An advanced real-time predictive maintenance framework for large scale machine systems

This thesis introduces and develops a novel real-time predictive maintenance system to estimate the machine system parameters using the motion current signature. Recently, motion current signature analysis has been addressed as an alternative to the use of sensors for monitoring internal faults of a motor. A maintenance system based upon the analysis of motion current signature avoids the need for the implementation and maintenance of expensive motion sensing technology. By developing nonlinear dynamical analysis for motion current signature, the research described in this thesis implements a novel real-time predictive maintenance system for current and future manufacturing machine systems. A crucial concept underpinning this project is that the motion current signature contains infor­mation relating to the machine system parameters and that this information can be extracted using nonlinear mapping techniques, such as neural networks. Towards this end, a proof of con­cept procedure is performed, which substantiates this concept. A simulation model, TuneLearn, is developed to simulate the large amount of training data required by the neural network ap­proach. Statistical validation and verification of the model is performed to ascertain confidence in the simulated motion current signature. Validation experiment concludes that, although, the simulation model generates a good macro-dynamical mapping of the motion current signature, it fails to accurately map the micro-dynamical structure due to the lack of knowledge regarding performance of higher order and nonlinear factors, such as backlash and compliance. Failure of the simulation model to determine the micro-dynamical structure suggests the pres­ence of nonlinearity in the motion current signature. This motivated us to perform surrogate data testing for nonlinearity in the motion current signature. Results confirm the presence of nonlinearity in the motion current signature, thereby, motivating the use of nonlinear tech­niques for further analysis. Outcomes of the experiment show that nonlinear noise reduction combined with the linear reverse algorithm offers precise machine system parameter estimation using the motion current signature for the implementation of the real-time predictive maintenance system. Finally, a linear reverse algorithm, BJEST, is developed and applied to the motion current signature to estimate the machine system parameters.

Demonstration of 10 Gbit/s transmission over 900 km SMF with <400 ns adaptation time using full-field EDC

This reported work significantly extends the reach of 10Gbit/s on-off keying singlemode fibre (SMF) transmission using full-field based electronic dispersion compensation (EDC) to 900 km. In addition, the EDC balances the complexity and the adaptation capability by employing a simple dispersive transmission line with static parameters for coarse dispersion compensation and 16-state maximum likelihood sequence estimation with Gaussian approximation based channel training for adaptive impairment trimming. Improved adaptation times of less than 400 ns for a bit error rate target of 10-3 over distances ranging from 0 to 900 km are reported.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

The use of ICT by logistics service providers and implications for training needs:a cross-country perspective

Changes in the international economic scenario in recent years have made it necessary for both industrial and service firms to reformulate their strategies, with a strong focus on the resources required for successful implementation. In this scenario, information and communication technologies (ICT) has a potentially vital role to play both as a key resource for re-engineering business processes within a framework of direct connection between suppliers and customers, and as a source of cost optimisation. There have also been innovations in the logistics and freight transport industry in relation to ICT diffusion. The implementation of such systems by third party logistics providers (3PL) allows the real-time exchange of information between supply chain partners, thereby improving planning capability and customer service. Unlike other industries, the logistics and freight transport industry is lagging somewhat behind other sectors in ICT diffusion. This situation is to be attributed to a series of both industry-specific and other factors, such as: (a) traditional resistance to change on the part of transport and logistics service providers; (b) the small size of firms that places considerable constraints upon investment in ICT; (c) the relative shortage of user-friendly applications; (d) the diffusion of internal standards on the part of the main providers in the industry whose aim is to protect company information, preventing its dissemination among customers and suppliers; (e) the insufficient degree of professional skills for using such technologies on the part of staff in such firms. The latter point is of critical importance insofar as the adoption of ICT is making it increasingly necessary both to develop new technical skills to use different hardware and new software tools, and to be able to plan processes of communication so as to allow the optimal use of ICT. The aim of this paper is to assess the impact of ICT on transport and logistics industry and to highlight how the use of such new technologies is affecting providers' training needs. The first part will provide a conceptual framework of the impact of ICT on the transport and logistics industry. In the second part the state of ICT dissemination in the Italian and Irish third party logistics industry will be outlined. In the third part, the impact of ICT on the training needs of transport and logistics service providers - based on case studies in both countries - are discussed. The implications of the foregoing for the development of appropriate training policies are considered. For the covering abstract see ITRD E126595.

Translating specialised texts:an overview of key factors involved in translator training for specialized translation

Translators wishing to work on translating specialised texts are traditionally recommended to spend much time and effort acquiring specialist knowledge of the domain involved, and for some areas of specialised activity, this is clearly essential. For other types of translation-based, domain-specific of communication, however, it is possible to develop a systematic approach to the task which will allow for the production of target texts which are adequate for purpose, in a range of specialised domains, without necessarily having formal qualifications in those areas. For Esselink (2000) translation agencies, and individual clients, would tend to prefer a subject expert who also happens to have competence in one or more languages over a trained translator with a high degree of translation competence, including the ability to deal with specialised translation tasks. The problem, for the would-be translator, is persuading prospective clients that he or she is capable of this. This paper will offer an overview of the principles used to design training intended to teach trainee translators how to use a systematic approach to specialised translation, in order to extend the range of areas in which they can tackle translation, without compromising quality or reliability. This approach will be described within the context of the functionalist approach developed in particular by Reiss and Vermeer (1984), Nord (1991, 1997) inter alia.

Demonstration of 10 Gbit/s transmission over 900 km SMF with <400 ns adaptation time using full-field EDC

This reported work significantly extends the reach of 10Gbit/s on-off keying singlemode fibre (SMF) transmission using full-field based electronic dispersion compensation (EDC) to 900 km. In addition, the EDC balances the complexity and the adaptation capability by employing a simple dispersive transmission line with static parameters for coarse dispersion compensation and 16-state maximum likelihood sequence estimation with Gaussian approximation based channel training for adaptive impairment trimming. Improved adaptation times of less than 400 ns for a bit error rate target of 10-3 over distances ranging from 0 to 900 km are reported.

Training perceptions, engagement and performance:comparing work engagement and personal role engagement

The purpose of this study was to compare two engagement constructs (work engagement and personal role engagement) with regards to their relationship with training perceptions and work role performance behaviours. It was hypothesised that personal role engagement would show incremental validity above that of work engagement at predicting work role performance behaviours and be a stronger mediator of the relationships between training perceptions and such behaviours. Questionnaire data was gathered from 304 full-time working adults in the UK. As predicted, personal role engagement was found to explain additional variance above that of work engagement for task proficiency, task adaptability, and task proactivity behaviours. Moreover, personal role engagement was a stronger mediator of the relationship between training perceptions and task proficiency as well as between training perceptions and task adaptability. Both work engagement and personal role engagement mediated the relationship between training perceptions and task proactivity to a similar degree. The findings suggest that personal role engagement has better practical utility to the HRD domain than work engagement, and indicates that future research may benefit from adopting the personal role engagement construct.