Aspects Regarding Knowledge-based Engineering
DANIELA GHELASE, LUIZA DASCHIEVICI
Faculty of Engineering, Braila,
Dunarea de Jos University,
47, Domneasca St., Galati,
ROMANIA
Abstract: Knowledge management (KM) has become an effective way of managing organization’s
intellectual capital or, in other words, organization’s full experience, skills and knowledge that is relevant for
more effective performance in future. The paper proposes a knowledge management to achieve a competitive
control of the machining systems. Then an application of Knowledge Management in engineering has been
attempted to explain. The model can be used by the manager for the choosing of competitive orders.
Key-Words: - knowledge management, mechanical engineering, information technology, machining system,
marketing knowledge, competitive management.
Received: April 2, 2022. Revised: January 6, 2023. Accepted: February 9, 2023. Published: March 22, 2023.
1 Introduction
The market dynamics is further passed to the mode
of operation and management. In a knowledge-
based society and economy, operations such as
determining the relevant information and
aggregating them into pieces of knowledge must be
automated, because in such a complex and
unpredictable environment, they are indispensable
tools for creating, searching and structuring
knowledge.
The interaction between the economic
environment and the manufacturing system is a
major source of knowledge about the economic
environment and the manufacturing system
themselves [14]. Consequently, it is necessary to
exist a knowledge management system to avoid
increased costs, waste of time and increassed
errors.
The recognition of the Knowledge Management
(KM) imperative will provide an impetus for
enterprise to understand and nurture their
knowledge resources and activities.
KM has assumed a broad range of meanings
from its inception; however, most of the published
material remains ambiguous and provides little
empirical evidence to support a specific definition
for the knowledge management concept. KM has
been acknowledged as being important to
competitive advantage and organizational progress.
Thus, a clear understanding and agreement
about KM should prove to be of great value for
enterprises. As enterprises strive to create a
competitive advantage with their products and
services, they continue to contemplate the KM
concept and the impact on organizational
success.
In a effort to define KM, enterprises must
determine which corporate knowledge should be
harvested organized, managed and shared.
A general definition has been ‘getting the right
information to the right people at the right time’ in
order for them to make better decisions.
Knowledge management implementation is an
advantage for the enterprise from viewpoint of the
competitiveness. The new knowledge will be used
both in the enterprise management and to develop
new products and new services or make important
changes in the business decisions.
By means of learning, the enterprise which uses
the knowledge able to adapt and respond
continuously to the changes of the business
environment.
An important goal of KM is seen to be the
sharing of best practice. So, by the improving the
flow of knowledge through the enterprise can be
obtained the following benefits:
- the sharing of the best practice around business
processes;
- the ability to respond more effectively to
customer demands.
Due to technology facilitates the rapid exchange
of information, the pace of acquisition is growing
exponentially in both large and small enterprises.
The vast amounts of knowledge possessed by the
enterprises are spread across countless structured
and unstructured sources.
To improve processes and bring new products to
the market faster and more cheaply, the enterprises
have to identify, make available and apply this
knowledge.
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
57
Volume 22, 2023
Thus, information must be understood, organized
and transformed for problems solving.
Consequently, information transformed in product
is knowledge and coordination of this kind of
knowledge is made by means of knowledge
management.
As shown above, the manufacturing industry
faces the challenge of responding quickly to the
ever-changing requirements of customers. It is
necessary that in these high competitive
environments, enterprises to control production
system dynamics of such as:
- change in the product types and variants;
- change in the production quantities.
Enterprises have to develop and implement more
responsive and flexible manufacturing systems
based on knowledge. By this way, they can respond
to outgoing and difficult to predict change in
production requirements and make products with
high quality, low cost and fast delivery.
Paper has the following structure: section 2
presents related literature, section 3 explains
knowledge management in engineering, section 4
contains a case study and section 5 summarizes the
main conclusions achieved.
2 Related Literature
The paper is related to several strands of literature.
