AI modelling is helping deliver reductions in energy usage and productivity increases in metal casting
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Spotted: Each year, over 3.3 billion tonnes of metals are produced globally, and most demand forecasts show this figure increasing. The problem is that high production rates also result in high waste generation. Casting – a largely manual process that produces complex metal parts – is a particularly wasteful area, with the industry having been slow to make use of digital optimisation .
However, German company Tvarit has developed a solution that could reduce this waste and boost productivity in metal manufacturing. The company uses artificial intelligence (AI) modelling to reduce energy consumption and increase yield in metal casting operations. The system uses more than 160 machine learning models to analyse data from sources such as operator input, machine data, and Internet of Things (IoT) sensors.
Modelling of the part being produced is then compared to a library of components to find the most appropriate model and the most efficient settings for the casting machinery. Once the optimal parameters for production are found, they are continuously optimised throughout the casting process. Tvarit claims the process consistently saves users more than 18 per cent of energy usage while improving the production yield.
Suhas Patel, CEO of Tvarit GmbH, highlights: “Metal manufacturing shop floors are very complex. On state-of-the-art machines, there are 2.4 trillion possible combinations to optimize process parameters. AI is the only way to eliminate waste on the shop floor.”
Tvarit recently completed a series A funding round, led by Momenta, a leading provider of digital solutions that help metal manufacturers achieve net-zero operations.
Manufacturing uses a huge amount of energy and produces massive volumes of waste, so it is no wonder that innovators are seeking to optimise the industry. Springwise has spotted an industrial-scale heat pump that cuts energy usage and an environmentally-friendly method for metal extraction.
Written By: Lisa Magloff