Author: Eman Alaa Heikal
Publisher:
Published: 2014
Total Pages: 258
ISBN-13:
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Abstract: In last century, the world has witnessed a great deal of technological and industrial progress. Branded products manufacturers have been competing in introducing new versions of their products frequently. Retailers and banks have been developing relaxed paying systems to fund the purchase of these new products. Exchanging strategies have been initiated by companies for customers to exchange their old version product for the latest versions. Such exchanging strategies are famous for vehicles, mobiles, and electrical appliances. Hence, a huge amount of unused or spent products are generated every day. Many researchers have been developing different models for dealing with the decisions related to remanufacturing operations. However, there is no decision making system the manufacturers could use for cost / benefit assessment of disassembling and recovering these products that considers the following points: (1) evaluating the value of recovering the whole product versus value associated with recovering its disassembled items , (2) using Multi-Objective Mixed Integer Linear Programming (MILP) to assign spent products and their items to various recovery alternatives considering their received physical conditions, (3) selection of operations for items is not limited by a fixed regular production-hour capacity for each operation, (4) model assumptions, constraints, and formulation that satisfy the three aspects of sustainability, which are economic, social responsibility, and environmental aspects in one step model , (5) considering other vital dimensions which are the quality of recovered products and the minimum batch size for vending recycled materials, (6) utilizing the recycling operation in the optimum way that increases revenue from vending isolated materials. The thesis addresses these points using mathematical modeling and optimization for the remanufacturing operations of spent products. The aim of this study is achieved through modeling the problem using a multi-objective mixed integer linear programming technique with two objective functions considering net profit maximization and total disposal weight minimization. Maximizing the net profit over specified planning periods satisfies the economic aspect of sustainability. Minimizing the total weight at all items assigned to disposal over specified planning periods satisfies the environmental aspect of sustainability. Initiating fair refunding system for spent products satisfies social responsibility aspect of sustainability. The optimum solutions of the model provides: optimal disassembly sequence of items, number of each item assigned to various recovery operations of the remanufacturing unit, specification of the required total regular production hours, total needed number of workers, and specification of the number of workers hired and fired. For verifying the proposed model and its LINGO code, the data of a simplified version of the trailer case study was used to display the model and tracking the displayed model to assure that the generated code exactly matches the model formulation, and to discover and correct any logical error. Then, the model was run several times to assure the accuracy of the model and to test the functionality of all the model mathematical equations. Its target was to assure that the integration of the model constraints exactly matched the logic of solving the problem, and the mathematical equation succeeded in expressing the model goals. A case study that involves a numerical real- life critical problem in Egypt is solved considering only the first objective function, which is targeting feasible solutions for the collected trailers that are prohibited to move on the Egyptian roads. The results show that the remanufacturing of semi-trailers from the collected trailers is the most profitable solution for the good-condition trailers, while applying the cannibalization operation on the bad conditions trailers is the most profitable solution for the case. The remanufacture unit would make a net profit of L.E 8,878,800 for applying this solution at the end of the three planning periods. In case the remanufacture unit decided to restrict its recovery activities to the good condition trailers, the net profit of scenario 2 is L.E 20,499,100 at the end of the three planning periods, which is associated with an increase of L.E 11,620,300 in profit compared to recovering different conditions trailers. A professional sensitivity analysis is implemented using the factorial design to accurately decide the significant input parameters that impact the net profit and total disposal weight at the end of the three planning periods for the trailers numerical problem. This factorial sensitivity analysis is designed to test 3 factors for 5 levels. Therefore, 53=125 runs are conducted of all possible combination of these factors (input parameters), and the determination of output responses corresponding to each combination. Hence, the significant input parameters that impact the decisions were concluded. The input parameters that were selected are: selling prices, refund costs, and direct labor processing costs. The output responses that were selected are the net profit and the total disposal weight. It was discovered that changing the selling prices of the output products from the recovery operations which are refurbishing, repairing, remanufacturing, and cannibalization, and the selling prices of the recycled materials has the most influential impact on the net profit , and has the only significant impact on the total disposal weight at the end of the three planning periods. The refund costs paid to the end users for compensating them of getting their products is the second significant factor on the net profit at the end of the three planning periods. Hence, it is crucial to specify these selling prices and refund costs wisely. Two approaches are used to solve the multiple objectives of the modified trailer case study, and to create a set of non-dominating solutions for the referred case which are: Minimax weighting method and constrained method. The most profitable and worst environmental non-dominated solution happened when the referred case was solved using the constrained method at bounding the disposal to 14870.3 kg, where the net profit value reaches its maximum of L.E 8,183,012, when the total weight of the items assigned to disposal reaches its peak of 14835.3 kg. This first best environmental non-dominating solution happened when the case was solved using the constrained method at bounding the disposal to 0 kg, where the net profit value reaches its minimum of L.E 7, 425,400. Solving the referred case using Minimax weighting methods is resulted in balancing solution of two competing objectives. The generated set of non-dominated solutions demonstrated the multi-objective nature of the proposed model.
