Efficient Markovian Framework for Digital Twinning Applications in Production System Engineering
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Digital twinning, although a highly promising technology, still requires further research and development, particularly regarding efficient simulation tools yielding reliable predictive analytics of the manufacturing process. In such a context, various production systems may rely on supporting algorithms of different complexities and reliabilities that provide predictive analytics in the process background. Thus, such algorithms represent the ‘consciousness’ of production systems by which their actual behavior is mapped into digital space. Efficient algorithms are therefore a prerequisite to the existence of digital twins. Otherwise, one is dealing with a mere database that fails to meet the digital twin concept to a large extent. Hence, an efficient Markovian framework is outlined in this work with the main purpose to use it as a governing determinant when considering the digital twinning of production systems