To be competitive organizations should react
adequately, interpret non-standardized information
for problem solving and decision making, as well
as change their infrastructure and management
strategies [8]. Usually there are a lot of information
and knowledge within organizations, but at the
same time many of them (service organizations, in
particular) are “information rich and knowledge
poor.” The information and knowledge assets, often
called an “intellectual capital,” i.e., knowledge that
can be converted into value, make a great potential
for organizations if utilized well [1].
Knowledge management (KM) has become an
effective way of managing organization’s
intellectual capital or, in other words,
organization’s full experience, skills and
knowledge that is relevant for more effective
performance in future.
Studies in KM mainly focus on organizational
knowledge captured in corporate and/or
organizational memories [2], [9], [19] and on the
development of knowledge management systems
(KMS). However these initiatives in organizations
have often run into difficulties mainly because the
expansion of individual’s personal tacit knowledge
to knowledge of organization as a whole causes
implementation problems.
In the paper [8] there are defined tacit knowledge
and explicit knowledge. Tacit knowledge is
personal knowledge gained through experience. It
may be shared and exchanged through direct
communication with others. Explicit knowledge is
represented in documents, emails, knowledge
repositories (data and knowledge bases), etc.
Explicit knowledge can be formalized in words and
numbers and it is easy distributed and shared.
Acquisition of explicit knowledge is indirect
because it must be encoded and decoded in one’s
mental models where it is kept as tacit knowledge.
In [11] it is shown that the concept of managing
knowledge has become increasingly popular both
in the practical and in the academic discussion in
the fields of engineering and management.
Successful management of knowledge-related
resources of companies has been recognized as a
key basis for acquiring competitive advantage and
other organizational success and the acquisition and
application of knowledge has even been argued to
constitute the focal role of organizations in the
society [4].
The paper [13] is concerned with a application of
knowledge management on the mechatronic
system. The Internet –based CNC machining center
has been considered and its knowledge
management model has been prepared. The model
prepared has been analyzed for machining
performance of the manufacturing system.
The architecture of KM model of internet – based
mechatronic system is presented in the figure 1.
The system presented in this paper consists of
KM model (PC), mechatronic system (CNC
machining center), user unit (PC, SMS) and data,
information converter unit. KM model consists of
knowledge bank compare, internet and network
connection, commentary and management units.
Operations of CNC Machining Center which is the
main production unit of the system can be
controlled both by the machine tool control panel
and by e-mail, network from distant places. Also,
the machine tool equipped with a lot of sensors so
that the machine tool performance can be
monitored and unexpected conditions can be
controlled.
Motivated by the literature discussed above, this
paper presents a knowledge management structure
of the machining system to provide
competitiveness of the enterprise.
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
58
Volume 22, 2023
3 Knowledge Management in
Engineering
Knowledge-based engineering is an engineering
methodology in which knowledge about the
product, the techniques used in design, analysis,
and manufacturing, is stored in a special product
model [23].
Knowledge discovery in databases (KDD) is the
non-trivial process of identifying valid, novel,
potentially useful, and ultimately understandable
patterns in data.
Fig. 1: System diagram of KM of internet – based mechatronic system
It can acquire implicit and useful knowledge in
large scale datasets, and involves an integration of
multiple disciplines such as statistics, artificial
intelligence, machine learning, pattern recognition,
etc. KDD has had great success in commercial
areas, and has begun to be used in knowledge
acquisition of engineering disciplines.
The overall KDD process includes data selection,
data preprocessing, data transformation, data
mining, interpretation, and evaluation, as shown in
Fig. 2 [21].
Defining data, information and knowledge is
difficult. It is possible to distinguish between data,
information and knowledge on base of external
means or from the perspectives of the user.
In [13] it is shown that, data are considered as raw
facts, information is regarded as an organized set of
data, and knowledge is perceived as meaningful
information.
Data consists of symbols that represent objects,
events, and their properties. Information is data that
has been made useful. Information answers who,
what, where, when, and how many questions.
Information is helpful in deciding what to do, not
how to do it.
Knowledge consists of instructions and know-how.
Knowledge answers how questions. Knowledge is
more than information. Information is data
organized into meaningful patterns. Information is
transformed into knowledge when a person or an
intelligence system reads, understands, interprets
and applies the information to a specific work
function.
