=Paper=
{{Paper
|id=Vol-2030/HAICTA_2017_paper72
|storemode=property
|title=A Fuzzy Multiple Criteria Approach for Environmental Performance Evaluation in the Food Industry
|pdfUrl=https://ceur-ws.org/Vol-2030/HAICTA_2017_paper72.pdf
|volume=Vol-2030
|authors=Evangelos Grigoroudis
|dblpUrl=https://dblp.org/rec/conf/haicta/Grigoroudis17
}}
==A Fuzzy Multiple Criteria Approach for Environmental Performance Evaluation in the Food Industry==
https://ceur-ws.org/Vol-2030/HAICTA_2017_paper72.pdf
A fuzzy multiple criteria approach for environmental
performance evaluation in the food industry
Evangelos Grigoroudis1
1
School of Production Engineering and Management, Technical University of Crete, Chania,
Greece, e-mail: vangelis@ergasya.tuc.gr
Abstract. An important tool for the evaluation and documentation of a
successful environmental management system is the Environmental
Performance Evaluation (EPE). EPE is generally defined as a continuous
internal process and management tool that using indicators evaluates the
environmental management system of an organization and compares past and
present performance. Relevant international standards such as ISO 14031-
14032 describe the categories of performance indicators; however they do not
determine a specific framework for the development, measurement and
evaluation of these indicators. The main aim of this study is to present an EPE
methodology based on the fuzzy UTASTAR method. Fuzzy UTASTAR is an
extension of the well-known UTASTAR method capable to handle both
ordinary (crisp) and fuzzy evaluation data. To demonstrate the application of
the methodology, a case study is presented, where fuzzy UTASTAR is used in
the frame of the EPE of a mills industry.
Keywords: Fuzzy UTASTAR, Environmental Performance Evaluation,
Environmental Performance Indicators, Environmental Management Systems.
1 Introduction
Environmental concerns present a high and constantly increasing trend with the
responsibility for its protection to lie not only to public authorities but also to
companies and organizations in general. Irrespective of their size and type of activity,
organizations are nowadays urged by their customers to offer products and services,
which not only comply with their expectations with respect to use, but are also
friendly to the environment. The environmental profile has emerged as a powerful
communication tool, and its importance for all internal and external parts that
comprise the environment of an organization increases continuously. Industry, in
particular, which is responsible for a large part of the pollution and depletion of
natural resources and energy, is called to modify its public image by increasing its
sensitivity to environment-related issues. To this end and in order to clearly
demonstrate their engagement to environmental-friendly policies and respective
activities, organizations are nowadays developing, adopting and maintaining
Environmental Management Systems (EMSs).
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EMSs offer multiple benefits to organizations as, beyond environmental
protection, they cover issues such as compliance to legislation and formal
regulations, prediction of future corrective actions, productivity increase, safety,
employee protection and satisfaction, estimation of required costs and reduction of
operational costs, and promotion of an improved organization image.
As part of their EMS, some organizations introduce formal procedures aimed at
providing them with reliable data and information so as to enable and easy
management decisions concerning their environmental performance. These
procedures, which are collectively known as Environmental Performance Evaluation
(EPE) assists them in identifying their important environmental aspects and in
defining all necessary actions so as to achieve their environmental objectives and
targets in a continuous basis (Kuhre, 1998).
Despite its widely acknowledged benefits, EPE is neither an easy nor a
straightforward task due to the high level of required effort and resources. And
although ISO has developed a standard, ISO 14031 (International Organization for
Standardization, 1999, 2004), specifically aimed at assisting organizations in this
difficult endeavor, EPE still remains an optional task.
The application of the UTA methods in environmental management problems is
rather limited and it is mainly focused on landfill selection, wastewater treatment
evaluation or transportation planning (Siskos and Assimakopoulos, 1989; Hatzinakos
et al., 1991; Demesouka et al., 2013). The presented work is one of the first research
attempts in applying a multiple criteria preference disaggregation approach in the
context of a systematic EPE process. It is, thus, the aim of this paper to outline the
main principles of the original and fuzzy UTASTAR, and to demonstrate via an
example application to a mills industry the use of fuzzy UTASTAR in the context of
EPE.
