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Digital twins in baking process automation In a digitization project, it is important to first consider several use cases, because they typically require the most effort, while the implementation of additional use cases promises additional revenue at a lower cost.
A digital twin encompasses all possible information about a product, its production and possibly also its performance throughout its complete lifecycle. Let us illustrate this with bread production: + The general digital twin of a batch of bread may consist of the base recipe, the formulation related to a specific production line and any kind of data collected during production, analytics, and finally transport and distribution. It may also include simulation models relevant for product design or production, and even consumer feedback may be part of it. + The production line in a bakery producing this bread also has a digital twin. It is a combi-
nation of digital twins of its stations and machines. These may include 3-dimensional CAD models used for hardware design; simulation models of different granularity ranging from detailed 3-dimensional simulations to 1-dimensional process flow simulations; models of its control to be used in e.g. production design and model-predictive control; a track of data is collected during operation for monitoring and analytics. The benefit of using digital twins is manifold: The design of a product and its production can be made faster and cheaper using simulation instead of prototyping; the degree of automation can be increased up to autonomous production (3); the transparency of production can be increased leading to more informed and optimal decisions; processes in the supply chain or related to audits can be simplified substantially. In most cases, the main hurdle is the collection of sufficient data points and the integration of several, usually isolated data sources. Digital twins can be stored and used in the cloud, on-premise, but can also be embedded (4). A particular decision typically depends on requirements concerning data privacy and real-time performance. Using digital twins in the cloud is becoming more and more attractive, especially for remote monitoring, analysis and computationally extensive
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What is a digital twin? The industry has seen a couple of periods, each of which introduced innovations leading to a substantial increase in productivity. The introduction of mechanical machines, mass production and electrification and finally automation using electronics and information technology were previous such periods. Now we are in the era of digitization, the advent of which had already been foreseen in 1991 (1) and which is a core innovation of Industry 4.0, a high-tech strategy originally developed in Germany (2). Digitization is about creating digital twins of physical objects, maintaining them, and using them for improving processes related to these objects.
