An instantaneous replenishment model under the effect of a sampling policy for defective items

DOI10.1016/j.apm.2012.02.030zbMath1351.90015OpenAlexW2001158244MaRDI QIDQ350368

Walid W. Nasr, Lama Moussawi-Haidar, Moueen K. Salameh

Publication date: 7 December 2016

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2012.02.030

zbMATH Keywords

lot sizingscreeningacceptance samplingeconomic order quantityimperfect qualityaverage outgoing quality limit

Mathematics Subject Classification ID

Inventory, storage, reservoirs (90B05)

Related Items (7)

Effect of deterioration on the instantaneous replenishment model with imperfect quality items ⋮ Optimization of sample size and order size in an inventory model with quality inspection and return of defective items ⋮ Optimal buyer's replenishment policy in the integrated inventory model for imperfect items ⋮ Determining an optimal production run length with an extended quality control policy for an imperfect process ⋮ Production lot sizing with quality screening and rework ⋮ Economic production quantity with the presence of imperfect quality and random machine breakdown and repair based on the artificial bee colony heuristic ⋮ An inventory model with imperfect items, stock dependent demand and permissible delay in payments under inflation

Cites Work

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• An application of fuzzy sets theory to the EOQ model with imperfect quality items
• Integrated inventory control and inspection policies with deterministic demand
• The Compound Hypergeometric Distribution and a System of Single Sampling Inspection Plans Based on Prior Distributions and Costs
• EPQ with Process Capability and Quality Assurance Considerations
• Optimal Lot Sizing, Process Quality Improvement and Setup Cost Reduction
• Joint Determination of Optimal Inventory and Quality Control Policy
• Joint determination of production quantity, inspection schedule, and quality control for an imperfect process with deteriorating products
• Lot Sizing with Random Yields: A Review

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