ABSTRACT
Digitalisation of manufacturing is a crucial component of the Industry 4.0 transformation. The digital twin is an important tool for enabling real-time digital access to precise information about physical systems and for supporting process optimisation via the translation of the associated big data into actionable insights. Although a variety of frameworks and conceptual models addressing the requirements and advantages of digital twins has been suggested in the academic literature, their implementation has received less attention. The work presented in this paper aims to make a proposition that considers the novel challenges introduced for data analysis in the presence of heterogeneous and dynamic cyber-physical systems in Industry 4.0. The proposed approach defines a digital twin simulation tool that captures the dynamics of a machining vibration signal from a source model and adapts them to a given target environment. This constitutes a flexible approach to knowledge extraction from the existing manufacturing simulation models, as information from both physics-based and data-driven solutions can be elicited this way. Therefore, an opportunity to reuse the costly established systems is made available to the manufacturing businesses, and the paper presents a process optimisation framework for such use case. The proposed approach is implemented as a domain adaptation algorithm based on the generative adversarial network model. The novel CycleStyleGAN architecture extends the CycleGAN model with a style-based signal encoding. The implemented model is validated in an experimental scenario that aims to replicate a real-world manufacturing knowledge transfer problem. The experiment shows that the transferred information enables the reduction of the required target domain data by one order of magnitude.
ABSTRACT
BACKGROUND AND PURPOSE: Health information systems (HIS) are expected to be effective and efficient in improving healthcare services, but empirical observation of HIS reveals that most perform poorly in terms of these metrics. Theoretical factors of HIS performance are widely studied, and solutions to mitigate poor performance have been proposed. In this paper we implement effective methods to eliminate some common drawbacks of HIS design and demonstrate the synergy between the methods. JointCalc, the first comprehensive patient-facing web-based decision support tool for joint replacement, is used as a case study for this purpose. METHODS AND RESULTS: User-centred design and thorough end-user involvement are employed throughout the design and development of JointCalc. This is supported by modern software production paradigms, including continuous integration/continuous development, agile and service-oriented architecture. The adopted methods result in a user-approved application delivered well within the scope of project. CONCLUSION: This work supports the claims of high potential efficiency of HIS. The methods identified are shown to be applicable in the production of an effective HIS whilst aiding development efficiency.
