Page 330 - Materials Chemistry, Second Edition

330 16. Life cycle sustainability improvement

situation that one process performs betters than another with respect to one evaluation cri-
terion, but it may performance worse with respect to another evaluation criterion. Therefore,
it is difficult for the stakeholders to know whether or not these processes or products are
sustainable, and they also don’t know the ways for improving the sustainability of the
nonsustainable alternatives. In addition, it is difficult for the decision-makers to get the data
of the alternative processes or products with respect to some soft criteria (i.e., social accept-
ability, working environment, and influences on health, etc.), because these data sometime
cannot be quantified. All in all, there are two problems should be addressed:

(1) LCSA can investigate the environmental, economic, and social performance of different
processes or products, but the stakeholders do not know whether or not they are
sustainable and the ways to improve the sustainability of the nonsustainable processes or
products;
(2) It lacks the methods for quantifying the relative performances of the processes or products
with respect to the soft criteria.
In order to solve the above two problems, a methodological framework was developed by
combining life cycle sustainability assessment method, the intuitionistic fuzzy AHP, and
data envelopment analysis (DEA) for judging whether or not these alternatives are sustain-
able and providing the methods for improving the sustainability of the nonsustainable
alternatives. DEA is a linear programming method, which can be used to assess the compar-
ative efficiency of different decision-making units (DMUs) with multiple inputs and outputs
(Banker et al., 1984). In this study, LCSA and the intuitionistic fuzzy AHP method were
combined to obtained the data with respect to the inputs and outputs. LCSA was employed
to collect the data for the hard evaluation criteria that can be quantified by LCA, LCC, and
SLCA. The intuitionistic fuzzy AHP as a weighting method is used for determining the data
of the alternatives with respect to the soft criteria. After obtaining all the data of all the alter-
natives with respect to all the evaluation criteria, the benefit-type criteria and the cost-type
criteria are used as the outputs and inputs in the DEA model, respectively.

16.2 Methods

An integrated data envelopment, weighting method, and life cycle thinking methodolog-
ical framework is developed in this study to measure the sustainability efficiency of different
energy and industrial systems, and these systems are recognized as the decision-making
units (DMUs). The outputs and the inputs are determined based on life cycle thinking
with the tools such as life cycle assessment, life cycle costing, and social life cycle assessment.
As for the data with respect to the soft criteria, which cannot be obtained directly
by using these life cycle tools, they are determined by using the weighting method, and
the intuitionistic fuzzy AHP is employed to determine the relative performances of the
alternatives with respect to the soft criteria. After determining the data of all the inputs
and the outputs, the data envelopment analysis (DEA) method is employed to measure
the sustainability efficiency of different energy and industrial systems. The DEA-efficient
and the non-DEA-efficient scenarios can be identified, and the countermeasures for