Gearbox failures cost thousands of lost production hours in plants that use industrial robots. In this context, an automated monitoring system that can warn the user of an impending failure can save precious resources. This problem has been addressed in many other domains through the use of machine learning approaches. However, standard machine learning algorithms are limited in their ability to detect gearbox failures, mainly due to task variability arises from robot-specific data. To improve detection performance of machine learning approaches, in this paper we propose techniques to curate the data prior to building a classification model. In a systematic hypothesis-driven study exploring the effect of different preprocessing techniques, we evaluate training data augmentation with estimated measurements, data differencing to suppress task dependence, inclusion of local variation, and selection of principal components on data collected from 26 industrial robots from the field. Our results show that preprocessing techniques improve the failure detection performance.

In this paper a graphical approach for Condition Monitoring Systems (CM) based on Model Driven Architecture is presented; in particular, the software application “Smart Monitoring Agent” or SMA. This graphical approach starts from the idea of modeling, applying and visualizing non-hierarchical relations. The presented method makes use of well-defined data models that take the solution to a superior level of configurability, using only graphical tools. Finally it is explained how this approach enables the flexible knowledge exchange between condition monitoring experts and software engineers.

During the last few years, software product line engineering has gained significant interest as a way for creating software products faster and cheaper. But what architecture is needed to integrate huge amounts of products, from different product lines? This paper describes such an architecture and its support processes and tools. Through cases, it is illustrated how the architecture is used to integrate new --- and old --- products in such diverse integration projects as vessel motion control, airport baggage handling systems, pulp&paper and oil&gas, in a very large organization. However, in a large organization it is a challenge to make everyone follow an architecture. Steps taken to ensure global architectural consistency are presented. It is concluded that a single architecture can be used to unify development in a huge organization, where the distributed development practices otherwise may prohibit integration of various products.