Ontological Framework for Integrating Environmental Issues within
Sustainable Enterprise
Enhancing Enterprise Decision-making
Edrisi Muñoz
, Elisabet Capón
, José M. Laínez
, Antonio Espuña
and Luis Puigjaner
Centro de Investigación en Matemáticas, Jalisco S/N, 36240, Guanajuato, Mexico
Institute for Chemical and Bioengineering, ETH Zürich, 8093 Zürich, Switzerland
School of Chemical Engineering, Purdue University, West Lafayette, IN, U.S.A.
Department of Chemical Engineering, Universitat Politècnica de Catalunya, Av. Diagonal, 647, E08028 Barcelona, Spain
Environmental modeling, Ontology Reuse, Enterprise Model, Decision Support Systems, Ontology Frame-
Ontologies stand for an excellent choice for building complex models while allowing a high level of flexibil-
ity, re-usability, usability and easiness of maintenance. This work proposes the re-use of an ontological model
for the integrated enterprise in order to include the environmental assessment function. Since enterprises are
complex systems involving different functionalities, decision-making becomes a highly challenging task, and
decision process is usually separated in several levels. Nevertheless, such levels are closely related by the
sharing of data and information. Therefore, effective integration among the different hierarchical levels, by
means of tools which improve information sharing and communication, may play a crucial role for the en-
hanced enterprise operation, and consequently for fulfilling the enterprise’s goals. The ontological framework
provides a common modeling framework which facilitates integration among the different decision levels,
and works as the mechanism for supporting information and knowledge sharing among multiple applications.
The general semantic framework developed is applied to a case study comprising an enterprise supply chain
network design-planning problem which considers environmental issues.
Currently, enterprises face stricter regulations related
to safety and environmental issues, new processes and
materials, and an increasing degree of uncertainty in
global economics. Even more, companies pursue to
create value in a more sustainable way to fulfill their
operations and goals, which implies properly harmo-
nizing profitability and natural resources and energy
consumption (Grossmann, 2004). Therefore, it is nec-
essary to develop and use approaches and tools ca-
pable of analyzing and understanding the processes’
effects on the environment. To succeed in reaching
such a balance, environmental performance must be
integrated into the business strategy and development.
Enterprises are highly complex systems which
consist of multiple business and process units geo-
graphically distributed and also with different scales
working together. The simultaneous inclusion of eco-
nomic and environmental concerns within enterprise
structures requires high flexible modeling systems,
capable of integrating the different scales and levels
of the organization. The integration of operations and
environmentaldata is one of the problems faced when
developing environmental decision support systems.
This paper proposes the reuse of an existing se-
mantic model in order to consider the addition of the
environmental system representation within the dif-
ferent supply chain decision levels, namely the life
cycle assessment. In order to carry out such a data
integration as well as to understand, analyze, syn-
chronize and ultimately improve the design and oper-
ation of complex flexible production systems we be-
lieve that a promising avenue is to represent the whole
system in an adequate ontological model, which cap-
tures the environmental and operational features rel-
evant for managers to support decision making pro-
cesses. Specifically, the integrated enterprise ontol-
ogy project by (Muñoz et al., 2011), which repre-
sents an integrated enterprise framework is reused.
Thus, this work exploits the link between transac-
tional and analytical systems and semantic and quan-
Muñoz E., Capón E., Laínez J., Espuña A. and Puigjaner L..
Ontological Framework for Integrating Environmental Issues within Sustainable Enterprise - Enhancing Enterprise Decision-making.
DOI: 10.5220/0004141103850388
In Proceedings of the International Conference on Knowledge Engineering and Ontology Development (KEOD-2012), pages 385-388
ISBN: 978-989-8565-30-3
2012 SCITEPRESS (Science and Technology Publications, Lda.)
titative models to propose sustainable solutions for
the design and operation of supply chains.
