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The research presented in this paper looks at evaluating RAMI4.0, a Research Architecture (RA) designed for Industry 4.0, through the representation of an existing Cyber-Physical System's (CPSs) key functionality. The use case represented is that of a UK firm refurbishing End of Life (EoL) IT devices for business clients. EoL refurbishment is a domain with many complexities due to an inherent business model which results in varying quantities, types and conditions of received devices. These uncertainties can generally not be addressed until the devices have arrived in the facility and are inspected. RAs are an important tool used in system development to represent functionality, this representation should be high level and allow the easy communication of key concepts for not only client-to-developers and developer-to-developer but also either to an audience. An appropriate RA will help industrialists to understand what Industry 4.0 means to them (i.e. increased flexibility and control) and the functionality of any system potentially being invested in. The results of this research included two proposals for the extension of RAMI4.0 regarding the representation of security and humans within the systems. While Industry 4.0 focusses on CPSs this work also makes a further recommendation that the focus of modelling should be shifted to Cyber-Physical Human Systems (CPHSs) to ensure correct consideration of the humans within the system.

Countermovement jumps (CMJs) are widely used in athlete training, performance monitoring and research as an indicator of power output. Despite extensive scientific research on CMJs, data for elite track and field athletes is limited, particularly for non-sprint events and female athletes. The purpose of this study was threefold: (i) to compare CMJ performance between elite sprinters and high jumpers; (ii) to compare CMJ performance between elite male and female athletes in these two events; and (iii) to determine which CMJ take-off parameters correlated most strongly with jump height. Twenty-seven elite athletes (sprinters: nine male and seven female; high jumpers: five male and six female) completed three maximal CMJs. Jump height and take-off phase parameters were obtained from the force–time data and compared between groups; additionally, time series comparisons were performed on the force, power and displacement data. There was no difference in jump height or any of the take-off parameters between the sprinters and high jumpers; however, the time series analysis indicated that the sprinters maintained a lower centre of mass position during the latter concentric phase. The male athletes jumped higher than the female athletes (by 10.0 cm or 24.2%; p < 0.001) with significantly greater body weight normalised peak power (17.9%, p = 0.002) and significantly shorter eccentric time (17.4%, p = 0.035). Jump height was most strongly correlated with peak power. In addition, jump height was also strongly correlated with positive impulse and both minimum and mean concentric centre of mass position. These results support the importance of accounting for event and gender when investigating CMJ performance.

In product-diverse, end-of-life (EoL) production lines the relevant markets, competitors and customer bases continuously change as new products are processed. The resale market itself changes with the influx of new products, as well as hardware and software discontinuations. Competitive business decision making is often performed by a human operator and may not be timely or fully informed. These are decisions such as whether to perform a high cost repair or recycle a product or whether to use a batch of parts in repair or sell them on can be used to optimise product life-cycle management (PLM) and profit margins. A real-time decision making capability can reduce the risk of performing non-profitable processing. The novel contribution of this work is an interoperable semantic decision support toolset that is necessary to enable a capability for timely EoL decisions based on complete knowledge on profitability, predicted pricing and cost-of-production. Many decision support systems have been proposed for the EoL domain, but a lack of interoperability and use of unstructured knowledge bases has led to decisions based on knowledge that is not up to date. Using formalised, semantic technologies offers sustainable decision making in this volatile and increasingly competitive domain.

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Strength asymmetry can be detrimental to athlete performance and may lead to injury. The countermovement jump (CMJ) can be used to measure strength asymmetry via shear force production. The reliability of parameters and effects of asymmetry and shear force production on vertical CMJ performance were evaluated in a study with 15 university-level sprint and high jump athletes ( m = 11, f = 4). The athletes performed three CMJs on two occasions, separated by 1 week. Tri-axial ground reaction force (GRF) was recorded using two force platforms embedded within a bespoke weight training area. Key performance metrics were calculated in real-time describing total CMJ performance, asymmetry and shear force production. Changes in the means and coefficients of variation (CV) were used to express reliability. Twenty-six parameters from the Total analysis and 21 Asymmetry analysis parameters showed a CV lower than 10%. Temporal and kinetic variables describing Asymmetry analysis highlight a lower CV compared with equivalent parameters derived from Total analysis. Shear parameters show high levels of CV compared with Total analysis and Asymmetry analysis. The measures of asymmetry calculated using methods described in this work were shown to be reliable for monitoring CMJ performance. No significant negative relationships were found between measures of asymmetry or shear force and traditional performance metrics in the CMJ (e.g. jump height, specific peak power and peak force). Further work is required to identify the potential of reducing asymmetry on CMJ performance.

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