Digitaler Zwilling des Produktionssystems

Overbeck, Leonard; Brützel, Oliver; Stricker, Nicole; Lanza, Gisela

doi:10.3139/104.112326

Cited by 9 publications

(2 citation statements)

References 13 publications

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“…On the one hand, the required knowledge to create or operate a simulation is often missing. On the other hand, many simulation tools are far too complex and not user-friendly, and the creation of a specific simulation usually requires much time, capacity, and know-how [4].…”

Section: Introductionmentioning

confidence: 99%

“…The Trumpf Group offers manufacturing solutions in the fields of machine tools, laser technology, electronics, and power tools [11]. Simulation service providers cooperate with such large companies because creating, operating, and inevitably maintaining such a simulation requires a high level of knowledge on this subject [4]. During the literature review, no proof could be found that small-and medium-sized enterprises (SME) use simulations in their daily production routine.…”

Section: Introductionmentioning

confidence: 99%

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Concept and Case Study for a Generic Simulation as a Digital Shadow to Be Used for Production Optimisation

et al. 2021

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Optimising an existing production plant is a challenging task for companies. Necessary physical test runs disturb running production processes. Simulation models are one opportunity to limit these physical test runs. This is particularly important since today’s fast and intelligent networking opportunities in production systems are in line with the call of Industry 4.0 for substantial and frequent changes. Creating simulation models for those systems requires high effort and in-depth knowledge of production processes. In the current literature, digital twins promise several advantages for production optimisation and can be used to simulate production systems, which reduce necessary physical test runs and related costs. While most companies are not able to create digital twins yet, companies using enterprise resource planning (ERP) systems have the general capability to create digital shadows. This paper presents a concept and a case study for a generic simulation of production systems in AnyLogic™ to create digital shadows as the first step towards a full digital twin. The generic simulation visualises production systems automatically and displays key performance indicators (KPIs) for the planned production program, using representational state transfer (REST) interfaces to extract product and production data from an ERP system. The case study has been applied in a learning factory of the University of Applied Life Sciences Emden/Leer. The results prove the presented concept of the generic simulation and show the limits and challenges of working with generic simulation models.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%