An early-stage decision-support framework for the implementation of intelligent automation

The constant pressure on manufacturing companies to improve productivity, reduce the lead time and progress in quality requires new technological developments and adoption.The rapid development of smart technology and robotics and autonomous systems (RAS) technology has a profound impact on manufacturing automation and might determine winners and losers of the next generation’s manufacturing competition. Simultaneously, recent smart technology developments in the areas enable an automation response to new production paradigms such as mass customisation and product-lifecycle considerations in the context of Industry 4.0. New paradigms, like mass customisation, increased both the complexity of the tasks and the risk due to smart technology integration. From a manufacturing automation perspective, intelligent automation has been identified as a possible response to arising demands. The presented research aims to support the industrial uptake of intelligent automation into manufacturing businesses by quantifying risks at the early design stage and business case development. An early-stage decision-support framework for the implementation of intelligent automation in manufacturing businesses is presented in this thesis.The framework is informed by an extensive literature review, updated and verified with surveys and workshops to add to the knowledge base due to the rapid development of the associated technologies. A paradigm shift from cost to a risk-modelling perspective is proposed to provide a more flexible and generic approach applicable throughout the current technology landscape. The proposed probabilistic decision-support framework consists of three parts:• A clustering algorithm to identify the manufacturing functions in manual processes from task analysis to mitigate early-stage design uncertainties• A Bayesian Belief Network (BBN) informed by an expert elicitation via the DELPHI method, where the identified functions become the unit of analysis.• A Markov-Chain Monte-Carlo method modelling the effects of uncertainties on the critical success factors to address issues of factor interdependencies after expert elicitation.Based on the overall decision framework a toolbox was developed in Microsoft Excel. Five different case studies are used to test and validate the framework. Evaluation of the results derived from the toolbox from the industrial feedback suggests a positive validation for commercial use. The main contributions to knowledge in the presented thesis arise from the following four points:• Early-stage decision-support framework for business case evaluation of intelligent automation.• Translating manual tasks to automation function via a novel clustering approach• Application of a Markov-Chain Monte-Carlo Method to simulate correlation between decision criteria• Causal relationship among Critical Success Factors has been established from business and technical perspectives.The implications on practise might be promising. The feedback arising from the created tool was promising from the industry, and a practical realisation of the decision-support tool seems to be desired from an industrial point of view.With respect to further work, the decision-support tool might have established a ground to analyse a human task automatically for automation purposes. The established clustering mechanisms and the related attributes could be connected to sensorial data and analyse a manufacturing task autonomously without the subjective input of task analysis experts. To enable such an autonomous process, however, the psychophysiological understanding must be increased in the future.</div

System requirements for service quality appraisal system (SQAS) to be used in commercial banks by blind customers

Includes bibliographical references (leaves 109-116).In a fast moving competitive sector like banking, the customer service department often finds it difficult to keep up with the pace at which customer concerns are raised. On the other hand, the speed at which this department responds to customer concerns determines the difference between keeping a customer and losing one. Thus, most banks have moved to technology to expedite the process of capturing and processing customer complaints. Unfortunately, not every customer serviced by these banks finds the deployed technologies accessible and usable. Among the customers who find technologies in the banks inaccessible and unusable are blind customers. In part, the inaccessibility of technologies used in banks may be attributed to poor requirements engineering. Poorly elicited requirements lead to the design of products which fail to satisfy the needs of the diverse population they service. The purpose of this project is to specify neatly validated requirements using the SMART criterion for a system that can be used to evaluate levels of customer satisfaction with services offered to them by banks. The envisaged system should be able to cater for the needs of the blind customers served by these banks. Data for the study was collected from blind people in a vocational school in Botswana, customer care managers in five different bank brands and the system designers. Data was collected through guided interview sessions, which on average lasted for thirty minutes per respondent. Data from the respondents was analyzed qualitatively and quantitatively. Data was summarized into tables, graphs, diagrams and charts to reveal trends. Data was further analyzed to specify the requirements of a system that allows blind customers to provide feedback to their banks. In an attempt to align the requirements to the specific needs of blind customers the specified requirements were reviewed and validated, guided by the principles of the SMART criterion

Constructionism through mobile interactive knowledge elicitation (MIKE) in human-computer interaction

