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Demand Forecasting: A Challenge for Furniture SMEs
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Author(s): Natalie Nicole Mar Hernández (UPAEP University, Mexico), Patricia Cano-Olivos (UPAEP University, Mexico), Diana Sánchez-Partida (UPAEP University, Mexico), José-Luis Martínez-Flores (UPAEP University, Mexico)and Santiago Omar Caballero-Morales (UPAEP University, Mexico)
Copyright: 2020
Pages: 21
Source title:
Handbook of Research on Developments and Trends in Industrial and Materials Engineering
Source Author(s)/Editor(s): Prasanta Sahoo (Jadavpur University, India)
DOI: 10.4018/978-1-7998-1831-1.ch001
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Abstract
This chapter provides a proposal for demand management in furniture SMEs located in the city of Puebla, México. The historical production data reviewed, and the classification of the most critical articles was made using the ABC classification methodology. Subsequently, the literature of SMEs was analyzed as well as the current situation and statistical information was sought. Additionally, it presented an overview of the models to forecast demand and applied to the most relevant articles. Due to the results and previous study, it was decided to implement a forecasting technique which is modelled by artificial neural networks. The ANN model developed with the TANSIGMOID transfer function by using MATLAB software. The appropriate forecasting techniques selected according to the variability of the demand of the articles takes a short-term planning horizon. This research will help the company reduce uncertainty, forecasting sales, and achieve better production planning through ANNs.
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