Modeling and forecasting customer demands

In this paper, I have made an attempt to seek what statistical models and forecasting techniques which are appropriate to support decision making in the operational level of supply chain while dealing with customer demands on short life cycle products to avoid undesired production condition. A typic...

Full description

Saved in:
Bibliographic Details
Main Author: See, Tian Pau.
Other Authors: Ma Maode
Format: Final Year Project
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/45011
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-45011
record_format dspace
spelling sg-ntu-dr.10356-450112023-07-07T16:27:24Z Modeling and forecasting customer demands See, Tian Pau. Ma Maode School of Electrical and Electronic Engineering A*STAR SIMTech DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation In this paper, I have made an attempt to seek what statistical models and forecasting techniques which are appropriate to support decision making in the operational level of supply chain while dealing with customer demands on short life cycle products to avoid undesired production condition. A typical demand curve for these short life products consists of rapid growth, maturity and decline phases coupled with seasonal variation. The literature study provides knowledge about the forecasting method ranges and their applications. Whilst, studying the current forecasting practices gives knowledge about what have been done in the company and the company’s expectations with respect to this matter. The company’s expectations are related to the general objectives of the forecasting process which is described through an objective tree approach and the solutions for the company’s specific forecasting problems which are identified through a system diagram and causal diagram approaches. Bachelor of Engineering 2011-06-08T03:29:00Z 2011-06-08T03:29:00Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/45011 en Nanyang Technological University 52 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation
See, Tian Pau.
Modeling and forecasting customer demands
description In this paper, I have made an attempt to seek what statistical models and forecasting techniques which are appropriate to support decision making in the operational level of supply chain while dealing with customer demands on short life cycle products to avoid undesired production condition. A typical demand curve for these short life products consists of rapid growth, maturity and decline phases coupled with seasonal variation. The literature study provides knowledge about the forecasting method ranges and their applications. Whilst, studying the current forecasting practices gives knowledge about what have been done in the company and the company’s expectations with respect to this matter. The company’s expectations are related to the general objectives of the forecasting process which is described through an objective tree approach and the solutions for the company’s specific forecasting problems which are identified through a system diagram and causal diagram approaches.
author2 Ma Maode
author_facet Ma Maode
See, Tian Pau.
format Final Year Project
author See, Tian Pau.
author_sort See, Tian Pau.
title Modeling and forecasting customer demands
title_short Modeling and forecasting customer demands
title_full Modeling and forecasting customer demands
title_fullStr Modeling and forecasting customer demands
title_full_unstemmed Modeling and forecasting customer demands
title_sort modeling and forecasting customer demands
publishDate 2011
url http://hdl.handle.net/10356/45011
_version_ 1772829010896617472