Inventory models for imperfect quality items with shortages and learning in inspection

The classical economic order quantity model, although well known and useful; assumes that all items received conform to quality characteristics. However, in practice, items may be damaged due to transportation and/or production conditions. This requires a buyer to screen each lot it receives from its vendor to separate the good from the nonconforming (due to imperfect quality) items. While screening is usually a manual task performed by inspectors, it may improve with learning. Besides, it was observed in some studies that coordinating activities (e.g., quality) between a buyer and a vendor may be subject to learning effects and results in improving the quality of each lot (as it contains less nonconforming items) delivered or produced.This paper investigates an EOQ model with imperfect quality items and shortages, where the fraction of imperfect quality in each shipment reduces because of learning. Mathematical models are developed for the cases of infinite and finite planning horizons. Numerical results, which have several interesting managerial insights and implications, are presented and discussed. This paper may be useful to managers who wish to benefit from the learning opportunities in their logistics and inventory systems, especially, when comparing different production strategies and making choices regarding the selection of suppliers or the processes that need improvements.