System of indicators with a fuzzy-base to evaluate the lean level

Abstract

Companies need to systematically and visibly manage the degree of leanness of their processes and evaluate the implementation of new smart manufacturing projects as part of the new industrial revolution. For this, it is necessary to identify indicators that support the decision-making process.This article proposes a measurement system with a tree-like structure of key performance indicators (KPIs) and key result indicators (KGIs). KPIs determine how well the process is performing to achieve results, indicating whether or not it will be feasible to achieve a goal. KGIs define measures to report whether a process met business objectives. Indicators and their supporting measurement elements are identified and classified in a multi-level hierarchy designed to provide answers at the strategic, tactical, and operational levels. In this way is possible to design a hierarchical framework that allow to indicate the casual relationship between different levels of KPI. The tool uses fuzzy logic with two objectives: 1) to allow the treatment of uncertainty and subjectivity associated with the casual relationship between different levels of KPI and supporting elements and the relationship between the indicators 2) for vague and ambiguous data as input parameters to the model from different domains and scales.