On the application of knowledge representation to
environmental issues, (Kraines et al., 2006) present
a framework for expert knowledge sharing and dis-
covery for integrated environmental assessment of
technologies and processes associated with industrial
ecology. A Life Cycle Assessment Ontology has been
proposed by (Brascher et al., 2007), including the do-
main represented by the ISO 14040 resulting in an
ontology containing the four phases of the LCA.
The proposed ontology supports different activities
by streamlining information and data integration by
means of an integrated model which captures the ac-
tivities developed along the different levels of the en-
terprise structure resulting in an integrated decision
making framework. The ontology provides the shared
and common domain structures required for the se-
mantic integration of information sources, resulting
in a competitive advantage.
Thus, the developed ontology adopts as base
model a previous enterprise conceptualization pre-
sented by (Muñoz et al., 2011) which supports and
integrates the different hierarchical enterprise levels.
The reuse of this model allows an automatic incorpo-
ration of the previous domain, providing the shared
and common structures required for the semantic in-
tegration of information sources. What is more, when
a previous model is reused, there is a chance of im-
provement, since a new revision of the area is carried
out and a new part of a specific area or a new spec-
ification is included. In this paper, additional model
classes, properties and axioms have been developed
to include the environmental functionalities. As a re-
sult, the environmental assessment model is described
and integrated with the enterprise model. Extended
reference of the integrated enterprise ontology can be
found in the original paper by (Muñoz et al., 2011).
2.1 Domain Definition
On the one hand, the domain of the ontology com-
prises the whole enterprise entity, including those ac-
tivities related to the operational, tactical and strate-
gic levels. Specifically, the conceptualization and
management of operational concepts (physical mod-
els, procedures, functions and processes) is based on
ANSI/ISA-88 and ANSI/ISA-95 (for Measurement
and Control, 2007) process standard, which catego-
rize and examine the relationships among them. On
the other hand, the environmental domain is rep-
resented based on the life-cycle assessment (LCA)
methodology standardized in the ISO 1404X series
(ISO14001, 2004) for setting an environmental man-
agement system (EMS).
2.2 Methodology
The methodology adopted in this work regarding
the ontology development consists of the continuous
improvement cycle using PDCA (Plan, Do(Study),
Check and Act) and replanning phases, as presented
in (Muñoz et al., 2011). This methodology encom-
passes the steps proposed by two existing methodolo-
gies, namely "Methontology" (López et al., 1999) and
“On-To-Knowledge” (Sure and Studer, 2002). The
former methodology supports the entire life-cycle of
ontology development, whereas the latter allows to
present knowledge efficiently and effectively by the
analysis of usage scenarios. Since the new ontologi-
cal model is based on a previous one (Muñoz et al.,
2011), the result of the re-planning and revisiting of
the different phases in the PDCA cycle is presented
Plan Phase. This stage captures the new require-
ments and specifications regarding the environ-
mental management domain, and next adequately
documenting them. The possible knowledge
sources are defined for expanding the original do-
main. Basically, the environmental domain re-
lies on definitions used by internationally recog-
nized organizations, environmental agencies and
research reports from the literature (Garrido and
Requena, 2011; Bojarski, 2010).
Do Phase. At this stage, the principal components
of the conceptualization model related to the en-
vironmental domain are established. Glossary
of terms, concepts and properties, hierarchies,
the taxonomy, class and instant attributes are de-
scribed. Thus, the equivalence between the terms
in the environmental assessment model and the
enterprise ontology model must be established.
The formalization of all the contents should agree
with the knowledge sources. Next, the model of
the ontology is formalized considering the previ-
ous information.
In this case, the OWL ontology editors used have
been Protégé as main editor and Swoop as com-
plementary editor, being both freeware and also
robust softwares.
Check Phase. In this stage, the language and the
conceptuality are checked in order to standard-
ize them with the support of expertise and ex-
perts. The reasoning of the ontological model is
done, which is one of the most important tasks.
Additionally, a short informatics application has
been developed in order to test the ontology in the
main application environment. Common defects
include inconsistent ontologies and unsatisfiable
concepts. In this work the RacerPro reasoner from
Protégé and Pallet reasoner from Swoop were
used as reasoners for testing the ontology.
