An investigation into the concept of motivation within design

This thesis was submitted for the degree of Master of Philosophy and awarded by Brunel University.This thesis argues that there is a need for design practitioners and design researchers to more clearly articulate and understand the role of design in motivating and engaging human behaviour. Reflecting upon a multifaceted design process adopted in the course of the development of a Public Engagement with Science Exhibition; Ergonomics Real Design hosted at the Design Museum, London in late 2009 and early 2010, this thesis profiles research exploring the concept of human motivational engagement as part of the design and utilisation of a museum exhibition. The role of design and designers in motivating humans is discussed and a number of factors that impact upon the motivational engagement of humans in the museum environment are identified. These factors are synthesised in this thesis in the form of a Motivational Design Framework. The thesis builds upon its definition of factors regulating the motivation of users within the design of multi-touchpoint sociotechnical systems, specifically within the museum environment, through documentation and case-based reflection upon an applied design process that sought to adopt a philosophy of motivational design and elicit the motivational engagement of its participants. Finally this thesis presents an approach to evaluating the motivational engagement of users following their interaction with a designed, multi-touchpoint user experience. The results of these research objectives are recorded and discussed in terms of their implication for design practitioners interested in consciously motivating and engaging user behaviour. This thesis synthesises some key concepts, methods and tools of interest to designers and design researchers who wish to support the motivational energisation, engagement and generative behavioural potential of their users. This thesis advocates for, and contributes to, the formalisation of motivation as a tractable and syntactic concept within the field of exhibition design specifically, and within the broader field of design research more generally

Time estimation in mechanical engineering design.

SIGLEAvailable from British Library Document Supply Centre-DSC:DX195730 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

An Interactive Visualisation System for Engineering Design using Evolutionary Computing

This thesis describes a system designed to promote collaboration between the human and computer during engineering design tasks. Evolutionary algorithms (in particular the genetic algorithm) can find good solutions to engineering design problems in a small number of iterations, but a review of the interactive evolutionary computing literature reveals that users would benefit from understanding the design space and having the freedom to direct the search. The main objective of this research is to fulfil a dual requirement: the computer should generate data and analyse the design space to identify high performing regions in terms of the quality and robustness of solutions, while at the same time the user should be allowed to interact with the data and use their experience and the information provided to guide the search inside and outside regions already found. To achieve these goals a flexible user interface was developed that links and clarifies the research fields of evolutionary computing, interactive engineering design and multivariate visualisation. A number of accessible visualisation techniques were incorporated into the system. An innovative algorithm based on univariate kernel density estimation is introduced that quickly identifies the relevant clusters in the data from the point of view of the original design variables or a natural coordinate system such as the principal or independent components. The robustness of solutions inside a region can be investigated by novel use of 'negative' genetic algorithm search to find the worst case scenario. New high performance regions can be discovered in further runs of the evolutionary algorithm; penalty functions are used to avoid previously found regions. The clustering procedure was also successfully applied to multiobjective problems and used to force the genetic algorithm to find desired solutions in the trade-off between objectives. The system was evaluated by a small number of users who were asked to solve simulated engineering design scenarios by finding and comparing robust regions in artificial test functions. Empirical comparison with benchmark algorithms was inconclusive but it was shown that even a devoted hybrid algorithm needs help to solve a design task. A critical analysis of the feedback and results suggested modifications to the clustering algorithm and a more practical way to evaluate the robustness of solutions. The system was also shown to experienced engineers working on their real world problems, new solutions were found in pertinent regions of objective space; links to the artefact aided comparison of results. It was confirmed that in practice a lot of design knowledge is encoded into design problems but experienced engineers use subjective knowledge of the problem to make decisions and evaluate the robustness of solutions. So the full potential of the system was seen in its ability to support decision making by supplying a diverse range of alternative design options, thereby enabling knowledge discovery in a wide-ranging number of applications

Barriers to creativity in the conceptual phase of engineering design : perceptions of designers at Rolls Royce Aerospace (Bristol) in new projects engineering

Merged with duplicate record 10026.1/693 on 03.04.2017 by CS (TIS)Anecdotal evidence from experienced engineers suggest that barriers to creativity are often due to the limitations of current technology, methods and support systems (Baird, Moore, & Jagodzinski, 2000). The aim of this research was to explore what the perceived barriers to creativity are and how they are circumvented by design engineers working in New Projects Engineering (NPE), Rolls-Royce Aerospace (Bristol). Semi-structured interviews with four employees working in engineering design comprised a Scoping Study. This provided a general overview of the major issues perceived by the design engineers regarding barriers to creativity and resulted in six themes being identified. These themes were used as a framework for a Design Group Interviews Study that followed. Sixteen engineers comprising project managers, team leaders, experienced designers and new designers, graduate employees and trainees were interviewed using the same method. Using grounded theory to analyse the data, sixteen categories were drawn from the data. Confirmation of the findings was achieved through presentations and workshops with different groups from Rolls-Royce, and the development of an Interrelationship Digraph illustrating the relationships between the categories. The second phase of the research focused on the phenomena under current working conditions. In the Tracking Study interview diaries recorded with thirteen design engineers over an eight week period highlighted the salient issues relating to their perceived barriers to creativity. Thirteen categories (some of which could be mapped onto the previous categories and some which were new) were drawn from the data. Validation of the categories was achieved through direct observations of two design engineers in the week long Shadowing Study and completed this phase of the research. Mapping and interpretation of the findings in relation to the literature obtained further verification. From these analyses it was becoming evident that perceived barriers to creativity were present at many different layers of the enterprise from a macro, organisational level to the micro-environment of the individual design engineer. The final phase entailed the development of a conditional/consequential matrix model to illustrate the relationship between the macro and micro conditions, under which barriers to creativity were investigated, leading to the development of a theory. The final conclusions and suggestions for improvements demonstrate the relationship between high/low barriers and high/low creativity. The research has shown the benefits of taking an interdisciplinary socio-technical approach and has highlighted the importance and relevance of the social dimension, as well as the technological, in the investigation of engineering design.Rolls-Royce pl

