scholarly journals An EPQ inventory model considering an imperfect production system with probabilistic demand and collaborative approach

2019 ◽  
Vol 17 (2) ◽  
pp. 282-304
Author(s):  
Katherinne Salas-Navarro ◽  
Jaime Acevedo-Chedid ◽  
Gina Mora Árquez ◽  
Whady F. Florez ◽  
Holman Ospina-Mateus ◽  
...  
Keyword(s):  
Supply Chain ◽  
Production System ◽  
Inventory Model ◽  
Collaborative Approach ◽  
Lot Size ◽  
Defective Items ◽  
Content Type ◽  
Imperfect Production ◽  
Imperfect Items ◽  
Exponential Probability

Purpose The purpose of this paper is to propose an economic production quantity (EPQ) inventory model considering imperfect items and probabilistic demand for a two-echelon supply chain. The production process is imperfect and the imperfect quality items are removed from the lot size. The demand rate of the inventory system is random and follows an exponential probability density function and the demand of the retailers is depending on the initiatives of the sales team. Design/methodology/approach Two approaches are examined. In the non-collaborative approach, any member of the supply chain can be the leader and takes decisions to optimize the profits, and in the collaborative system, all members make joint decisions about the production, supply, sales and inventory to optimize the profits of the supply chain members. The calculus approach is applied to find the maximum profit related to the members of the supply chain. Findings A numerical example is presented to illustrate the performance of the EPQ model. The results show that collaborative approach generates greater profits to the supply chain and the market’s demand represents the variable behavior and uncertainty that is generated in the replenishment of a supply chain. Originality/value The new and major contributions of this research are: the inventory model considers demand for products is random variable which follows an exponential probability distribution function and it also depends on the initiatives of sales teams, the imperfect production system generates defective items, different cycle time are considered in manufacturer and retailers and collaborative and non-collaborative approaches are also studied.

scholarly journals A Single-Stage Manufacturing Model with Imperfect Items, Inspections, Rework, and Planned Backorders

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 446 ◽  
Author(s):  
Chang Wook Kang ◽  
Misbah Ullah ◽  
Mitali Sarkar ◽  
Muhammad Omair ◽  
Biswajit Sarkar
Keyword(s):  
Production System ◽  
Single Stage ◽  
Order Quantity ◽  
Lot Size ◽  
Defective Items ◽  
Long Run ◽  
Proposed Model ◽  
Imperfect Items ◽  
Inspection Process ◽  
Inspection Station

Each industry prefers to sell perfect products in order to maintain its brand image. However, due to a long-run single-stage production system, the industry generally obtains obstacles. To solve this issue, a single-stage manufacturing model is formulated to make a perfect production system without defective items. For this, the industry decides to stop selling any products until whole products are ready to fulfill the order quantity. Furthermore, manufacturing managers prefer product qualification from the inspection station especially when processes are imperfect. The purpose of the proposed manufacturing model considers that the customer demands are not fulfilled during the production phase due to imperfection in the process, however customers are satisfied either at the end of the inspection process or after reworking the imperfect products. Rework operation, inspection process, and planned backordering are incorporated in the proposed model. An analytical approach is utilized to optimize the lot size and planned backorder quantities based on the minimum average cost. Numerical examples are used to illustrate and compare the proposed model with previously developed models. The proposed model is considered more beneficial in comparison with the existing models as it incorporates imperfection, rework, inspection rate, and planned backorders.

Two-echelon imperfect production fuzzy supply chain model for reliability dependent demand with probabilistic deterioration and rework

2021 ◽  
pp. 1-15
Author(s):  
Sudip Adak ◽  
G.S. Mahapatra
Keyword(s):  
Supply Chain ◽  
Production Rate ◽  
Production Cost ◽  
Idle Time ◽  
Chain Model ◽  
Specific Time ◽  
Defective Items ◽  
Imperfect Production ◽  
Supply Chain Model ◽  
Dependent Demand

This paper develops a fuzzy two-layer supply chain for manufacturer and retailer with defective and non-defective types of products. The manufacturer produces up to a specific time, including faulty and non-defective items, and after the screening, the non-defective item sends to the retailer. The retailer’s strategy is to do the screening of items received from the manufacturer; subsequently, the perfect quality items are used to fulfill the customer’s demand, and the defective items are reworked. The retailer considers that customer demand is time and reliability dependent. The supply chain considers probabilistic deterioration for the manufacturer and retailers along with the strategies such as production rate, unit production cost, cost of idle time of manufacturer, screening, rework, etc. The optimum average profit of the integrated model is evaluated for both the cases crisp and fuzzy environments. Managerial insights and the effect of changes in the parameters’ values on the optimal inventory policy under fuzziness are presented.

