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Credit Financing Scheme for Imperfect Quality Items with Allowable Shortage and Learning Effects on Screening Process
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 186 - Number 48 |
| Year of Publication: 2024 |
| Authors: Leena Sharma, A.R. Nigwal |
10.5120/ijca2024924143
|
Leena Sharma, A.R. Nigwal . Credit Financing Scheme for Imperfect Quality Items with Allowable Shortage and Learning Effects on Screening Process. International Journal of Computer Applications. 186, 48 ( Nov 2024), 35-42. DOI=10.5120/ijca2024924143
Abstract
The advent of new technologies, systems, trend workforce and new applications in manufacturing/production sector has undoubtedly lightened workloads. However occasional diversifications in production system cannot be completely eliminated. Each produced/ordered batch may contain a fraction of defective items which can vary from batch to batch. Nevertheless, defective items are often removed from high quality batch through a discrete screening procedure. Thus, a screening process is considered an essential task in technology -based industries, with the sole objective of ensuring customer satisfaction. Furthermore, the repetition of same tasks enhances workers efficiency. Additionally, credit financing has been recognized as an impressive promotional tool to attract new customers and serve as an effective incentive scheme for retailers. Based on this scenario, the present article proposed an inventory model for a retailer dealing with imperfect quality items under permissible delays in payment. A screening process was applied to each batch to separate good and defective items and learning effects were analyzed with allowable shortages under fully backlogged demand. This model developed such strategies so that the order quantity, shortages and the number of repetitions on screening are optimized and the expected total profit may be maximum. A mathematical model was formulated to represent this scenario. The results were validated using numerical examples and a comprehensive sensitivity analysis was conducted with respect to key parameters.
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