Extension of product’s useful life through product recovery options can help to reduce the consumption of natural resource and environmental pollution. Remanufacturing operation is considered as the most suitable product recovery option for automotive parts. The objective of this paper is to identify the barriers and the critical success factors in automotive engine remanufacturing. A case study is carried out in an automotive engine remanufacturing plant, situated in the south-western part of India. In this case study, the strategic, tactical and operational characteristics of the remanufacturing process are explored, what are the barriers they have faced while remanufacturing and to overcome those barriers, what strategies they have adopted are also analyzed. A fuzzy technique for order performance by similarity to ideal solutions (TOPSIS) is used to identify the critical success factor to overcome the roadblocks of remanufacturing. As this study is directed by the experts’ opinion from the remanufacturing plant which proves its practical implication. This case study is also useful for the other OEM remanufacturers in India.

Many researchers focused on economic production quantity (EPQ) model for deteriorating items with rework of defective items in a single production run. Few of them proposed the model for multi-production inventory model under the assumptions (i) all the defective items can be reproduced as serviceable items and (ii) all the deteriorating items can be detached from the inventory through screening process. However, in real life manufacturing systems, due to controllable or uncontrollable factors, the defective items may not be reproduced as serviceable items and hence the generation of scrap (disposable) items is potential. It is possible that the internally deteriorating items like fruits, vegetables, eggs, pharmaceutical drugs, etc. pass on to customers which will make negative impact on corporate image in the global market. This paper presents a multi-production run inventory model for deteriorating items with scrap, defective items, failure rework and penalty cost for selling the deteriorating items to customers under finite planning horizon. Our objective is to determine the optimal production run, optimal finite planning horizon by minimizing the total cost of the system. A solution procedure with an algorithm is proposed and a numerical example is provided to demonstrate the applicability of the model. Finally, sensitivity analysis is provided to provide managerial phenomena of the system.

This paper considers the factor influencing on an airline carrier based on operations of an airport on the routes flown out of that airport. This study deals with evaluation of the Customer Performance index (CPI) of distinct domestic civil airlines in India. CPI consists of various parameters; among them many disembodied parameters, which are difficult to measure. In this context, initially we identified the prime factors that are crucial for evaluation of performances provided by various airlines in India. Thereafter, in order to determine the hierarchy among these factors; modified digital logic (MDL) approach is employed and cost is found to be the most important criteria. Furthermore, CPI is calculated using fuzzy-VIKOR approach. Such approaches can help the airlines in re-evaluating their current policies and then formulate comparatively more efficient market strategies to improve performance quality and to gain customers’ loyalty.

Recently, Symbiotic Organisms Search (SOS) algorithm is being used for solving complex problems of optimization. This paper proposes an Improved Symbiotic Organisms Search (I-SOS) algorithm for solving different complex unconstrained global optimization problems. In the improved algorithm, a random weighted reflective parameter and predation phase are suggested to enhance the performance of the algorithm. The performances of this algorithm are compared with the other state-of-the-art algorithms. The parametric study of the common control parameter has also been performed.

Inflation is an important factor influencing traditional economic order quality models. Marketing strategy depends on inflation due to public demand and availability of the materials. This paper presents an optimal inventory policy for deteriorating items using exponential demand rate under permissible delay in payments. Mathematical model has been derived under two cases: case I: cycle time is greater than or equal to permissible delay period, case II: cycle time is less than permissible delay period by considering holding cost as a function of time. Numerical examples and sensitivity analysis are given to reflect the numerical results. Mathematica software is used for finding optimal solutions.

This study aims to investigate the factors that influence consumer satisfaction with e-grocery shopping. Moreover, it also delves into factors that motivate shoppers to buy groceries from online retailers rather than conventional stores. A primary survey was administered to collect data. Initially, 500 questionnaires were circulated to respondents. People who have ordered groceries from online sites were the expected respondents. In this study, convenience sampling was used, and data were analyzed using structural equation modeling (SEM). The findings affirmed the relationship between consumer satisfaction and perceived convenience, risk factors, perceived product quality, and time value. However, perceived value and value for the time have a little significant effect on consumer satisfaction. There have been relatively few academic studies that look at the variables that influence customer satisfaction when shopping for groceries online. Most of the studies look at the variables that influence consumer satisfaction in the life insurance and financial services industries. By analyzing the data from Delhi and the Nation Capital Region (NCR) of Delhi, this research aims to bridge this gap available in the literature.

This paper presents an experimental investigation on cutting temperature during hard turning of EN 24 steel (50 HRC) using TiN coated carbide insert under dry environment. The prediction model is developed using response surface methodology and optimization of process parameter is performed by desirability approach. A stiff rise in cutting temperature is noticed when feed and cutting speed are elevated. The effect of depth of cut on cutting temperature is not that much significant compared with cutting speed and feed as observed from main effects plot. The response surface second order model presented high correlation coefficient (R2 = 0.992) explaining 99.2 % of the variability in the cutting temperature which indicates the goodness of fit for the model to the actual data and high statistical significance of the model. The experimental and predicted values are very close to each other. The calculated error for cutting temperature lies between 1.88-3.19 % during confirmation trial. Therefore, the developed second order model correlates the relationship of the cutting temperature with the process parameters with good degree of approximation. The optimal combination for process parameter is depth of cut at 0.2mm, feed of 0.1597 mm/rev and cutting speed of 70m/min. Based on these combination, the value of cutting temperature is 302.950C whose desirability is one.

The objective of this work is to generalize the three echelon supply chain model proposed by Jaber and Goyal (2008) [Jaber, M. Y., & Goyal, S. K. (2008). Coordinating a three-level supply chain with multiple suppliers, a vendor and multiple buyers. International Journal Production Economics, 116, 95-103.] for multi-items where single item was considered in production and distribution. This paper develops the coordination amongst different parties in a three-echelon supply chain with a centralized decision process. Producer, suppliers and retailers are the parties of the supply chain where multiple suppliers deliver various types of raw materials to a producer; producer produces different types of items, multi-items, in different units of the factory and supplies the items to multiple retailers. Different deterioration rates for finished items and raw materials are also considered. The model developed of this paper guarantees that the local costs for the members either remain the same as before coordination, or decrease as a result of coordination. A numerical example along with graphical illustrations is considered and the sensitivity analysis is provided to test the feasibility of the proposed model.

In this paper, an attempt is made to characterize the preservation technology for deteriorating items to reduce the deterioration rate. This model assumes a single producer and single supplier and formulates a production model with a time varying rate of deterioration rate. Here production and demand are treated as a fuzzy variables and total cost is minimized for both the crisp and fuzzy model. Shortage is allowed on the supplier’s part, which is partially backlogged. A solution procedure is presented to determine an optimal replenishment cycle and total cost per unit time, which is a convex function of preservation technology cost. Results have been validated with relevant example. In a way, the proposed model provides a unique theory to reduce the deterioration rate for the production model.

This article studies the manufacturer & apos; s pricing strategy in a supply chain with a single manufacturer and two competing retailers. The manufacturer, as a Stackelberg leader specifies wholesale prices to two retailers who face advertisement dependent demand. Based on this gaming structure, two mathematical models are developed - the cooperative advertising model where manufacturer shares a fraction of retailers & apos; advertising costs and the non-cooperative advertising model where manufacturer does not share any retailer & apos; s advertising expenses. The optimal strategies of the manufacturer and retailers are determined and a numerical example is taken to illustrate the theoretical results derived. We show that cooperative advertising policy is beneficial not only for the participating entities but also for the entire supply chain.