An EPQ model for deteriorating items with imperfect production, inspection errors, rework and shortages : a type-2 fuzzy approach

OPSEARCH ◽  
2019 ◽  
Vol 56 (3) ◽  
pp. 657-688 ◽  
Author(s):  
Chayanika Rout ◽  
Ravi Shankar Kumar ◽  
Debjani Chakraborty ◽  
Adrijit Goswami
Keyword(s):  
Deteriorating Items ◽  
Fuzzy Approach ◽  
Inspection Errors ◽  
Imperfect Production ◽  
Epq Model ◽  
Production Inspection

Solution of an EPQ model for imperfect production process under game and neutrosophic fuzzy approach

2020 ◽  
Vol 93 ◽  
pp. 106397 ◽  
Author(s):  
Sujit Kumar De ◽  
Prasun Kumar Nayak ◽  
Anup Khan ◽  
Kousik Bhattacharya ◽  
Florentin Smarandache
Keyword(s):  
Production Process ◽  
Fuzzy Approach ◽  
Imperfect Production ◽  
Imperfect Production Process ◽  
Epq Model

An EPQ Model for Deteriorating Items With Imperfect Production, Two Types of Inspection Errors and Rework Under Complete Backordering

2020 ◽  
Vol 22 (02) ◽  
pp. 2040011
Author(s):  
Chayanika Rout ◽  
Debjani Chakraborty ◽  
Adrijit Goswami
Keyword(s):  
Type I Error ◽  
Type I ◽  
Lot Size ◽  
Inventory Cost ◽  
Inspection Errors ◽  
Imperfect Production ◽  
Constant Rate ◽  
Epq Model ◽  
Total Inventory ◽  
Production Lot Size

This paper presents an EPQ model which illustrates imperfect production and imperfect inspection processes for items that are subject to a constant rate of deterioration. The model considers two types of inspection errors, namely, Type I error of falsely screening out a proportion of nondefects, thereby passing them on for rework and Type II error of falsely not screening out a proportion of defects, thus selling those to customers which results in defect sales returns. The screened and returned items are then reworked and the proportion that could not be reworked successfully is scrapped. Shortages are allowed and are completely backlogged. Finally, we calculate the optimal production lot size and the optimal backordering quantity in order to minimize the total inventory cost per unit time. A numerical example is also considered to exemplify the obtained theoretical results which is followed by the complete sensitivity analysis of the involved parameters for even better managerial insights.

Multi-item EPQ model with learning effect on imperfect production over fuzzy-random planning horizon

2016 ◽  
Vol 4 (1) ◽  
pp. 80-110 ◽  
Author(s):  
Amalesh Kumar Manna ◽  
Barun Das ◽  
Jayanta Kumar Dey ◽  
Shyamal Kumar Mondal
Keyword(s):  
Learning Effect ◽  
Planning Horizon ◽  
Imperfect Production ◽  
Epq Model ◽  
Random Planning Horizon ◽  
Fuzzy Random
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