To implement a resilient manufacturing system, adaptive systems are required to respond to changes and disruptions. In this article, we present a research prototype of an adaptive production system. Adaptivity is implemented here in three components and on different levels. The first component is an adaptive robotic system that can be easily trained to pick up heterogeneous parts and place them on an autonomously guided vehicle. This component implements adaptivity at the task level. The second component is a planning system that can be used to reschedule production orders on an ad hoc basis. This system also allows the simulation of machine failures to analyze resilience. This job shop planning system implements adaptivity at runtime at the level of production execution. The third component is a modular process modeling and execution system that enables adaptivity at the process level. It supports the users in redesigning production processes with the help of a graphical user interface. The overall system is modular, with the three components being run in an adaptive, agile, and decentralized way. It forms a system-of-systems that shows resilience to several disruptive events.
Digital transformation affects many aspects of our everyday lives. This paper focuses on challenges and opportunities in the area of factory automation. It presents the layout and components of the Pilotfabrik Industrie 4.0 of TU Wien as an example of a modern, flexible, and highly digitized smart factory. Furthermore, the paper presents use cases that were implemented based on the available IoPT devices in the Pilotfabrik Industrie 4.0. The first use case aims to improve product quality by detecting chatter – a vibrational phenomenon in machine tools – and taking appropriate countermeasures. The second use case tries to predict tool breakage by closely monitoring the power consumption of the machine tool and, thus, reducing the probability of damaged products.
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