Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/9027
Title: Production process parameter optimization with a new model based on a genetic algorithm and ABC classification method
Authors: Eric M.
Stefanovic, Miladin
Djordjevic, Aleksandar
Stefanovic N.
Mišić, Milan
Abadic, Nebojsa
Popovic P.
Journal: Advances in Mechanical Engineering
Issue Date: 1-Aug-2016
Abstract: © The Author(s) 2016. The difference between the production cost and selling price of the products may be viewed as a criterion that determines an organization's competitiveness and market success. In such circumstances, it is necessary to impact these criteria in order to maximize this difference. The selling products' price, in modern market conditions, is a category which may not be significantly affected. So organizations have one option, which is the production cost reduction. This is the motive for business organizations and the imperative of each organization. The key parameters that influence the costs of production and therefore influence the competitiveness of organizations are the parameters of production machines and processes used to create products. To define optimal parameter values for production machines and processes that will reduce production costs and increase competitiveness of production organizations, the authors have developed a new mathematical model. The model is based on application of the ABC classification method to classify production line processes based on their costs and an application of a genetic algorithm to find the optimal values of production machine parameters used in these processes. It has been applied in three different modern production line processes; the costs obtained by the model application have been compared with the real production costs.
URI: https://scidar.kg.ac.rs/handle/123456789/9027
Type: journal article
DOI: 10.1177/1687814016663477
ISSN: 16878132
SCOPUS: 84984923523
Appears in Collections:Faculty of Engineering, Kragujevac

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