Fuzzy UTASTAR, initially proposed by Patiniotakis et al. (2011), is an extension
of the well-known UTASTAR method (Jacquet-Lagrèze and Siskos, 1982; Siskos
and Yannacopoulos, 1985; Siskos et al., 2005) capable to handle both ordinary and
fuzzy data, which allows its user to infer fuzzy value functions from a partial
preorder of options, evaluated against multiple criteria. This property offers to the
decision makers (DMs) much flexibility, which is necessary as it is well-known that
the majority of the real-world decision problems include a high level of uncertainty
that prevents the assignment of accurate evaluations (scores) to the available
alternative options. In case of course that the evaluation data are crisp, the method
behaves exactly as the original UTASTAR method (Patiniotakis et al., 2011).
2 Application and Results
2.1 Environmental performance indicators
To demonstrate the application of the fuzzy UTASTAR approach to EPE, a mill
industry certified according to the ISO 9000 standard for quality management has
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been selected (Sbokou et al., 2014). The company produces a wide range of flour
products for home use, professional, as well as for animal feeding. To this end it uses
cereals like wheat, barley, corn, oats and rye as raw materials, as well as energy and
water.
To conduct the EPE, data has been collected via the ISO 9000 quality manual, an
Environmental Impact Study, several control lists, measurements and fieldwork
within the industry’s premises. Significant information has been also gathered
through communication with the top management, as well as the directors of the
different departments. This approach allowed the identification of the industry’s
environmental policy and goals, environmental aspects, environmental impacts, and
the relevant national and European legislation (Sbokou et al., 2014).
The application of the a risk assessment approach reduced the initial set of 36
indicators to a final set including 17 indicators allocated to 5 different categories as
summarized in Table 1. The first three indicators’ categories concern environmental
emissions, while the last three concern management-operational indicators.
It should be noted that the indicators, which are not included in the final set, may
not be less useful or appropriate for the EPE process. The final set just reflects the
current priorities and interests of the industry and should be regularly reviewed and
updated in the future as part of the continuous improvement of the industry’s EPE
process.
2.2 Development and evaluation of scenarios
In order to apply fuzzy UTASTAR, a reference set should be developed including
alternative scenarios involving different combinations of indicator values that can be
evaluated and prioritized by the industry. For each indicator 3 performance levels
were identified to reflect low, medium and high value. To further define the
reference set for each indicator category, a scenarios development methodology was
used, based in the design of statistical experiments taking into account a subset only
of all possible combinations of indicator values.
Following the aforementioned rationale, reference sets were defined as follows: a)
reference set including 4 scenarios for the indicators’ category air emissions
(includes 3 indicators); b) reference set including 7 scenarios for the indicators’
category solid waste (includes 6 indicators); c) reference set including 3 scenarios for
the indicators’ category resources and energy (includes 2 indicators); d) reference set
including 3 scenarios for the indicators’ category environmental education and third
parties (includes 2 indicators); and e) reference set including 5 scenarios for the
indicators’ category recycling and improvement actions (includes 4 indicators).
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Table 1. The final set of indicators.
Category Indicator Units
Air emissions Quantity of CO2 tn of CO2 / month
Quantity of NOx kg of NOx / month
Quantity of SOx kg of SOx / month
Solid waste Quantity of production process kg of bioproducts /day
biproducts
Quantity of waste from packing of kg of packing materials / month
raw and other materials
Ash quantity kg of ash / month
Percentage of well-managed % of used phosphine packing
phosphine packing disposed via authorized bodies /
month
Percentage of well-managed used % of used batteries disposed via
batteries authorized bodies or returned to
suppliers / month
Percentage of well-managed used % of used oils disposed via
oils authorized bodies / month
Resources and Average water consumption m3 of water / month
energy Noise levels at the production units dB
and the borders of the industry
facilities
Environmental Number of proposals for the Number of proposals / year
education and improvement of environmental
third parties performance
Number of complaints from the local Number of complaints / year
community
Recycling and Number of products or packings with % of products and packings with
improvement clear environmental guidelines for such guidelines
actions use and disposal
Number of emergency exercises Number of emergency exercises
carried out carried out / total number of planned
emergency exercises
Time to respond to and complete Number of days for response and
corrective actions completion of corrective actions /
year
Cost allocated to improvement Environmental-related costs / total
actions and environmental initiatives budget
as part of the total budget
2.3 Fuzzy UTASTAR results
Given the criteria and the reference sets defined for each environmental indicator
category, the fuzzy UTASTART model is applied to provide (fuzzy) marginal and
global value functions.
Table 2 summarizes the performance assessment of the industries’ current
condition using the previous value functions. More specifically, the first and the
second columns list the considered dimensions and the indicators per dimension,
597
respectively. The third column presents the current values of the indicators as
measured/estimated by the industry, while the fourth column shows the value of the
current indicator as estimated (via linear interpolation) using the value functions of
calculated by Fuzzy UTASTAR. The last column presents the same results with the
previous column, which are now normalized in the range [0, 1].