System dynamics modelling of fixed and dynamic Kanban controlled production systems: a supply chain perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jagan Mohan Reddy K. ◽  
Neelakanteswara Rao A. ◽  
Krishnanand Lanka ◽  
PRC Gopal
Keyword(s):  
Supply Chain ◽  
System Dynamics ◽  
Cycle Time ◽  
Production System ◽  
Demand Uncertainty ◽  
Production Systems ◽  
Decision Variable ◽  
Content Type ◽  
Pull Production ◽  
Kanban System

Purpose Pull production systems have received much attention in the supply chain management environment. The number of Kanbans is a key decision variable in the pull production system as it affects the finished goods inventory (FGI) and backorders of the system. The purpose of this study is to compare the performance of the fixed and dynamic Kanban systems in terms of operational metrics (FGI and backorders) under the demand uncertainty. Design/methodology/approach In this paper, the system dynamics (SD) approach was used to model the performance of fixed and dynamic Kanban based production systems. SD approach has enabled the feedback mechanism and is an appropriate tool to incorporate the dynamic control during the simulation. Initially, a simple Kanban based production system was developed and then compared the performance of production systems with fixed and dynamic controlled Kanbans at the various demand scenarios. Findings From the present study, it is observed that the dynamic Kanban system has advantages over the fixed Kanban system and also observed that the variation in the backorders with respect to the demand uncertainty under the dynamic Kanban system is negligible. Research limitations/implications In a just-in-time production system, the number of Kanbans is a key decision variable. The number of Kanbans is mainly depended on the demand, cycle time, safety stock factor (SSF) and container size. However, this study considered only demand uncertainty to compare the fixed and dynamic Kanban systems. This paper further recommends researchers to consider other control variables which may influence the number of Kanbans such as cycle time, SSF and container size. Originality/value This study will be useful to decision-makers and production managers in the selection of the Kanban systems in uncertain demand applications.

scholarly journals Inventory control in a two-level supply chain with learning, quality and inspection errors

2021 ◽  
Author(s):  
Mehmood Khan
Keyword(s):  
Supply Chain ◽  
Product Quality ◽  
Inventory Management ◽  
Human Error ◽  
Threshold Value ◽  
Process Quality ◽  
Lot Size ◽  
Defective Items ◽  
Inspection Errors ◽  
Screening Cost

A common measure of quality for a buyer or a vendor is the defect rate. Defects may represent an attribute, a dimension or a quantity. They may be classified as product quality defects or process quality defects. Product quality defects may be caused by human error which can de due to fatigue, lack of proper training, or other reasons. For example, an inspector may misclassify a defective fuel tank of a car as good. On the other hand, process quality defects maybe caused by a machine going out-of-control. While many researchers assume that the screening processes which separate the defective items are error-free, it would be realistic to consider misclassification errors in this process. Beside inspection errors, learning is another human factor that brings in enhancement in the overall performance of a supply chain. Learning is inherent when there are workers involved in a repetitive type of production process. Learning and forgetting are even more important in manufacturing environments that emphasize on flexibility where workers are cross-trained to do different tasks and where products have a short life cycle. Inventory management with learning in quality, inspection and processing time will be the focus of this thesis. A number of models will be developed for a buyer and/or a two level supply chain to incorporate these human factors. The key findings of this work may be summarized as 1. Inspection errors significantly affect the annual profit. 2. An increase in the unit screening cost reduces the annual profit to a great extent at slower rates of learning. 3. For the two-level supply chain we investigated, learning in production drops the annual cost significantly while the learning in supplier's quality results in a situation where there are no defectives from the suppliers. 4. Type II error may seem to be beneficial for a two level supply chain as the order/lot size goes down and thus affects the costs of ordering, production and screening. 5. Consignment stocking policy performs better than conventional stocking when holding costs go higher than a threshold value.

scholarly journals A consignment stock policy for a two-level supply chain with imperfect quality items

2021 ◽  
Author(s):  
Ehab A. Bazan
Keyword(s):  
Supply Chain ◽  
Production Process ◽  
Supply Chain Coordination ◽  
Secondary Market ◽  
Batch Size ◽  
Imperfect Production ◽  
Managerial Decisions ◽  
Imperfect Items ◽  
Imperfect Production Process ◽  
Stock Policy

A consignment stock is a type of supply-chain coordination for the management of supply-chains in which there is a joint vendor and buyer policy that is mainly focused on having the vendor manage the buyer's inventory. This thesis aims to investigate the consignment stock strategy in a single-vendor single-buyer supply-chain context considering imperfect items that may be produced from an imperfect production process. It develops a flexible mathematical model that allows for managerial decisions with regards to imperfect items and seeks to minimize costs (maximize profits) of the supply-chain. Such managerial decisions include scrapping items at a cost, selling them for a marginal profit to a secondary market, applying re-work, and/or applying minor setups to restore the production process. Results show that the introduction of imperfect items increases the batch size and reduces the number of shipments. Minor setups were shown to reduce cost, increase the number of shipments and reduce its size.

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