{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/76385"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/76385","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"The development and analysis of a multi-attribute quality control cost model","abstract":"A multi-attribute quality control cost model is presented in this thesis. The mathematical model expresses the expected total cost of the quality system per lot as a function of the decision variables, nᵢ and cᵢ, i = 1, 2, . . . , m, where nᵢ is the sample size for the ith attribute. cᵢ is the acceptance number for the ith attribute. m is the number of attributes. The expected total cost is denoted by C<sub>T</sub> and can be expressed as C<sub>T</sub> = E (cost of sampling inspection). E (cost of accepting the lot). E (cost of rejecting and scrapping the lot). E (cost of rejecting and screening the lot). An optimal sampling plan can be obtained by determining the nᵢ and cᵢ, i = 1, 2, …, m, that minimizes C<sub>T</sub>. The nᵢ and cᵢ are found by means of a search technique that has proved useful in attribute quality control systems. In addition to the model development and optimization, a sensitivity analysis is performed on the use of the gallllla distribution as an estimate of the true process distribution for single and triple attribute systems. Also, a model sensitivity analysis is performed on errors in the estimation of the Cₐᵢ, the cost of accepting a defective unit.","abstract_html":"A multi-attribute quality control cost model is presented in this thesis. The mathematical model expresses the expected total cost of the quality system per lot as a function of the decision variables, nᵢ and cᵢ, i = 1, 2, . . . , m, where nᵢ is the sample size for the ith attribute. cᵢ is the acceptance number for the ith attribute. m is the number of attributes. The expected total cost is denoted by C&lt;sub&gt;T&lt;/sub&gt; and can be expressed as C&lt;sub&gt;T&lt;/sub&gt; = E (cost of sampling inspection). E (cost of accepting the lot). E (cost of rejecting and scrapping the lot). E (cost of rejecting and screening the lot). An optimal sampling plan can be obtained by determining the nᵢ and cᵢ, i = 1, 2, …, m, that minimizes C&lt;sub&gt;T&lt;/sub&gt;. The nᵢ and cᵢ are found by means of a search technique that has proved useful in attribute quality control systems. In addition to the model development and optimization, a sensitivity analysis is performed on the use of the gallllla distribution as an estimate of the true process distribution for single and triple attribute systems. Also, a model sensitivity analysis is performed on errors in the estimation of the Cₐᵢ, the cost of accepting a defective unit.","abstract_has_math":false,"creators":["McCaslin, James Albert, 1948-"],"institution":"Virginia Polytechnic Institute and State University","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Industrial Engineering and Operations Research","degree_department":"Industrial Engineering and Operations Research","school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1973,"date_issued":"1973","date_published":"1973","updated_at":"2026-07-22T22:19:15Z","subjects":[],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10919/76385","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.department","label":"Department","values":["Industrial Engineering and Operations Research"]},{"key":"dc:creator","label":"Author","values":["McCaslin, James Albert, 1948-"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2017-03-10T21:43:10Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2017-03-10T21:43:10Z"]},{"key":"dc:date.issued","label":"Date","values":["1973"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Polytechnic Institute and State University"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Industrial Engineering and Operations Research"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/76385"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A multi-attribute quality control cost model is presented in this thesis. The mathematical model expresses the expected total cost of the quality system per lot as a function of the decision variables, nᵢ and cᵢ, i = 1, 2, . . . , m, where nᵢ is the sample size for the ith attribute. cᵢ is the acceptance number for the ith attribute. m is the number of attributes. The expected total cost is denoted by C<sub>T</sub> and can be expressed as C<sub>T</sub> = E (cost of sampling inspection). E (cost of accepting the lot). E (cost of rejecting and scrapping the lot). E (cost of rejecting and screening the lot). An optimal sampling plan can be obtained by determining the nᵢ and cᵢ, i = 1, 2, …, m, that minimizes C<sub>T</sub>. The nᵢ and cᵢ are found by means of a search technique that has proved useful in attribute quality control systems. In addition to the model development and optimization, a sensitivity analysis is performed on the use of the gallllla distribution as an estimate of the true process distribution for single and triple attribute systems. Also, a model sensitivity analysis is performed on errors in the estimation of the Cₐᵢ, the cost of accepting a defective unit."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Master of Science"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The development and analysis of a multi-attribute quality control cost model"]}]}],"canonical_facts":{"dc:contributor.department":["Industrial Engineering and Operations Research"],"dc:creator":["McCaslin, James Albert, 1948-"],"dc:date.accessioned":["2017-03-10T21:43:10Z"],"dc:date.available":["2017-03-10T21:43:10Z"],"dc:date.issued":["1973"],"dc:description.abstract":["A multi-attribute quality control cost model is presented in this thesis. The mathematical model expresses the expected total cost of the quality system per lot as a function of the decision variables, nᵢ and cᵢ, i = 1, 2, . . . , m, where nᵢ is the sample size for the ith attribute. cᵢ is the acceptance number for the ith attribute. m is the number of attributes. The expected total cost is denoted by C<sub>T</sub> and can be expressed as C<sub>T</sub> = E (cost of sampling inspection). E (cost of accepting the lot). E (cost of rejecting and scrapping the lot). E (cost of rejecting and screening the lot). An optimal sampling plan can be obtained by determining the nᵢ and cᵢ, i = 1, 2, …, m, that minimizes C<sub>T</sub>. The nᵢ and cᵢ are found by means of a search technique that has proved useful in attribute quality control systems. In addition to the model development and optimization, a sensitivity analysis is performed on the use of the gallllla distribution as an estimate of the true process distribution for single and triple attribute systems. Also, a model sensitivity analysis is performed on errors in the estimation of the Cₐᵢ, the cost of accepting a defective unit."],"dc:description.degree":["Master of Science"],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10919/76385"],"dc:language.iso":["en"],"dc:publisher":["Virginia Polytechnic Institute and State University"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["The development and analysis of a multi-attribute quality control cost model"],"dc:type":["Thesis"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Industrial Engineering and Operations Research"],"thesis:degree_level":["masters"],"thesis:degree_name":["Master of Science"],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:15Z"}