Title :
Rule Cubes for Causal Investigations
Author :
Blumenstock, Axel ; Schweiggert, Franz ; Müller, Markus
Author_Institution :
Univ. of Ulm, Ulm
Abstract :
With the complexity of modern vehicles tremendously increasing, quality engineers play a key role within today´s automotive industry. Field data analysis supports corrective actions in development, production and after sales support. We decompose the requirements and show that association rules, being a popular approach to generating ex- planative models, still exhibit shortcomings. Recently proposed interactive rule cubes are a promising alternative. We extend this work by introducing a way of intuitively visualizing and meaningfully ranking them. Moreover, we present methods to interactively factorize a problem and validate hypotheses by ranking patterns based on expectations, and by browsing a cube-based network of related influences. All this is currently in use as an interactive tool for warranty data analysis in the automotive industry. A real-world case study shows how engineers successfully use it in identifying root causes of quality issues.
Keywords :
automobile industry; computational complexity; data analysis; interactive systems; automotive industry; causal investigations; cube-based network; field data analysis; interactive tool; ranking patterns; vehicles complexity; warranty data analysis; Automotive engineering; Data analysis; Data engineering; Data mining; Information processing; Information technology; Mining industry; Production; Vehicles; Warranties;
Conference_Titel :
Data Mining, 2007. ICDM 2007. Seventh IEEE International Conference on
Conference_Location :
Omaha, NE
Print_ISBN :
978-0-7695-3018-5
DOI :
10.1109/ICDM.2007.29