| dc.description.abstract | Energy efficiency in manufacturing is an increasingly discussed issue in the pursuit of reducing energy costs and reducing the negative environmental impact of industrial processes. Thus, it seeks to produce more with less energy and for this it is essential to have full knowledge of consumption in production. In order to work on energy efficiency improvement in manufacturing, it is necessary to have energy management and, to reach that, is important to have an energy monitoring of productive resources. To evaluate collected data by monitoring system, are needed Key Performance Indicators (KPIs) that can provide decision-making support for process improvement that promote better energy efficiency. These energy efficiency KPIs can receive information by cross-checking energy monitoring system databases with production monitoring systems such as the Manufacturing Execution System (MES), which can provide real-time information of the resources, products and production. In this context, this work proposed the application of eight KPIs that could be used integrating data from an energy monitoring system with a production monitoring system. Firstly, was made a study of the main energy KPIs in manufacturing and to validate these eight indicators, an experimental study was conducted to generate data that would feed these indicators and allow an evaluation and discussion of their relevance. The experimental study of this work was divided into two parts, the first for validation of indicators at product and process level and the second at production level in a machining process. The construction of the experimental study was carried out using Taguchi's Design of Experiments (DOE) methodology in nine samples with different combinations of values for three different cutting parameters (depth of cut (Ap), feed (Fn) and cutting speed (VC)). The results obtained show that the most relevant KPIs were the indicator of direct energy and the indicator of energy efficiency in performance. The direct energy KPI has the sample with the most severe cutting conditions and the shortest cycle time as the one with the best energy efficiency, with 167 Wh less energy consumption than the sample with milder cutting conditions. The energy efficiency indicator on performance, on the other hand, presented the impact of energy waste when there is low performance in production and the result of the sample with a shorter cycle time shown an efficiency of 64 percentage points higher than the sample with a longer cycle time. | en |
