Dynamic Performance of Service-manufacturing Hybrid Supply Chain with Two Forecasting Methods

DOI

10.2991/fmsmt-17.2017.241How to use a DOI?

Keywords

Hybrid Supply Chain, Exponential Smoothing Forecasts, Moving Average Forecasts, Dynamic Response.

Abstract

This paper deals with the study of the dynamic performance of service-manufacturing hybrid supply chain with different forecasting methods. Two forecasting methods in two-echelon hybrid supply chain system are exponential smoothing forecasts (ESF) and moving average forecasts (MAF). Based on Automatic Pipeline Inventory and Order Based Production Control System (APIOBPCS), the Automatic Pipeline Control System of Production and Service in Hybrid Supply Chain (APIOBPSCS) is built using control theory. On this basis, the dynamic responses of two hybrid supply chain systems under step demand input are analyzed by simulation. As the system parameters change, two kinds of hybrid supply chains with different forecasting methods are compared in the performance , the fluctuations of product order rate, works in process (WIP), and actual inventory of product and service pile-up rate. Simulation result shows that the overall influence of hybrid supply chain should be considered according to the different forecasting methods. With selecting corresponding forecasting methods, the reasonable system parameters will be set to improve the overall operation efficiency of hybrid supply chain system.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Weiwei Wang
AU  - Yue Hong
AU  - Zaifang Zhang
PY  - 2017/04
DA  - 2017/04
TI  - Dynamic Performance of Service-manufacturing Hybrid Supply Chain with Two Forecasting Methods
BT  - Proceedings of the 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017)
PB  - Atlantis Press
SP  - 1231
EP  - 1236
SN  - 2352-5401
UR  - https://doi.org/10.2991/fmsmt-17.2017.241
DO  - 10.2991/fmsmt-17.2017.241
ID  - Wang2017/04
ER  -