Act Phase. Having found defects in the ontology,
their resolution can be non-trivial, requiring an
exploration of remedies with a cost/benefit anal-
ysis. In this case, one would like to generate re-
pair solutions that impact the ontology minimally.
Particular care and effort must be taken to ensure
that ontology repair is carried out efficiently. The
necessary documentation of the implementation is
fulfilled for the maintenance ontology task.
2.3 Models Usability
In order to exploit the full potential of the ontologi-
cal model for connecting transactional and analytical
systems, Java has been used as a high-level program-
ming language, because it provides a good versatility,
efficiency and security. The code was built using the
platform NetBeans IDE 7.0.
The application of the ontological model for the
environmental performance assessment takes place
within the different enterprise decision layers, which
are integrated by means of the enterprise ontology
project. In this particular work, decision-making con-
cerns the operational and strategic levels.
The operation of the framework consists of re-
trieving the environmental mid-point categories re-
lated to the functional units and elements in the LCA
assessment by querying the environmental database
using the Java code, the values for the ontologies in-
stances that require environmental assessment. Once
such values are obtained, they are stored in the on-
tology. Next, when the optimization model needs the
data for formulating the problem, such information is
retrieved from the ontology as well.
The dimension of the final ontological model con-
sists of 276 classes, 67 restrictions, and 224 object
properties stemming from the enterprise model itself,
and 108 classes, 34 restrictions, and 74 object prop-
erties characterizing the environmental management
domain. These components make the ontology rea-
soning and its use possible. The reasoning time for
the consistency of the model and classes is 1.062
and 0.281 CPU s respectively in an Intel-Core 2 at
2.83GHz in a successful compilation.
The analytical systems for taking decisions are
based on mathematical optimization, specifically the
centralized approach to supply chain design and plan-
ning presented by (Laínez et al., 2009) and the STN-
formulation (Maravelias and Grossmann, 2003) to
production scheduling are considered in this work.
The case studies are based on a supply chain network
design-planning problem presented by (Laínez et al.,
2009). It consists of three suppliers, four potential
locations for the processing sites and the distribution
centers in a planning horizon of five annual periods.
The production process fulfills the demand of six mar-
kets that entails two final products and one intermedi-
ate product.
The strategic analytical optimization model pre-
sented by (Laínez et al., 2009) also includes an LCA
formulation that computes the mid-point and end-
point impact categories based on the production and
distribution activities that are performed to optimally
satisfy the demand. Qualitatively speaking, the prob-
lem representation in the proposed ontological frame-
work results in 761 instances. The reasoning time for
the problem instances is 0.688 CPU s in a successful
It is important to mention that each possible site
is fully represented in the ontology. Each produc-
tion plant (site) may contain a set of four equipment
technologies as presented by (Kondili et al., 1993), a
benchmark problem for the scheduling of batch pro-
cess industries. The production process consist of five
production tasks and nine states, namely three raw
materials, two final products and four intermediates.
Specifically, each site is described by 111 instances,
which may be adequately used to take operational de-
cisions. Precisely, the scheduling optimization model
has been adapted to also consider decisions related to
environmental considerations of the plant.
The analytical optimization model must be pro-
vided with the necessary information, which is de-
rived from the ontological model and the related data
contained in the database. Additionally, the ontologi-
cal model optimizes the way in which the databases
are distributed along the enterprise structure. As a
result, databases are well located and their data are
easily available and can be transformed into valuable
In order to generate the required inputs for the
optimization model which has been implemented in
GAMS and solved using the MILP solver CPLEX 9.0,
the Java application is used. Such code generates the
.txt files which are called by the optimization prob-
The results of the optimization model are identical
to those reported in the original paper. Furthermore,
the previous results can be dated back to the ontolog-
ical model for further exploitation by the other de-
cision levels, such as the operational system of each
site. This can be achieved by automatically updating
the databases with the resulting optimization data.