Table 2. Assessment of current industry performance based on fuzzy UTASTAR results.
Category Indicator Current Unweighted Normalized
value value (weighted)
value
Air Quantity of CO2 35 0.080 0.667
emissions Quantity of NOx 75 0.029 0.674
Quantity of SOx 160 0.452 0.540
Overall value of air emissions 0.561
Solid waste Quantity of produced biproducts 3 0.300 0.806
Quantity of waste from packing of raw 25 0.119 0.783
and other materials
Ash quantity 450 0.041 0.225
Percentage of well-managed phosphine 100 0.100 1.000
packing
Percentage of well-managed used 100 0.100 1.000
batteries
Percentage of well-managed used oils 100 0.094 1.000
Overall value of solid waste 0.754
Resources Average water consumption 800 0.077 0.770
and energy Noise levels at the production units 48 0.100 0.111
and the borders of the industry
facilities
Overall value of resources and energy 0.177
Environme Number of proposals for the 1 0.083 0.332
ntal improvement of environmental
education performance
and third Number of complaints from the local 1 0.750 1.000
parties community
Overall value of environmental 0.833
education and third parties
Recycling Number of products or packings with 85 0.100 0.775
and clear environmental guidelines for use
improveme and disposal
nt actions Number of emergency exercises 100 0.250 1.000
carried out
Time to respond to and complete 4 0.198 0.333
corrective actions
Cost allocated to improvement actions 2 0.120 0.444
and environmental initiatives as part of
the total budget
Overall value of recycling and 0.668
improvement actions
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More specifically, the assessment results of Table 2 transform the current values
of the selected indicators using the estimated value functions. For example, the
industry currently emits 35 tn of CO2 per month and this corresponds to a weighted
value (score) of 0.080. The sum of these weighted values provide an overall
performance score for the EPE dimensions (e.g., 0.561 for air emissions, in a range
of 0.000-1.000). Usually the performance score of the set of indicators is also
presented in an unweighted form, in order to have clear view about potential
improvement actions. For example, the weighted value of 0.080 of the quantity of
CO2 corresponds to an unweighted value of 0.667. The latter is defined in [0, 1] and
reveals the moderate performance of the industry in this particular indicator.
Figure 1 presents the overall EPE using the aggregated value of indicators within a
specific category (fourth column of Table 2). This type of graph provides a general
view of the industry’s EPE. As shown, resources and energy is the environmental
dimension with the lowest performance, while other dimensions may also require
improvements (e.g., air emissions).
The previous findings provide a clear view of the strengths and weaknesses of the
industry’s EPE. Most importantly, it can identify the parts of environmental
management that need improvement, as well as the level of effort that is required for
this improvement. They are very useful as they can display in a simple and
understandable manner to the top management the performance of the industry. They
also allow for comparisons with past performances, as well as for the establishment
of particular goals per indicator, per environmental dimension or globally.
Fig. 1. Overall environmental performance evaluation per dimension.
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3 Concluding Remarks
EPE is an important tool for the evaluation and the documentation of a successful
environmental management system. The EPE is defined as a continuous internal
process and a management tool that uses indicators in order to evaluate the
environmental management system of a business organization and to compare past
and present environmental performance. International standards ISO 14031-14032
describe the categories of performance indicators; however they do not determine a
specific framework for the development and measurement of these indicators. The
main aim of this study is to present an EPE methodology based on a fuzzy
multicriteria analysis approach.
In particular, the Fuzzy UTASTAR method is applied in order to evaluate the
environmental performance of a mill industry. Fuzzy UTASTAR, as presented
herein, comprises a method that carries all the characteristics of the original method
and at the same time can also handle fuzzy data. With fuzzy UTASTAR, the
estimated value functions are also fuzzy, focusing mainly in taking into account the
ambiguity and uncertainty, which are common characteristics in real-world problems
and situations. Fuzzy UTASTAR is able to handle this vagueness assisting DMs in
their difficult tasks, and at the same time easies the modelling of his/her preferences.
As far as EPE is concerned, the application presented herein showed that fuzzy
UTASTAR is able to identify the weaknesses in relation to environmental issues,
thus allowing organizations to align their improvement efforts and actions based on
their environmental policy. It can also provide a clear view of the distance of the
organization from its goals and targets. Conclusively fuzzy UTASTAR is an
approach that can be adopted by organizations, irrespective of size and type of
activity, and enable them to evaluate their environmental performance in an easy and
straightforward manner.
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