these comparisons indicate that the EWMA and CUSUM control schemes are with better ARL properties for detecting small process mean shift than the Shewhart x chart with supplementary runs rules. Because of using all past information, the CUSUM and EWMA control schemes are more sensitive to detect small shifts in process mean. Both schemes have equivalent average run lengths up to a process mean shift of one standard error. However, the CUSUM and EWMA schemes do not detect large shifts in the mean as quickly as the Shewhart x chart. Although the runs rules increase the sensitivity of the Shewhart chart to small shifts in the mean, it also reduces the ARL at the target value u0, and thus result in more false alarms (Type I error). To illustrate the use of these three control schemes, a set of observations taken from a precision grinding process is collected. Due to the tight tolerance required from customer specification, the control charts are designed to give minimum ARL if a lo shift in the process mean occurs (upward or downwards). For convenience of data analysis and presentation, a SPC program is developed in Microsoft Excel. This program not only produces control charts but also calculates the average run length for different control schemes with in-control and out-of-control states. | en_US |
| dcterms.extent | vi, 178 leaves : ill. ; 30 cm | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 1998 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Manufacturing processes -- Quality control | en_US |
| dcterms.LCSH | Quality control -- Charts, diagrams, etc | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b14370402.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 4.31 MB | Adobe PDF | View/Open |
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