Proposta de um modelo de simulação baseado em lógica Fuzzy e no SCOR para predizer o desempenho da empresa-foco em cadeias de suprimentos / Proposal of a fuzzy logic simulation model to predict performance of focus company in supply chains

AUTOR(ES)

Gilberto Miller Devós Ganga

DATA DE PUBLICAÇÃO

2010

RESUMO

This paper presents and discusses a proposal based on the theory of fuzzy sets to predict performance of focus company in a supply chain modeled according to causal relationships among performance metrics proposed by SCOR (version 8.0). The use of performance measurement systems to manage performance of supply chains presents some limitations such as difficulty of interpretation of results of qualitative nature as well as the complexity of having a conventional performance measuring system that can adequately handle cause-and-effect relationships of metrics of performance of different business processes of a supply chain. On the other hand, fuzzy logic, a technique suitable for dealing with uncertainty and subjectivity, becomes an interesting alternative approach. Using a descriptive quantitative approach, the research was based on the assumption that a quantitative simulation model can be built that explain (at least in part) the behavior of operational processes. Results of simulation were very much in line with those of the SCORmark methodology (SCC). Statistical analysis of the simulation results based on surface response method also confirmed the relevance of the causal relationships embedded in the model. In general, the findings reinforces the proposition that adoption of a simulation model based on fuzzy-logic and on metrics of the SCOR model seems to be a feasible approach to help managers in the decision making process of managing performance of supply chains.

ASSUNTO(S)

medidas de desempenho gestão do desempenho modelo scor scor model fuzzy logic performance management gestão da cadeia de suprimentos scm performance metrics simulation model lógica fuzzy modelo de simulação supply chain management

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