Data-Driven Operator Behavior Visualiza-tion: Developing a Prototype for Wheel Loader
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Journal Title
Journal ISSN
Volume Title
Perustieteiden korkeakoulu |
Master's thesis
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Author
Date
2022-12-12
Department
Major/Subject
Human Computer Interaction and Design
Mcode
SCI3020
Degree programme
Master's Programme in ICT Innovation
Language
en
Pages
65+16
Series
Abstract
To ensure operators are working in a way that delivers optimum fuel efficiency and productivity to achieve optimum results on-site, the company aspires to create visual tools to keep track of operator behavior in the operator environment. Monitor operator behavior with key indicators then visualized to inform how this affects important results for the customers and for Volvo CE. The audience is operators themselves, and internal staff like UX engineers and Product owners. Data-driven concept design (DDCD) is a decision-making approach that heavily relies on collected data and highlights the need to proactively plan and design. It is a popular approach to capturing tacit customer needs and makes a great contribution to data visualization design. Also, an emerging concept like the digital twin provides inspired ideas in data visualization conceptual design. However, little research is on the DDCD for data visualization. Thus, this work aims to explore appropriate data visualization techniques under the DDCD framework. The result is to help Volvo CE, primarily via data visualization, keep track of operator behaviors, and how these affect wheel loader productivity and energy efficiency data on different levels and in a wider context. To carry out, A series of DDCD cases for the improvement of wheel loader operator behaviors are researched and designed, to present data in a clear and concise visual way for both internal audience and operator training. As the result, a prototype containing a series of visualization techniques is proposed for two target groups and corresponding application scenarios including coaching and aid decision-making. Created a series of dashboards with expected functionalities based on understanding the current machine. The prototype for the internal audience has functionality: site and time selection, weekly overview window, phase selection, cycle thread trace, insight window, data presentation, and toolbox. The prototype for operator training has functionality: site and time selection, opponent se-lection, phase selection, cycle thread trace, external data window, individual comparison section, and insights block.Description
Supervisor
Pauletto, SandraThesis advisor
Windlin, CharlesKeywords
data-driven concept design, data-visualization, user research, decision-making, digital twin
