{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/29142"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/29142","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Impact of Alternative Flow Control Policies on Value Stream Delivery Robustness Under Demand Instability: a System Dynamics Modeling and Simulation Approach","abstract":"This research explores the effect of proposed management policies and related structures on the dynamics of value streams, particularly under demand instability. It relies on methods from the systems thinking and modeling literature and was designed to fulfill three main objectives. Objective 1: Provide insight into the causes of problematic behavior in traditional value streams. Objective 2: Identify modes of demand behavior suitable for pull-based systems operation. Objective 3: Propose and test alternative value stream management policies and structures. The achievement of objectives 1 and 3 required the fulfillment of both a hypothetical and a real case. The hypothetical case was designed to describe the problem and improvement alternatives in generic terms, whereas the real case served to contextualize the main generic modeling elements in a real world situation, thus serving as an illustrative example. The research approach was one based on system dynamics modeling and simulation methodologies that reflect the scientific method. Three alternative policies were created and tested. Policy 1: a decision rule for altering the number of kanbans in circulation at the protective decoupling inventory during production cycles. Policy 2: a decision rule for defining the amount of demand to include in value stream schedules. Policy 3: a decision rule for setting a purposefully unbalanced downstream production capacity. The results suggest a benefit from the combined use of Policies 2 and 3 in the face of sudden demand peaks. Policy 1 is expected to provide minor benefits but also significantly increase the risk of upstream instability and therefore its use is not recommended. This study provides a causality perspective of the structure of value streams, and gives enterprise engineers new insights into the state-of-the-art in value stream design.","abstract_html":"This research explores the effect of proposed management policies and related structures on the dynamics of value streams, particularly under demand instability. It relies on methods from the systems thinking and modeling literature and was designed to fulfill three main objectives. Objective 1: Provide insight into the causes of problematic behavior in traditional value streams. Objective 2: Identify modes of demand behavior suitable for pull-based systems operation. Objective 3: Propose and test alternative value stream management policies and structures. The achievement of objectives 1 and 3 required the fulfillment of both a hypothetical and a real case. The hypothetical case was designed to describe the problem and improvement alternatives in generic terms, whereas the real case served to contextualize the main generic modeling elements in a real world situation, thus serving as an illustrative example. The research approach was one based on system dynamics modeling and simulation methodologies that reflect the scientific method. Three alternative policies were created and tested. Policy 1: a decision rule for altering the number of kanbans in circulation at the protective decoupling inventory during production cycles. Policy 2: a decision rule for defining the amount of demand to include in value stream schedules. Policy 3: a decision rule for setting a purposefully unbalanced downstream production capacity. The results suggest a benefit from the combined use of Policies 2 and 3 in the face of sudden demand peaks. Policy 1 is expected to provide minor benefits but also significantly increase the risk of upstream instability and therefore its use is not recommended. This study provides a causality perspective of the structure of value streams, and gives enterprise engineers new insights into the state-of-the-art in value stream design.","abstract_has_math":false,"creators":["Sousa, George"],"institution":"Virginia Tech","degree_name":"Ph. D.","degree_level":"doctoral","degree_discipline":"Industrial and Systems Engineering","degree_department":"Industrial and Systems Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Koelling, C. Patrick","Van Aken, Eileen M."],"committee_members":["Rentes, Antonio F.","Ellis, Kimberly P.","Chen, Fengshan Frank"],"year":2004,"date_issued":"2004-09-17","date_published":"2004-09-17","updated_at":"2026-07-22T22:18:47Z","subjects":["systems engineering","lean enterprise design","delivery performance","value stream mapping","systems thinking"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-09302004-235116"],"render_values":[{"text":"etd-09302004-235116","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/29142","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Koelling, C. 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Policy 1: a decision rule for altering the number of kanbans in circulation at the protective decoupling inventory during production cycles. Policy 2: a decision rule for defining the amount of demand to include in value stream schedules. Policy 3: a decision rule for setting a purposefully unbalanced downstream production capacity. The results suggest a benefit from the combined use of Policies 2 and 3 in the face of sudden demand peaks. Policy 1 is expected to provide minor benefits but also significantly increase the risk of upstream instability and therefore its use is not recommended. This study provides a causality perspective of the structure of value streams, and gives enterprise engineers new insights into the state-of-the-art in value stream design."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. 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