Batch Sizing in Sustainable Production Systems with Imperfect Quality

In classic Economic Production Quantity (EPQ), an optimal batch size is determined to minimize total production cost including setup and inventory holding costs, and defective parts are not allowed. In this paper an imperfect EPQ system is studied to minimize the overall cost, where setup cost, scarp rate, batch size, and electrical power demand are determined by the model. In this imperfect production system, a percentage of the batch is defective in each cycle, which will be reworked at an extra charge. In addition, the model considers electrical power demand charge which accounts for a large percentage of industrial utility bills. This framework also determines the optimal level of investment on system design and flexibility which in turn, is a function of setup cost, electrical power requirement (power demand), and scrap rate. The proposed constrained cost minimization problem is formulated as a nonlinear mathematical model, and is solved using a posynomial Geometric Programming (GP) approach to present a closed form solution for the batch size, setup cost, allowable defective rate and power requirements. The model is illustrated through a numerical example and some sensitivity analysis is performed

Multi products single machine economic production quantity model with multiple batch size

In this paper, a multi products single machine economic order quantity model with discrete delivery is developed. A unique cycle length is considered for all produced items with an assumption that all products are manufactured on a single machine with a limited capacity. The proposed model considers different items such as production, setup, holding, and transportation costs. The resulted model is formulated as a mixed integer nonlinear programming model. Harmony search algorithm, extended cutting plane and particle swarm optimization methods are used to solve the proposed model. Two numerical examples are used to analyze and to evaluate the performance of the proposed model

Model EPQ Multi Item yang Dimodifikasi untuk Dua Permintaan secara Simultan

Inventory is one of many factors of the business operation that need to be controlled by industries in order to improve efficiency, enhance productivity, and decrease the holding cost. The holding cost of inventories in supply chain contribute to 20% - 40% of the product value. It can be controlled by applying appropriate inventory model, such as EPQ/Economic Production Quantity and EOQ/Economic Order Quantity. EPQ is an inventory model that used to determine the optimum production lot size with balanced the production setup cost and holding cost. Even the classic EPQ has applied widely in industries, the assumption used by this model differed between the researchers whether it is continuous or discrete demand, because the multi delivery or discrete demand is mostly used by industries. Even so, there are industries that used both continuous and discrete demand simultaneously. Based on previous research, there was an advanced EPQ model that synchronizing both assumptions simultaneously, but it still addressed single item problem. Since almost the industries produced multi item, this model has lack of applicability. Therefore, this research proposed a multi item EPQ Model that synchronizing continuous and discrete demand simultaneously. The solution procedure that used in this proposed model are classical calculus method/differential calculus and simultaneous approach. A numerical example is given to show the effectiveness of the proposed approach based on the data from the literature

Global optimisation for a developed price discrimination model:A signomial geometric programming-based approach

This paper presents a price discrimination model for a manufacturer who acts in two different markets. In order to have a fair price discrimination model and compare monopoly and competitive markets, it is assumed that there is no competitor in the first market (monopoly market) and there is a strong competitor in the other market (competitive market). The manufacturer objective is to maximize the total benefit in both markets. The decision variables are selling price, lot size, marketing expenditure, customer service cost, flexibility and reliability of production process, set up costs and quality of products. The proposed model in this paper is a signomial geometric programming problem which is difficult to solve and find the globally optimal solution. So, this signomial model is converted to a posynomial geometric type and using an iterative method, the globally optimal solution is found. To illustrate the capability of the proposed model, a numerical example is solved and the sensitivity analysis is implemented under different conditions

Global optimisation for a developed price discrimination model:A signomial geometric programming-based approach

This paper presents a price discrimination model for a manufacturer who acts in two different markets. In order to have a fair price discrimination model and compare monopoly and competitive markets, it is assumed that there is no competitor in the first market (monopoly market) and there is a strong competitor in the other market (competitive market). The manufacturer objective is to maximize the total benefit in both markets. The decision variables are selling price, lot size, marketing expenditure, customer service cost, flexibility and reliability of production process, set up costs and quality of products. The proposed model in this paper is a signomial geometric programming problem which is difficult to solve and find the globally optimal solution. So, this signomial model is converted to a posynomial geometric type and using an iterative method, the globally optimal solution is found. To illustrate the capability of the proposed model, a numerical example is solved and the sensitivity analysis is implemented under different conditions

PRODUCTION PLANNING MULTI-PRODUCT AND MULTI-MACHINE PROBLEMS IN ORDER TO MAXIMIZE THE ECONOMIC PERFOMANCE

Este artigo propõe um novo método que visa à maximização do resultado econômico operacional, através do planejamento de produção. O modelo utiliza um algoritmo de otimização que envolve quatro áreas de análise: mercado, produção, custos e por fim o resultado econômico. O objetivo é a maximização do lucro. A aplicação do modelo ocorre em uma empresa de manufatura que tem se caracterizado por alta variabilidade na definição dos preços de venda. Os resultados deste estudo indicam que pequenas variações nos preços de venda podem comprometer substancialmente os lucros globais do sistema produtivo