Visual Analysis of Aluminum Production Data with Tightly Linked Views

Abstract

Monitoring, analyzing and determining the production quality in a complex and long-running process such as in the aluminum production is a challenging task. We aim to support production data exploration in the aluminum industry. To this end, we developed the first version of the interactive visual analytics tool ADAM. The main aspect of concern is product quality, which is obtained from the quality inspection of aluminum plates at the end of the production process. A set of tightly linked views of production parameters with cross-filtering capability support the inspection of factors possibly influencing the product quality. ADAM allows highly responsive forward and backward search in the quality and production parameter space, leading to an understanding of important parameters, and supporting production planning and process improvement. Our approach was designed in an iterative development cycle guided by domain requirements from a major aluminum producer. We introduce the domain problem, propose a visual analytics design to support the problem, and demonstrate by application to real production data the usefulness and possible insights which can be obtained.