30 Material Criticality Assessment for Business Purposes …
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based on subjective judgments which contain imprecise, ambiguous or vague expressions. Moreover, when multiple metrics are considered to assess the overall criticality,
the linguistic terms are difficult to be directly aggregated into a single term. Although
the single rating number is usually assigned to each term for aggregation purposes
(Duclos et al. 2010), it ignores or loses information about linguistic imprecision. In
response to these limitations, a fuzzy linguistic approach has been developed based
on fuzzy set theory (Zadeh 1975; Zadeh 1965) as a way to represent imprecise,
incomplete or vague information (Bosc and Prade 1997; Dubois and Prade 1998).
This approach has already been used in different fields to evaluate the supply chain
flexibility (Chuu 2011), the performance of products (Cheng and Lin 2002), the
quality of information (Herrera-Viedma et al. 2006) and so on. These studies suggest
that the fuzzy linguistic approach can represent appropriately the linguistic terms
and capture imprecise information for supporting decision-making processes. This
study has two objectives:
(1) Investigate the risk metrics for criticality assessment at a business level;
(2) Develop appropriate approach to manage linguistic information.
Therefore, in this paper, we explore the fuzzy linguistic approach to represent directly linguistic information from experts’ knowledge, which are used for
qualitative criticality assessment of materials.
30.2 Materials and Methods
30.2.1 Criticality Assessment
We characterize the material criticality by a series of risk metrics: abundance risk,
conflict material risk, monopoly of supply risk, sourcing and geopolitical risk, environmental country risk, and price volatility risk. These risk metrics are selected
because they are highly linked to the different risk aspects from business perspectives represented by the critical materials. For example, the companies are required
by legislation to declare when materials are sourced from the conflict regions, so
that the political risk can be quickly and efficiently identified using conflict material
risk metric. For another example, the companies may be exposed to price volatility
risk due to the use of critical materials of high value. Hence, the decision-makers,
especially the risk managers in the commercial organizations, are familiar with the
use of risk terms and the data for these metrics are available in numerous databases
(for this research we have used data found in the GRANTA MI database) (Granta
Ansys 2017). These metrics are represented by numerical indicators, based on which
linguistic risk levels are defined.
457
based on subjective judgments which contain imprecise, ambiguous or vague expressions. Moreover, when multiple metrics are considered to assess the overall criticality,
the linguistic terms are difficult to be directly aggregated into a single term. Although
the single rating number is usually assigned to each term for aggregation purposes
(Duclos et al. 2010), it ignores or loses information about linguistic imprecision. In
response to these limitations, a fuzzy linguistic approach has been developed based
on fuzzy set theory (Zadeh 1975; Zadeh 1965) as a way to represent imprecise,
incomplete or vague information (Bosc and Prade 1997; Dubois and Prade 1998).
This approach has already been used in different fields to evaluate the supply chain
flexibility (Chuu 2011), the performance of products (Cheng and Lin 2002), the
quality of information (Herrera-Viedma et al. 2006) and so on. These studies suggest
that the fuzzy linguistic approach can represent appropriately the linguistic terms
and capture imprecise information for supporting decision-making processes. This
study has two objectives:
(1) Investigate the risk metrics for criticality assessment at a business level;
(2) Develop appropriate approach to manage linguistic information.
Therefore, in this paper, we explore the fuzzy linguistic approach to represent directly linguistic information from experts’ knowledge, which are used for
qualitative criticality assessment of materials.
30.2 Materials and Methods
30.2.1 Criticality Assessment
We characterize the material criticality by a series of risk metrics: abundance risk,
conflict material risk, monopoly of supply risk, sourcing and geopolitical risk, environmental country risk, and price volatility risk. These risk metrics are selected
because they are highly linked to the different risk aspects from business perspectives represented by the critical materials. For example, the companies are required
by legislation to declare when materials are sourced from the conflict regions, so
that the political risk can be quickly and efficiently identified using conflict material
risk metric. For another example, the companies may be exposed to price volatility
risk due to the use of critical materials of high value. Hence, the decision-makers,
especially the risk managers in the commercial organizations, are familiar with the
use of risk terms and the data for these metrics are available in numerous databases
(for this research we have used data found in the GRANTA MI database) (Granta
Ansys 2017). These metrics are represented by numerical indicators, based on which
linguistic risk levels are defined.