Mobile computing holds significant as-yet unknown applications of interest in the field of Cyberscience (e-Science) methods. This thesis provides a diverse exploration into the advancement of HC1 theory through the development and testing of mobile cyberscience tools. This is done by synthesising new metrics from learning epistemologies, with the benefits that can be provided by mobile computing solutions. This thesis aims to explore how mobile cyberscience can improve HCI knowledge elicitation (KE) methods. A review of the current state of the art in mobile computing and mobile HCI demonstrates that there is very little reported research in the direction of applying mobile computing to HCI theory (rather than the reverse which is demonstrated to be significantly considered in academia). This motivates a review of the current methods and cyberscience-based tools in the domain of KE in HCI, with several prototype mobile tool designs discussed. A review of candidate grounding theories in pedagogical epistemologies is then covered to build a theoretical foundation for this work. This facilitates the acquisition of a mobile-applicable investigation candidate, namely Constructionism theory, for software modelling in mobile computing methods in HCI KE. A framework for investigating constructionism is designed and presented, describing three key models that extend the domain of HCI KE theory. Through the design, implementation and testing (both expert and user testing) of several mobile computing tools for HCI KE, termed MIKE (Mobile Interactive Knowledge Elicitation) tools, these three key models of constructionism are explored through empirical research and are reported in this thesis as separate case studies. Case study 1 investigates the use of inert constructionism through the use of card sorting. Case Study 2 investigates the use of semi-dynamic constructionism through the use of affinity diagramming. Case Study 3 investigates the use of dynamic constructionism, through the use of low fidelity paper prototyping. The findings from these case studies indicate that mobile cyberscience has a significant scope for application in the practice of current-day HCI methods, and that new qualitative measures in HCI can be acquired through mobile cyberscience tools. There are three main contributions of this thesis that provide practitioners, educators and researchers in HCI with new knowledge. Firstly, the fields of mobile computing and mobile HCI are expanded with the empirically tested simulation of the techniques of card sorting, affinity diagramming and low-fidelity paper prototyping in HCI theory through mobile software. Secondly, a developed framework of constructionism theory successfully enhances the field of HCI KE, contributing to the growth of grounding theories in the field of HCI through the findings of three separately reported case studies. Lastly, cyberscience research for HCI has been given an expansion of research in the area of augmenting HCI with mobile computing. This is achieved through the user centred design, development and user testing of several mobile tools incorporating facilities unique to HCI practitioners, educators and researchers, leading to several related peer-reviewed publications

Supporting engineering design using knowledge based systems technology with a case study in electricity distribution network design

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis explores the architectural requirements of engineering design support systems based on knowledge based systems technology. The exploration is based on an understanding of the nature of designing as a professional activity and on the extent to which designers' competence can be modelled. Attention is focused on certain salient aspects of designers' competent behaviour. The theoretical study leads to the specification of requirements to be satisfied by a knowledge based system which will support designers in their professional setting and to the proposal of some knowledge based system components which will meet the requirements identified. The theoretical aspect of the thesis is complemented by a case study based on a designer of high voltage electricity distribution networks. The case study illustrates the theoretical component of the thesis and the methodological basis for the work. The practical realizability of the components of the knowledge based systems architecture proposed are demonstrated using the results of the analysis of the knowledge elicited in the case study without prejudicing the general applicability of the ideas. An object-oriented knowledge engineering software development environment is used to demonstrate how some components of the design situation represented can be implemented.Financial support provided by Brunel University

Rational design theory: a decision-based foundation for studying design methods

While design theories provide a foundation for representing and reasoning about design methods, existing design theories do not explicitly include uncertainty considerations or recognize tradeoffs between the design artifact and the design process. These limitations prevent the existing theories from adequately describing and explaining observed or proposed design methods. In this thesis, Rational Design Theory is introduced as a normative theoretical framework for evaluating prescriptive design methods. This new theory is based on a two-level perspective of design decisions in which the interactions between the artifact and the design process decisions are considered. Rational Design Theory consists of normative decision theory applied to design process decisions, and is complemented by a decision-theory-inspired conceptual model of design. The application of decision analysis to design process decisions provides a structured framework for the qualitative and quantitative evaluation of design methods. The qualitative evaluation capabilities are demonstrated in a review of the systematic design method of Pahl and Beitz. The quantitative evaluation capabilities are demonstrated in two example problems. In these two quantitative examples, Value of Information analysis is investigated as a strategy for deciding when to perform an analysis to gather additional information in support of a choice between two design concepts. Both quantitative examples demonstrate that Value of Information achieves very good results when compared to a more comprehensive decision analysis that allows for a sequence of analyses to be performed.Ph.D.Committee Chair: Paredis, Chris; Committee Member: Ashuri, Baabak; Committee Member: Bras, Bert; Committee Member: McGinnis, Leon; Committee Member: Rosen, Davi

An Optimisation-based Framework for Complex Business Process: Healthcare Application

The Irish healthcare system is currently facing major pressures due to rising demand, caused by population growth, ageing and high expectations of service quality. This pressure on the Irish healthcare system creates a need for support from research institutions in dealing with decision areas such as resource allocation and performance measurement. While approaches such as modelling, simulation, multi-criteria decision analysis, performance management, and optimisation can – when applied skilfully – improve healthcare performance, they represent just one part of the solution. Accordingly, to achieve significant and sustainable performance, this research aims to develop a practical, yet effective, optimisation-based framework for managing complex processes in the healthcare domain. Through an extensive review of the literature on the aforementioned solution techniques, limitations of using each technique on its own are identified in order to define a practical integrated approach toward developing the proposed framework. During the framework validation phase, real-time strategies have to be optimised to solve Emergency Department performance issues in a major hospital. Results show a potential of significant reduction in patients average length of stay (i.e. 48% of average patient throughput time) whilst reducing the over-reliance on overstretched nursing resources, that resulted in an increase of staff utilisation between 7% and 10%. Given the high uncertainty in healthcare service demand, using the integrated framework allows decision makers to find optimal staff schedules that improve emergency department performance. The proposed optimum staff schedule reduces the average waiting time of patients by 57% and also contributes to reduce number of patients left without treatment to 8% instead of 17%. The developed framework has been implemented by the hospital partner with a high level of success