IT CAPACITY FORECASTING: STATISTICAL MODELLING PROCESS AND
APPLICATIONS FOR SEMICONDUCTOR INDUSTRY.
M. Lutz* **. X. Boucher.*
O. Roustant*. X. Ambrosioni**
*ENSMSE-G2I, 158 cours Fauriel, 42100 Saint Etienne, France
(Tel: + 33-4-38 92-21-98; e-mail: lutz@emse.fr).
** STMicroelectronics, Crolles, France
Abstract: The objective of this paper is to present a modeling procedure, based on the use of statistical
methods, to develop predictive models for Information Technology (IT) capacity planning. The goal of
these models is to be able to SUHGLFW ,7 YDULDEOHV¶ EHKDYLRXU, using initial inputs provided by high-level
business explanatory variables. The modelling process consists in two main sequences, exploration and
explanation, divided into modelling steps, which mix qualitative and quantitative analyses. The
modelling process builds a progressive understanding of relationships among the different levels of the
IT architecture. The final outcome is a statistical model, linking IT resource utilization to manufacturing
activities variables. An application of the modelling process is developed in the context of the
STMicroelectronics information system. As a result, two predictive models which focus on subsystems of
the whole information system, link the physical seUYHUV¶ GDLO\ use to manufacturing variables such as
level of production, manufacturing processes deployment and fabrication throughput.
Keywords: information system, IT capacity planning, statistical analysis, semiconductor industry
1. INTRODUCTION AND RESEARCH
BACKGROUND
An Information System is a critical factor when bettering
modern manufacturing systems efficiency (Cardinali, 1992;
Gowan and Mathieu, 1996). This is notably true within the
current application field: semiconductor industry (Leachman
and HRGJHV ,QIRUPDWLRQ 6\VWHP¶V HIILFLHQF\ LWVHOI LV
based on an adequate specification of firms¶ Information
Technologies (IT) architectures (Earl, 1989). Consequently,
IT managers must basically anticipate to provide without
interruption enough IT resRXUFHV WR VXSSRUW ILUP¶V RSHUDWLRQV
plans and forecasts so that they function without interruption
(Kloesterboer, 2011).
Therefore, quantitative IT capacity models are of great
LQWHUHVW WR VXSSRUW ,7 PDQDJHUV¶ GHFLVLRQ SURFHVVes. The ITIL
(Information Technology Infrastructure Library) framework
recommends three main approaches for IT capacity
modelling: analytical & simulation modelling and as well as
trend analysis (Kloesterboer, 2011). The purpose of such
models is to quantify the level of IT resources needed for a
given level of workload, forecasted by IT managers on the
basis of hypothetical scenarios (Jain, 1991; Gunther, 2007).
However, usual IT capacity planning studies in the field of
computer systems engineering are still struggling to build
such models, with an operational link to high-level business
or industrial variables. For instance, in a recent publication it
was stated³You may not be able to make a direct correlation
between the business trends and your IT capacity, but you
should at least look at whatever your organization publishes
and see how it compare your component and service trends´
(Kloesterboer, 2011). The purpose of our paper is to present
an answer to such a limitation. Indeed, we intend to
demonstrate that 1) links between IT resources and high-level
industrial activities (here silicon wafer manufacture) can be
established; 2) a structured modelling process can formalize
rigorously such links.
This paper presents some results of PhD research in
collaboration with the Crolles 300 IT Department of the
company STMicroelectronics. From an industrial perspective,
the objective is to build a model with good predictive
features, based on the link among IT resources variables and
high-level industrial variables. The impact of such model
would be not only to ease communication among IT and
production managers but also to compare and analyse IT
capacity hypothetical scenarios, based on industrial input
variables. Academically, many research papers deal with the
link between semiconductor manufacturing and production
equipment capacity (Geng and Jiang, 2009). However, to the
best of our knowledge, few if any publications link
semiconductor manufacturing system activity to the capacity
of its IT architecture. More generally, it can be observed that
IT capacity planning has little been explored by industrial
engineering as of yet. The results presented in this paper only
constitute an important initial step for much further research.
The final objective will be to completely design a decision-
making tool, which will encompass the use of quantitative
models in a wider industrial scope. However, this decision
tool is not the purpose of this paper and will be addressed in
future publications. The focus of the paper is to present the
modelling process used to build the quantitative models that
will be required.
Proceedings of the 14th IFAC Symposium on
Information Control Problems in Manufacturing
Bucharest, Romania, May 23-25, 2012
978-3-902661-98-2/12/$20.00 © 2012 IFAC
1568
10.3182/20120523-3-RO-2023.00043