About this paper

Appears in:
Pages: 4593-4599
Publication year: 2014
ISBN: 978-84-617-2484-0
ISSN: 2340-1095

Conference name: 7th International Conference of Education, Research and Innovation
Dates: 17-19 November, 2014
Location: Seville, Spain

WORKSHOP DESIGN TO IMPROVE STUDENTS PRODUCTION PLANNING SKILLS IN A CHEMICAL ENGINEERING DEGREE

J.R. Trapero Arenas1, F.J. Fernandez Morales1, R. Miranda2

1University of Castilla-La Mancha (SPAIN)
2Complutense University of Madrid (SPAIN)
Demand forecasting is a topic of paramount importance in order to reduce inventory costs and maximize client service level. Typically, this function is accomplished by means of a Forecasting Support System (FSS), which integrates a statistical tool with judgemental adjusted forecasts introduced by managers. In principle, the forecast employed by the company is the result of two sources of information. On the one hand, the FSS provides a statistical forecast, known as either system forecast or baseline forecast. Usually, this forecast comes from a univariate statistical tool as the exponential smoothing. On the other hand, several meetings are arranged among the managers that use such forecasts (production, finance and marketing staff) to agree a final forecast by modifying the baseline forecast. The reason of this adjustment is to incorporate key information that it is very difficult to include in a statistical model. The aim of this work is to design a workshop that reproduced this kind of decisions to train students in planning production skills. It should be noted that traditional books in business administration do not usually implement tools that allow students to integrate judgemental opinions and statistical forecasts. Actually, most of the fundamental bibliography just rely on basic statistical tools to introduce the area of demand planning.

The workshop will utilize the data collected from a real chemical company. Therefore, the first objective of this work is to employ an Excel sheet to implement the statistical forecasting algorithm, in our case study it will be an exponential smoothing on the basis of the company past sales. Secondly, the forecasts implemented by students will be compared to the forecasts made by the company managers. Lastly, after analysing potential discrepancies between student and managers responses, a final model that combines statistical and judgmental forecasts will be implemented as well to have a set of forecasts that minimize the company inventory costs.
@InProceedings{TRAPEROARENAS2014WOR,
author = {Trapero Arenas, J.R. and Fernandez Morales, F.J. and Miranda, R.},
title = {WORKSHOP DESIGN TO IMPROVE STUDENTS PRODUCTION PLANNING SKILLS IN A CHEMICAL ENGINEERING DEGREE},
series = {7th International Conference of Education, Research and Innovation},
booktitle = {ICERI2014 Proceedings},
isbn = {978-84-617-2484-0},
issn = {2340-1095},
publisher = {IATED},
location = {Seville, Spain},
month = {17-19 November, 2014},
year = {2014},
pages = {4593-4599}}
TY - CONF
AU - J.R. Trapero Arenas AU - F.J. Fernandez Morales AU - R. Miranda
TI - WORKSHOP DESIGN TO IMPROVE STUDENTS PRODUCTION PLANNING SKILLS IN A CHEMICAL ENGINEERING DEGREE
SN - 978-84-617-2484-0/2340-1095
PY - 2014
Y1 - 17-19 November, 2014
CI - Seville, Spain
JO - 7th International Conference of Education, Research and Innovation
JA - ICERI2014 Proceedings
SP - 4593
EP - 4599
ER -
J.R. Trapero Arenas, F.J. Fernandez Morales, R. Miranda (2014) WORKSHOP DESIGN TO IMPROVE STUDENTS PRODUCTION PLANNING SKILLS IN A CHEMICAL ENGINEERING DEGREE, ICERI2014 Proceedings, pp. 4593-4599.
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