Intelligent system for selection of order picking technologies
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Intelligent system for selection of order picking technologies Gabriela Villarreal-Zapata1 • Tomas E. Salais-Fierro1
•
Jania Astrid Saucedo-Martı´nez1
Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract The material handling industry in order to increase the productivity and quality of the order picking process has developed various technical or technological equipment. Therefore, to establish the right technology for every specific business context is a decision that need to be evaluated in a right way. The purpose of this paper is to create an intelligent decision model to select the most appropriate order picking technology. The present study shows an artificial neural network (ANN) trained with the results of an analytic hierarchy process (AHP). The weighting of the determining criteria and the prioritization of the different technologies from several experts are obtained through the AHP, while the artificial neural network is used to automate the decision process. The designed ANN can synthesize expert judgments and then predict the prioritization of order picking technologies. Keywords Order picking Technology Decision making Artificial neural network
1 Introduction The Distribution center is a key element in supply chain, specifically between the production and distribution entities. The tasks or activities that take place in it require a large amount of labor and capital. As a result, the tasks not only has an effect on the warehouse but also on the productivity and operating costs of the entire supply chain [26]. Order picking represents a key activity and one of the most important sources of operational costs in the distribution centers or warehouses. Since the beginning and until the end of this activity, there are numerous possibilities of obtaining unsatisfactory results that affect the quality of the service and the client-supplier relationship [11]. Nevertheless, the client requirements have changed; more frequent orders with smaller amounts of products are
& Tomas E. Salais-Fierro [email protected] Gabriela Villarreal-Zapata [email protected] Jania Astrid Saucedo-Martı´nez [email protected] 1
Facultad de Ingenierı´a Meca´nica y Ele´ctrica, Universidad Auto´noma de Nuevo Leo´n, Ciudad Universitaria, San Nicolas de los Garza, Nuevo Leon, Mexico
now a reality. Thus, companies must respond faster and within shorter time windows and this in turn influences the warehouse configuration and the order preparation activity since they must be done in a shorter time window within larger pick volume [2]. Therefore, an important objective is to minimize or eliminate errors in order picking process and, although fully automating activity is a way to achieve it, the flexibility needed to respond to changes in consumer trends can not be replaced [23]. So, in most situations, humans are the best alternative [28]. To support and facilitate the task of the employee, the material handling industry has devel
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