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
59
Volume 22, 2023
Fig. 2: The process of knowledge discovery
One person's or one intelligence system's
knowledge can be another person's or intelligence
system's information.
If the information can’t be applied to anything,
it remains just information.
However, a person can take that same
information, understand it and interpret it in the
context of previous experience, and apply to
anything, it is transformed to knowledge [15].
Information is becoming ever more important in
engineering. It is not suitable to use data,
information and knowledge conventionally. That is
there is conceptual confusion. Also, today's
technological products need interaction between
different disciplines.
So the confusion increases more. At the
multidisciplinary engineering system, any
discipline contains some information peculiar to
system. However, most of the information mean
essentially same even if they are expressed in
different terms in different disciplines. Therefore,
the available information must be evaluated,
simplified and transformed into usable form that is
knowledge.
Next, the knowledge is coordinated and
connected with the system. So, a kind of know-
how is acquired for the technological product. This
case is generally based on a model, while it has
special characteristics. An example of machining
system has been analyzed in the following section.
The model produced by technical knowledge
which is acquired by the interaction of data,
information and knowledge, by the coordination
and the application of them on engineering system.
KM model is presented in Fig. 3.
KM is a comprehensive process of knowledge
creation, knowledge validation, knowledge
presentation, knowledge distribution and
knowledge application [15]. When KM model is
applied by the enterprise into its production
process it is obtained increasing competitiveness of
the product in the market.
That is KM model can be used for every stage
of the engineering works such us design,
manufacture, maintenance and repair.
4 Case Study
Let us assume that in market there are more offers
quotations for a certain product. Using
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
60
Volume 22, 2023
reinforcement learning, the information from
market becomes marketing knowledge and they
are compared with the ones from knowledge bank.
After the comparison, knowledge unit send the
technical-economic parameters to the modeling
unit. Also, modeling unit interacts with the
knowledge bank to achieve the machining model.
On basis of generated model, simulations are
made and analyzed in control unit. This unit sends
to the CNC machining system the manufacturing
instructions that satisfy the customer demands in
the competitive conditions of the enterprise.
For example, from the simulations (fig. 4) it can
see what is the maximum profit rate depending on
the cutting speed and the federate of the machining
process.
The control unit sends to the CNC machining
system the manufacturing parameters: cutting
speed v’op, feed rate s, depth of cut t.
On basis of these simulations the manager can
decide if the order is accepted or rejected.
5 Conclusion
Today, information has become more important.
Even data, information and knowledge are often
used as if they have same meaning. This problem
raises difficulties in engineering. It is necessary to
exist a knowledge management system to avoid
increased costs, waste of time and increased errors.
Fig. 4 Maximum profit rate of the manufacturing system
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
61
Volume 22, 2023
Knowledge-based engineering is an
engineering methodology in which knowledge
about the product, the techniques used in design,
analysis, and manufacturing, is stored in a special
product model.
In this paper the model of the knowledge
management of the mechanical engineering was
proposed.
Using and comparing marketing knowledge
with stored and updated ones the machining
model is carried out, analyzed and on its basis are
generated instructions regarding the progress of
the machining process in order to obtain
maximum competitiveness.
By modeling and simulations, the manager can
decide if the order is accepted and control the
machining system to satisfy the customer
demands.
To achieve these objectives, the competitive
management uses the reinforcement learning to
get to know the market and the unsupervised on-
line learning technique to get to know the
machining system.
Note that we propose to give managers a
knowledge management model, so that they can
interact with the economic environment (market).
This knowledge management model represents
a technical-economic model that can be used for
competitive management of the manufacturing
process without requesting experiments and
based on the extraction of the knowledge from the
previous experience.
References:
[1] Apshvalka, D., & Grundspenkis, J., Making
organizations to act more intelligently in the
framework of the organizational knowledge
management system, Scientific proceedings
of Riga Technical University,5th series
computer science, applied computer
systems, Vol. 17, p. 72–82, Riga: RTU
Publishing, 2003.
[2] Brooking, A., Corporate memory: Strategies
for knowledge management, London:
International Thomson Business Press,
1999.
