A Universal Analysis Tool For Process- And Energy-Optimization Of Insulation Processes In The Production Of Electric Drives
2015 5TH INTERNATIONAL ELECTRIC DRIVES PRODUCTION CONFERENCE (EDPC)(2015)
摘要
The process of deciding on an appropriate impregnation method is quite challenging due to the high amount of distinct methods and rising requirements, especially within traction drive production. At the Institute for Factory Automation and Production Systems in Nuremberg (FAPS), a simulation tool for the analysis of impregnation processes for electric drives was developed. This tool enables an accurate and detailed analysis of impregnation and curing methods using a material flow simulation to evaluate the level of economy. The primary focus lies on process capabilities (e.g. lead times, work in process, output), economic efficiency and energy consumption.This paper presents the process of defining the necessary constraints and requirements for a tool in order to display and compare several currently available impregnation processes. The actual tool based on commonly used value stream analysis software provides universal adaptability to existing impregnation units as well as improvement scenarios. Additionally, an energy analysis extension of the software developed at FAPS was integrated into the analysis tool. The extension allows readily importing actual recorded energy data and thus predicting the overall energy consumption in a clear and precise manner. To aid the analysis of the simulation results, automated evaluation was integrated into the tool. This includes a visual presentation of the results, a fully automated graphical interpretation of the data and the possibility of comparing several scenarios at once.The tool aims to simplify the analysis of impregnation scenarios. It is suitable for performing a detailed comparison of real impregnation processes as well as future, improved methods and alternatives that are still under development.
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关键词
Impregnation,Insulation,Flow Simulation Impregnation,Insulation,Flow Simulation
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