Turning Machine Data into Insight
Summary: The machines that are used to build plane parts are expensive to repair, buy, and run. In an attempt to reduce these costs, 50 machines were connected to sensors, but there was not an intuitive way for users to see historical data or aggregated data from these sensors. This product worked to remedy this problem. It could be used to see which machines were using resources (electricity) when no parts were being worked on and to determine whether work could be reallocated to other machines instead of purchasing new machines.
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Researcher, Visual and Interactive Designer
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I collaborated with data scientists, and engineers to determine what data indicated what statuses of each machine via qualitative interviews. Additionally, both the users of the machines and their managers were interviewed to determine what were common causes of machine downtime.
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The design was created, with careful consideration to the existing design system and design best practices. This included principles such as visual hierarchy, gestalt principles, and results from eye tracking studies.
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After the initial build, quality assurance was performed by both me and team members. This included querying a SQL database to see whether the product outputs matched the database. I also tested on individuals who were unfamiliar with the project to determine whether the visuals aligned with their understanding of machine utilization.
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This product has been used to assist in analysis allocation resources over 2,000 times and has allowed the company to buy fewer new machines.