[3] Chen, T., Evaluating the mid-term
competitiveness of a product in a
semiconductor fabrication factory with a
systematic procedure, Computers &
Industrial Engineering, Volume 53, Issue
3, October 2007, p. 499-513.
[4] Dyer, J. H., Nobeoka, K., Creating and
managing a high-performance knowledge-
sharing network: The Toyota case, Strategic
Management Journal, Chichester, 21-2000-
3, p. 345-367.
[5] Epureanu, A., Teodor, V., On-Line
Geometrical Identification of
Reconfigurable Machine Tool Using Virtual
Machining, Publicată în revista
Enformatica, vol. 15, SPANIA, ISBN 975-
00803-4-3, 2006.
[6] Falticeanu C., Managementul intreprinderii
industriale, Ed. Zigotto, Galati, 2007
[7] Gi-Tae Yeo, Roe M. and Dinwoodie, J.,
Evaluating the competitiveness of container
ports in Korea and China Transportation
Research Part A: Policy and Practice, In
Press, Corrected Proof, Available online 14
February, 2008
[8] Grundspenkis, J., Agent based approach for
organization and personal knowledge
modelling: knowledge management
perspective, J Intell Manuf 18, p. 451-457,
2007
[9] Grundspenkis, J., Concepts of
organizations, intelligent agents,
knowledge, learning and memories:
Towards an inter-disciplinary knowledge
management, K. Wang, J. Grundspenkis, &
A. Yerofeyev (Eds.), Applied computational
intelligence to engineering and business, p.
172–191, Riga: RTU Publishing, 2001.
[10] H’nida F., Martin P., Vernadat F., Cost
estimation in mechanical production:The
Cost Entity approach applied to integrated
product engineering, International Journal
of Production Economics, 103, 2006, p.17-
35.
[11] Huber, G. P., Organizational learning: The
contributing processes and the literature,
Organization Science, Providence, RI, 2-
1991-1, p. 88-115.
[12] Jin Xue-Jun, Yu Jin-Jin, The effect of
knowledge economy on the management
and labor relations, Journal of Zhejiang
University (Science), V.2, No. 1, p. 114-
118, Jan.-Mar., ISSN 1009-3095, 2001.
[13] Karayel, D., Ozkan, S., Keles, R., General
framework for distributed knowledge
management in mechatronic systems,
Journal of Intelligent Manufacturing, 15, p.
511-515, 2004.
[14] Koren, Y., Ulsoy G., Reconfigurable
manufacturing system having a production
capacity method for designing and method
for changing its production capacity, in
United States Patent, US 6, 349, 237 B1,
2002
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
62
Volume 22, 2023
[15] Lerch, F.J., Harter, D.E., Cognitive support
for real-time dynamic decision making,
Information System Research, 12(1), p. 63-
82, 2001.
[16] Loch, C. H., Chick, S., Huchzermeier, A.,
Can European Manufacturing Companies
Compete?: Industrial Competitiveness,
Employment and Growth in Europe,
European Management Journal, Volume
25, Issue 4, August 2007, p. 251-265.
[17] Rooney, A., Handbook on the knowledge
economy, Cheltenham: Edward Elgar,
ISBN 1843767953, 2005.
[18] Stewart, R.A., IT enhanced project
information management in construction:
Pathways to improved performance and
strategic competitiveness, Automation in
Construction, Volume 16, Issue 4, July
2007, p. 511-517.
[19] Walsh, J. P.,&Ungson, G. R.,
Organizational memory, Academy of
Management Review, 16(1), p. 57–91, 1991.
[20] Wooldridge, J., Introductory Econometries:
A Modern Approach, Mason:Thomson
South-Western, 2003.
[21] Yin J., Li D., Peng Y., Knowledge
acquisition from metal forming simulation,
Int J. Adv. Manuf. Tehnol., 29, p. 279-286,
2006.
WSEAS TRANSACTIONS on COMPUTERS
DOI: 10.37394/23205.2023.22.6
Daniela Ghelase, Luiza Daschievici
E-ISSN: 2224-2872
63
Volume 22, 2023
Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed in the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare
that are relevant to the content of this article.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en
_US
