{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/54835"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/54835","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Process control: a dynamic programming approach","abstract":"In this thesis, a cost based process control model is formulated. A dynamic programming approach is used and along with the techniques of Bayesian decision theory, an optimal set of steady state control policies are shown to exist which are dependent upon prior beliefs about the condition of the process. It is the objective of this thesis to compare the results obtained from this approach to those of an X̅ control chart approach. The model proposed by Knappenberger and Grandage [20] is used as a basis for comparison. Numerical examples are used to illustrate each procedure. The results obtained illustrate that by using the operating policies specified by the dynamic approach, a savings of from 29% to 40% in the optimal cost per unit to operate the quality control procedure can be achieved rather than utilizing the policies of the X̅ control chart model.","abstract_html":"In this thesis, a cost based process control model is formulated. A dynamic programming approach is used and along with the techniques of Bayesian decision theory, an optimal set of steady state control policies are shown to exist which are dependent upon prior beliefs about the condition of the process. It is the objective of this thesis to compare the results obtained from this approach to those of an X̅ control chart approach. The model proposed by Knappenberger and Grandage [20] is used as a basis for comparison. Numerical examples are used to illustrate each procedure. The results obtained illustrate that by using the operating policies specified by the dynamic approach, a savings of from 29% to 40% in the optimal cost per unit to operate the quality control procedure can be achieved rather than utilizing the policies of the X̅ control chart model.","abstract_has_math":false,"creators":["Beverly, William Howard"],"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":1974,"date_issued":"1974","date_published":"1974","updated_at":"2026-07-22T22:19:12Z","subjects":[],"languages":["en_US"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10919/54835","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":["Beverly, William Howard"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2015-07-28T20:42:12Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2015-07-28T20:42:12Z"]},{"key":"dc:date.issued","label":"Date","values":["1974"]},{"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_US"]},{"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/10919/54835"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["In this thesis, a cost based process control model is formulated. A dynamic programming approach is used and along with the techniques of Bayesian decision theory, an optimal set of steady state control policies are shown to exist which are dependent upon prior beliefs about the condition of the process. It is the objective of this thesis to compare the results obtained from this approach to those of an X̅ control chart approach. The model proposed by Knappenberger and Grandage [20] is used as a basis for comparison. Numerical examples are used to illustrate each procedure. The results obtained illustrate that by using the operating policies specified by the dynamic approach, a savings of from 29% to 40% in the optimal cost per unit to operate the quality control procedure can be achieved rather than utilizing the policies of the X̅ control chart model."]},{"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":["Process control: a dynamic programming approach"]}]}],"canonical_facts":{"dc:contributor.department":["Industrial Engineering and Operations Research"],"dc:creator":["Beverly, William Howard"],"dc:date.accessioned":["2015-07-28T20:42:12Z"],"dc:date.available":["2015-07-28T20:42:12Z"],"dc:date.issued":["1974"],"dc:description.abstract":["In this thesis, a cost based process control model is formulated. A dynamic programming approach is used and along with the techniques of Bayesian decision theory, an optimal set of steady state control policies are shown to exist which are dependent upon prior beliefs about the condition of the process. It is the objective of this thesis to compare the results obtained from this approach to those of an X̅ control chart approach. The model proposed by Knappenberger and Grandage [20] is used as a basis for comparison. Numerical examples are used to illustrate each procedure. The results obtained illustrate that by using the operating policies specified by the dynamic approach, a savings of from 29% to 40% in the optimal cost per unit to operate the quality control procedure can be achieved rather than utilizing the policies of the X̅ control chart model."],"dc:description.degree":["Master of Science"],"dc:format.mimetype":["application/pdf"],"dc:identifier.uri":["http://hdl.handle.net/10919/54835"],"dc:language.iso":["en_US"],"dc:publisher":["Virginia Polytechnic Institute and State University"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Process control: a dynamic programming approach"],"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":"2026-07-22T22:19:12Z"}