This paper aims to propose a supply chain resilience assessment framework. An inductive research approach was used being performed an exploratory case study in the Portuguese automotive supply chain. The study investigates the main effects of supply chain disturbance and how companies can increase supply chain resilience. Empirical findings were used to develop a resilience assessment model with two perspectives, an “ex post” analysis, where it measures the performance loss after a disturbance occurrence, and in an “ex ante” analysis, measuring the characteristics that confer resilience properties to the supply chain.
In a global market, companies must deal with a high rate of changes in business environment. Most manufacturing systems fail to sustain productivity when process disturbances occur. Therefore, it is necessary to create resilient production systems with the ability to return, rapidly, to the initial stage or to an improved one. The parameters, variables and restrictions of the production system are inherently vagueness. This situation suggests that there are dependencies between relevant variables which are not possible to know with precision. The fuzzy logic theory has the ability to describe, in a quantitative and qualitative way, problems that involve vagueness and imprecision. This paper provides an overview for the use of fuzzy logic to establish resilient production systems. Fuzzy concepts are reviewed, in particular its applications to production systems, trying to classify related fuzzy parameters and vari-ables. In addition, the concept of resilient systems are reviewed and extended to production. Finally, it is proposed an approach to establish resilient production systems using the fuzzy set theory
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