It is a truism that the amount of information being generated in the modern digital world is increasing at an exponential rate. This is influencing engineering as it is in other forms of business, as well as everyday life. Engineering has a significant visual dimension to it: drawings, diagrams, sketches, photographs, graphs are the everyday language of the engineer. Despite the prevalence of such visual information, the role that such information plays and how it affects, for example, how documents can be reused is an under-researched area. This thesis thus proposes the important role of visual representations and images for supporting informed decisions, in particular for complex domains such as Engineering Design. The particular context for this research is associated with in-service design knowledge and information requirements. The increasing number of actual products in-service, the requirement to create safe design solutions quickly, the amassment of service data and the importance of product services to organisational competitiveness are all increasing the information pressures upon Design teams. The pervasive nature of visual representations in Engineering Design and prevalent document information suggests that they are an important asset within document information resources. This research focusses upon the purpose of Engineering Design image utilisation for information processing, and hence supporting efficient decision making. Some of the additional challenges identified throughout this research are the immaturity of current image recognition technologies and thus limitations of automated media extraction tools for supporting Design Engineers. This is significantly contributed to by the complexity of the information media and formats that constitute design engineering information and the current knowledge management trend to capture information without clear “reuse” purpose. The methods used to conduct this research demonstrate the merits of underused techniques in design engineering such as storyboarding. This storyboarding method is used for investigating the facets of tacit knowledge and the underpinning cognitive processing of document information resources for critical Design Engineering informative content. The innovative research method developed provides a useful framework for the collection of rich data using simulated tasks. The data collection is a rich multi-stream recording of design engineers in industry conducting work based scenarios. In particular the focus is upon conducting efficient research in industrial working practices with minimal facing research time with design engineers and the rich data that can be collected from them in situ. This thesis illustrates that there are a number of pressing difficulties in reusing image media, both technical process related in nature. This is currently limiting the usefulness of valuable information resources in practice, but also significantly raises the information burden for design engineer. This thesis has attributed the value of reusing visual representations due to their important role in design engineering decisions. It has provided evidence of the intuitive and important human need for visual information to provide mental stimulation in particular for making confident design decisions. The storyboard research method has outlined an industrial data collection and decision coding framework that is reproducible and can be used to better understand human information processing, and thus supports the development of document information systems. Additional rich information utilisation patterns for design engineering document information have also been evidenced in the empirical research results provided. This thesis also provides practical industrial examples to suggest techniques that could overcome the current technological shortfalls limiting the “reuse” of visual information in documents for Design Engineers.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:698983 |
| Date | January 2016 |
| Creators | Carey, Emily |
| Contributors | Culley, Stephen |
| Publisher | University of Bath |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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