dc.contributor.advisor | Barker, Kash | |
dc.contributor.author | Bourgeois, Christopher | |
dc.date.accessioned | 2021-05-12T15:20:18Z | |
dc.date.available | 2021-05-12T15:20:18Z | |
dc.date.issued | 2021-05 | |
dc.identifier.uri | https://hdl.handle.net/11244/329531 | |
dc.description.abstract | Production facilities are critical components of the global economy and supply chain. Firms are forced to balance several competing objectives—from reducing operating costs by managing inventory to increasing profits by satisfying customer demand. The act of scheduling material through an interconnected production network is analytically challenging; therefore, stakeholders require statistical insights in order to strengthen decision making. This inventory scheduling application allows decision makers to monitor the status and impact of numerous production parameters, while aiming to mitigate the propagation of schedule risk through the system. This work extends the material planning framework from Soltanisehat et al. (2021) that (i) jointly represents work center and material relationships and (ii) integrates stochastic methods to assess potential risk. Using network flow optimization and Monte Carlo simulation, this extension accommodates three primary considerations: (i) safety stock and other inventory restrictions, (ii) multi-product order satisfaction, and (iii) costs derived from holding inventory and delaying orders. An illustrative example examines the impact of six experimental scenarios on order fulfillment, work center utilization, and material inventory and production. | en_US |
dc.language | en_US | en_US |
dc.rights | Attribution 4.0 International | * |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | * |
dc.subject | Monte Carlo simulation | en_US |
dc.subject | material requirements planning | en_US |
dc.subject | production schedule risk | en_US |
dc.subject | network flow optimization | en_US |
dc.title | Inventory Scheduling Framework to Fulfill Multi-Product Orders within an Interconnected Production Network | en_US |
dc.contributor.committeeMember | González, Andrés | |
dc.contributor.committeeMember | Li, Yifu | |
dc.date.manuscript | 2021-05 | |
dc.thesis.degree | Master of Science | en_US |
ou.group | Gallogly College of Engineering::School of Industrial and Systems Engineering | en_US |
shareok.orcid | 0000-0003-3219-2361 | en_US |
shareok.nativefileaccess | restricted | en_US |