The SMA mass production optimization challenge

by Ingpuls GmbH

Identify relevant production processes to reduce waste and significantly save energy as well as material input and also reduce the wear of tools.

Keywords: Shape Memory Alloys, SMA, Intelligent materials, mass production, production efficiency, production waste, tool wear, energy efficiency, sustainability, big data analysis, artificial intelligence, Industrie 4.0, IoT

SMA are functional materials with a very promising future. The production of these alloys implies hundreds of single processing steps. Therefore, special efforts are required to manufacture these NiTi-based SMA components with good reproducibility. This is a fundamental condition to establish SMA in high volume markets and applications like automotive or consumer electronics.
Today we are in the middle of our first and preparing several new mass production projects. We have made our very first experiences on a low automatization level and systematically collected a large amount of data. We think now is the time to analyze the large amount of data to identify efficiency potentials concerning production processes and wear management. We believe modern concepts like big data analysis, neuronal network technologies or artificial intelligence to be key factors for improvement. By their use and implementation in our production we hope to optimize our processes, reduce waste and become even more sustainable than before. If you think you might have solutions or techniques to address our problem, we invite you to join the Ingpuls SMA challenge.