A method and application of machine learning in design

This thesis addresses the issue of developing machine learning techniques for the acquisition and organization of design knowledge to be used in knowledge-based design systems. It presents a general method of developing machine learning tools in the design domain. An identification tree is introduced to distinguish different approaches and strategies of machine learning in design. Three existing approaches are identified: the knowledge-oriented, the learner-oriented, and the design-oriented approach. The learner-oriented approach is critical, which focuses on the development of new machine learning tools for design knowledge acquisition. Four strategies that are suitable for this approach are: specialization, generalization, integration and exploration. A general method, called MLDS (Machine Learning in Design with 5 steps), of developing machine learning techniques in the design domain is presented. It consists of the following steps: 1) identify source data and target knowledge; 2) determine source representation and target representation; 3) identify the background knowledge available; 4) identify the features of data, knowledge and domain; and 5) develop (specialize, generalize, integrate or explore) a machine learning tool. The method is elaborated step by step and the dependencies between the components are illustrated with a corresponding framework. To assist in characterising the data, knowledge and domain, a set of formal measures are introduced. They include density of dataset, size of description space, homogeneity of dataset, complexity of domain, difficulty of domain, stability of domain, and usage of knowledge. Design knowledge is partitioned into two main types: empirical and causal. Empirical knowledge is modelled as empirical associations in categories of design attributes or empirical mappings between these meaningful categories. Eight types of empirical mappings are distinguished. Among them the mappings from one multiple dimensional space to another are recognized as the most important for both knowledge-based design systems and machine learning in design. The MLDS method is applied to the preliminary design of a learning model for the integration of design cases and design prototypes. Both source and target representations use the framework of design prototypes. The function-behaviour-structure categorization of design prototypes is used as background knowledge to improve both supervised and unsupervised learning in this task. Many-to-many mappings and time- or order-dependent data are discovered as the most important characteristics of the design domain for machine learning. Multiple attribute prediction and the capture of design concept ‘drift’ are identified as challenging tasks for machine learning in design. After the possibilities and limitations of solving the problem by modifying existing learning methods (both supervised and unsupervised) are considered, a learning model is created by integrating several learning techniques. The basic scheme of this model is that of goal-driven concept formation, which consists of flexible categorization, extensive generalization, temporary suspension, and cognitively-based sequence prediction in design. The learning process is described as follows: each time one category of attributes is treated as the predictive feature set and the remaining as the predicted feature set; a conceptual hierarchy or decision tree is constructed incrementally according the predictive features of design cases (but statistical information is generalized with both feature sets); whenever the predictive or the predicted feature set of a node becomes homogeneous, the construction process at that branch will temporarily suspend until a new case arrives and breaks this homogeneity; frequency—based prediction at indeterminate nodes is replaced with a cognitively-based sequence prediction, which allows the more recent cases to have stronger influence on the determination of the default or predicted values. An advantage of this scheme is that with the single learning algorithm, all the types of empirical mappings between function, behaviour and structure or between design problem specification and design solution description can be generalized from design cases. To enrich the indexing facilities in a conceptual hierarchy and improve its case retrieval ability, extensive generalization based memory organizations are investigated as alternatives for concept formation. An integration of the above learning techniques reduces the memory requirement of some existing extensive generalization models to a level applicable to practical problems in the design domain. The MLD5 method is particularly useful in the preliminary design of a learning system for the identification of a learning problem and of suitable strategies for solving the problem in the domain. Although the MLDS method is developed and demonstrated in the context of design, it is independent of any particular design problems and is applicable to some other domains as well. The cognitive model of sequence-based prediction developed with this method can be integrated with general concept formation methods to improve their performance in those domains where concepts drift or knowledge changes quickly, and where the degree of indeterminacy is high

Design Reasoning Without Explanations

This paper proposes'connectionism'as an alternative to'classical cognitivism'in understanding design. In the process the author considers the difficulties encountered within a particular view of the role of explanations and typologies. Connectionism provides an alternative model that does not depend on the articulation of explanations and typologie