INDUSTRY 4.0/SMART FACTORIES


MACHINE LEARNING: ARE WE THERE YET? S


eventy years ago WW2 code-breaker and founder of computer science Alan Turing proposed that a ‘learning machine’ could become artificially intelligent. Some advances are starting to show promise. However, as a sub discipline of informatics, there’s still a lot of deep learning and artificial neural networking to undertake before the latest generation of injection moulding machines can fully predict and react autonomously to a given production situation.


Several Sumitomo (SHI) Demag automation experts shared their insight and the AI advances that are emerging at an inaugural online workshop hosted last month by Polymer Technology Ireland and the Institute of Materials (IOM). With machine learning at the heart of future autonomous and intelligent systems, understanding the data independencies and interoperability will be critical, highlighted presenters Dr. Melanie Rohde-Tibitanzl and Dr. Thorsten Thümen. AI has now leapt beyond academic curiosity and has begun edging towards reality. New research by the World Economic Forum predicts that by 2025 the division of tasks between humans and machines will be equally split, with reduced demand for people globally to perform operational, machinery repairs, assembly and stock keeping duties. Additionally, the current COVID-19 pandemic has seen a rapid digitalisation of work processes.


HANDLING LARGE DATA POOLS To accelerate the development of autonomous machine learning in a moulding production environment, Sumitomo (SHI) Demag has been busily working behind the scenes with a consortium of scientific academics and technology pioneers. This has resulted in


IKV in collaboration with Sumitomo (SHI) Demag demonstrate the digital landscape and unveil the focus of its next publicly funded research project - AI and self-learning machines


24 MARCH 2021 | FACTORY&HANDLINGSOLUTIONS


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