Abstract
In manufacturing environments, machine learning models are being built for several use cases, such as predictive maintenance and product quality control. In this context, the various manufacturing processes, machines, and product variants make it necessary to create and use lots of different machine learning models. This calls for a software system that is able to manage all these diverse machine learning models and associated metadata. However, current model management systems do not associate models with business and domain context to provide non-expert users with tailored functions for model search and discovery. Moreover, none of the existing systems provides a comprehensive overview of all models within an organization. In our demonstration, we present the MMP, our model management platform that addresses these issues. The MMP provides a model metadata extractor, a model registry, and a context manager to store model metadata in a central metadata store. On top of this, the MMP provides frontend components that offer the above-mentioned functionalities that are missing in existing systems and approaches. In our demonstration, we show two scenarios for model management in Industry 4.0 environments that illustrate the novel functionalities of the MMP. We demonstrate to the audience how the platform and its metadata, linking models to their business and domain context, help non-expert users to search and discover models. Furthermore, we show how to use MMP's powerful visualizations for model reporting, such as a dashboard and a model landscape view.
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