Quality capability self-diagnosis : a multicriteria evaluation approach Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/00000210n

Descriptions

Attribute NameValues
Creator
Abstract or Summary
  • Quality Capability Self-diagnosis is a convenient and economical way to assess the performance of an operating quality system, as well as a basis for initiating necessary corrective actions essential to quality improvement and preparation for certification. This paper describes the research leading to the development of a cost-effective and systematic methodology for performing quality capability self-diagnosis. ISO 9000 series standards and the methods used to implement multicriteria system evaluation are employed to provide a sound basis for the development of this quality capability self-diagnosis scheme (QCSDS). The QCSDS has been developed to assist manufacturers in the conduct of quality assurance audits using internal personnel. The methodological structure of QCSDS is presented in two major parts: a regular model and a refined model. The regular model includes: (1) development of quality system auditing criteria, (2) selection of a suitable checklist developed from ISO 9000 series requirements, (3) development of importance weights for applicable criteria, (4) performance measurement, (5) quality system rating, (6) analysis of quality auditing results, and (7) suggestions for improvement. The refined model is developed to strengthen capability of the model and its reliability for confirming the effectiveness of an operating quality system using quality cost analysis, utility theory and regression analysis. A decision support system (QCSDDSS) based on the Quattro Pro spreadsheet is incorporated to facilitate the application of QCSDS. The QCSDDSS development is based on the regular model using ISO 9002 to provide both tabular and graphical displays for performance demonstration and improvement analysis.
Resource Type
Date Available
Date Copyright
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome) using Capture Perfect 3.0 on a Canon DR-9050C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces
Additional Information
  • description.provenance : Submitted by Kirsten Clark (kcscannerosu@gmail.com) on 2012-12-05T22:57:34Z No. of bitstreams: 1 HuangKueiJung1994.pdf: 14185651 bytes, checksum: e05281941ed6b74b5c5b1d92e04633b9 (MD5)
  • description.provenance : Made available in DSpace on 2012-12-06T18:27:38Z (GMT). No. of bitstreams: 1 HuangKueiJung1994.pdf: 14185651 bytes, checksum: e05281941ed6b74b5c5b1d92e04633b9 (MD5) Previous issue date: 1994-01-24
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2012-12-06T18:27:37Z (GMT) No. of bitstreams: 1 HuangKueiJung1994.pdf: 14185651 bytes, checksum: e05281941ed6b74b5c5b1d92e04633b9 (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2012-12-05T23:01:03Z (GMT) No. of bitstreams: 1 HuangKueiJung1994.pdf: 14185651 bytes, checksum: e05281941ed6b74b5c5b1d92e04633b9 (MD5)

Relationships

In Administrative Set:
Last modified: 08/04/2017

Downloadable Content

Download PDF
Citations:

EndNote | Zotero | Mendeley

Items