Demand Forecasting in Hybrid MTS/MTO Production Systems

Demand Forecasting in Hybrid MTS/MTO Production Systems

Moeen Sammak Jalali (Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran) and S.M.T. Fatemi Ghomi (Department of Industrial Engineering, Amirkabir University of Technology, Tehran, Iran)
Copyright: © 2018 |Pages: 16
DOI: 10.4018/IJAIE.2018010104

Abstract

This article describes how simplifying production-planning approaches for demand responsiveness has been well recognized as an operative means of accomplishing production efficiency. To support an effective decision making in manufacturing environments, this study will focus on adopting time series analysis concepts. It will attempt to focus on bringing forward novel structures for classifications of available surveying materials, which helps companies using time series analysis within production strategies to make a logical prediction of demands in hybrid manufacturing systems. In this regard, the authors will present two different categorizing structures as efficient ways of helping practitioners and academicians to find new approaches for applying near possible future forecasts by means of time series analysis methods.
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1. Introduction

1.1. Motivation and Significance

Literature survey of this paper indicates that there is a need to dedicate research works to the development of techniques, methods, and approaches for forecasting demands in the new aged manufacturing systems, i.e. Hybrid MTS/MTO production systems. With this regard, we embark on applying a time series analysis forecasting within Hybrid production systems to make a more accurate prediction of the possible demands in the future.

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