Engineering information modeling in databases: needs and constructions
| DOI | https://doi.org/10.1108/02635570510616102 |
| Date | 01 September 2005 |
| Pages | 900-918 |
| Published date | 01 September 2005 |
| Author | Z.M. Ma |
| Subject Matter | Economics,Information & knowledge management,Management science & operations |
Engineering information
modeling in databases:
needs and constructions
Z.M. Ma
Department of Computer Science and Engineering, Northeastern University,
Shenyang, Liaoning, People’s Republic of China
Abstract
Purpose – To provide a selective bibliography for researchers and practitioners interested in
database modeling of engineering information with sources which can help them develop engineering
information systems.
Design/methodology/approach – Identifies the requirements for engineering information
modeling and then investigates how current database models satisfy these requirements at two
levels: conceptual data models and logical database models.
Findings – Presents the relationships among the conceptual data models and the logical database
models for engineering information modeling viewed from database conceptual design.
Originality/value – Currently few papers provide comprehensive discussions about how current
engineering information modeling can be supported by database technologies. This paper fills this
gap. The contribution of the paper is to identify the direction of database study viewed from
engineering applications and provide a guidance of information modeling for engineering design,
manufacturing, and production management.
Keywords Database managementsystems, Modelling, Industrialengineering
Paper type Research paper
1. Introduction
To increase product competitiveness, current manufacturing enterprises have to
deliver their products at reduced cost and high quality in a short time. The change
from sellers’ market to buyers’ market results in a steady decrease in the product life
cycle time and the demands for tailor-made and small-batch products. All these
changes require that manufacturing enterprises quickly respond to market changes.
Traditional production patterns and manufacturing technologies may find it difficult
to satisfy the requirements of current product development. Many types of advanced
manufacturing tech niques, such as compu ter integrated manuf acturing, agile
manufacturing, concurrent engineering, and virtual enterprise based on global
manufacturing have been proposed to meet these requirements. One of the
foundational supporting strategies is the computer-based information technology.
Information systems have become the nerve center of current manufacturing systems.
So some new requirements on information modeling are introduced.
Database systems are the key to implementing information modeling. Engineering
information modeling requires database support. Engineering applications, however,
are data and knowledge intensive applications. Some unique characteristics and usage
of new technologies have put many potential requirements on engineering information
modeling, which challenge today’s database systems and promote their evolvement.
Database systems have gone through the development from hierarchical and network
The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at
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IMDS
105,7
900
Industrial Management & Data
Systems
Vol. 105 No. 7, 2005
pp. 900-918
qEmerald Group Publishing Limited
0263-5577
DOI 10.1108/02635570510616102
databases to relational databases. But in non-transaction processing such as
CAD/CAM, knowledge-based system, multimedia and internet systems, most of these
data intensive application systems suffer from the same limitations of relational
databases. Therefore, some non-traditional data models have been proposed. These
data models are fundamental tools for modeling databases or the potential database
models. Incorporation between additional semantics and data models has been a major
goal for database research and development.
Focusing on engineering applications of databases, in this paper, we identify the
requirements for engineering information modeling and investigate the satisfactions of
current database models to these requirements. Here we differentiate two levels of
database models: conceptual data models and logical database models. Constructions
of database models for engineering information modeling are hereby proposed.
The remainder of the paper is organized as follows. Section 2 identifies the ge neric
requirements of engineering information modeling. The issues that current databases
satisfy these requirements are investigated in Section 3. Section 4 proposes the
constructions of database models. Section 5 concludes this paper.
2. Needs for engineering information modeling
2.1 Complex objects and relationships
Engineering data have complex structure and are usually large in volume. Engineering
design objects and their components are not independent. They are generally organized
into taxonomical hierarchies. The specialization association is the well-known
association. Also the part-whole association, which relates components to the
compound of which they are part, is another key association in engineering settings.
Typically product modeling for product family and product variants has resulted in
product data models, which define the form and content of product data generated
through the product life cycle from specification through design to manufacturing.
Products are generally complex (Figure 1 shows a simple example of product structure)
and product data models should hereby have advanced modeling abilities for
unstructured objects, relationships, abstractions, and so on (Shaw et al., 1989).
2.2 Data exchange and share
Engineering activities are generally performed across departmental and organization
boundaries. Product development based on virtual enterprises, for example, is
performed by several independent member companies that are physically located at
Figure 1.
An example illustration of
product structure
Engineering
information
modeling
901
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