This ontology enhances the way for achieving a suc-
cessful enterprise decision making supporting tool
which adapts and recognizes the different elements
found through the hierarchy models that are associ-
ated with the whole supply chain and allows to assess
the environmental performance of the enterprises by
communicating to environmental life cycle databases
and to analytical models.
Moreover, a general semantic framework is pro-
posed, which is able to model any enterprise partic-
ular case and its environmental implications, prov-
ing its re-usability. Furthermore, it has been proved
the ontology usability by its application to an opti-
mization framework. As a whole, the main contri-
butions of this framework and the model behind are
re-usability, usability, higher efficiency in communi-
cation and coordination procedures within the enter-
prise in order to assess its environmental issues.
This work represents a step forward to support
the integration, not just communication, of different
software tools applicable to the management and ex-
ploitation of plant database information, resulting into
an enhancement of the entire process management
structure for aiding the automatic design and opera-
tion of more sustainable enterprises.
Further work is underway to unveil the full poten-
tial to implement a large-scale semantic web approach
to support business processes decisions in a sustain-
able enterprise.
Financial support received from CIMAT México is
fully acknowledged. In addition, financial support
provided by research Project EHMAN (DPI2009-
09386) funded by the European Union (European Re-
gional Development Fund ERDF) and the Spanish
"Ministerio de Ciencia e Innovación" is fully appre-
Bojarski, A. (2010). Life cycle thinking and general mod-
elling contribution to chemical process sustainable
design and operation. PhD thesis, Universitat Politèc-
nica de Catalunya.
Brascher, M., Monteiro, F., and Silva, A. (2007). Life cycle
assessment ontology. In ISKO, editor, Proceedings
of the 8th Conference of the International Society for
Knowledge Organization, pages 169 – 177.
for Measurement, I. S. and Control (2007). Isa-88/95 tech-
nical report: Using isa-88 and isa-95 together. Tech-
nical report, ISA The Instrumentation, Systems, and
Automation Society.
Garrido, J. and Requena, I. (2011). Proposal of ontology
for environmental impact assessment: An application
with knowledge mobilization. Expert Systems with
Applications, 38:2462 – 2472.
Grossmann, I. E. (2004). Challenges in the new millen-
nium: product discovery and design, enterprise and
supply chain optimization, global life cycle assess-
ment. Computers & Chemical Engineering, 29(1):29–
ISO14001 (2004). Environmental management systems -
requirements with guidance for use. Technical report,
Kondili, E., Pantelides, C., and Sargent, R. (1993). A
general algorithm for short-term scheduling of batch
operations–i. milp formulation. Computers & Chemi-
cal Engineering, 17(2):211 – 227.
Kraines, S., Batres, R., Kemper, B., Michihisa, K., and
Wolowski, V. (2006). Internet-based integrated en-
vironmental assessment, part ii: Semantic searching
based on ontologies and agent systems for knowledge
discovery. Journal of Industrial Ecology, 10:37 – 60.
Laínez, J. M., Kopanos, G., Espuña, A., and Puigjaner, L.
(2009). Flexible design-planning of supply chain net-
works. AIChE Journal, 55(7):1736–1753.
López, M. F., Gómez-Pérez, A., Sierra, J. P., and Sierra,
A. P. (1999). Building a chemical ontology using
methontology and the ontology design environment.
IEEE Intelligent Systems, 14(1):37–46.
Maravelias, C. T. and Grossmann, I. E. (2003). New
general continuous-time state-task network formula-
tion for short-term scheduling of multipurpose batch
plants. Industrial & Engineering Chemistry Research,
Muñoz, E., Capon-Garcia, E., Lainez, J., Espuña, A., and
Puigjaner, L. (2011). Ontological framework for the
enterprise from a process perspective. In SciTePress,
editor, Proceedings of the International Conference
on Knowledge Engineering and Ontology Develop-
ment, pages 538 – 546.
Sure, Y. and Studer, R. (2002). On-to-knowledge method-
ology. Technical report, University of Karlsruhe.