BACKGROUND: Numerous studies examine simulation modelling in healthcare. These studies present a bewildering array of simulation techniques and applications, making it challenging to characterise the literature. OBJECTIVE: The aim of this paper is to provides an overview of the level of activity of simulation modelling in healthcare and the key themes. METHODS: Umbrella review of systematic literature reviews of simulation modelling in healthcare. Searches were conducted of academic databases (JSTOR, SCOPUS, PUBMED, IEEE, SAGE, ACM, Wiley Online Library, Science Direct) and grey literature sources, enhanced by citation searches. The articles were included if they performed a systematic review of simulation modelling techniques in health care. After quality assessment of all included articles, data was extracted on numbers of studies included in each review, types of applications, techniques used for simulation modelling, data sources and simulation software. RESULTS:The search strategy yielded a total of 117 potential articles. Following sifting, 37 heterogeneous reviews were included. Most reviews achieved moderate quality rating on a modified AMSTAR checklist. All the review articles described the types of applications used for simulation modelling; 15 reviews described techniques used for simulation modelling; 3 reviews described data sources used for simulation modelling; and 6 reviews described software used for simulation modelling. The remaining reviews either did not report or did not provide enough detail for the data to be extracted. CONCLUSION: Simulation modelling techniques have been used for a wide range of applications in healthcare, with a variety of software tools and data sources. The number of reviews published in the recent years suggest an increased interest for simulation modelling in healthcare. (263 words)

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The adoption of Industry 4.0 technologies within the manufacturing and process industries is widely accepted to have benefits for production cycles, increase system flexibility and give production managers more options on the production line through reconfigurable systems. A key enabler in Industry 4.0 technology is the rise in Cyber-Physical Systems (CPS) and Digital Twins (DTs). Both technologies connect the physical to the cyber world in order to generate smart manufacturing capabilities. State of the art research accurately describes the frameworks, challenges and advantages surrounding these technologies but fails to deliver on testbeds and case studies that can be used for development and validation. This research demonstrates a novel proof of concept Industry 4.0 production system which lays the foundations for future research in DT technologies, process optimisation and manufacturing data analytics. Using a connected system of commercial off-the-shelf cameras to retrofit a standard programmable logic controlled production process, a digital simulation is updated in real time to create the DT. The system can identify and accurately track the product through the production cycle whilst updating the DT in real-time. The implemented system is a lightweight, low cost, customable and scalable design solution which provides a testbed for practical Industry 4.0 research both for academic and industrial research purposes.