Modular Data Analytics as a Tool for Citizen Data Scientists in Quality Management

Abstract

The vision of Industrial Data Science to link data along the entire value chain with data from the product life cycle contains great potential for holistic quality improvements. In order to be able to exploit this increasing potential, tools and evaluations as well as the qualification of experts in quality management in the field of Industrial Data Science are essential. A promising approach is the generalisation and modularisation of data analysis processes, which can be reused in Quality Management for similar analytics tasks of different data sources in this discipline. With an appropriate integration into the company’s processes and easy accessibility of the generalized analytics modules, this approach promises to reduce the complexity and difficulty of data analysis. In this paper a total of seven different exemplary analysis modules that quality management experts can use to handle, visualise and analyse new data in Field Quality Surveillance. These are provided as part of a research project via a browser-based platform that enables users to perform data analyses without the use of other software or programming knowledge. The analysis modules are a central building block for supporting Quality Management experts to act as Citizen Data Scientists. In addition, skills training and general change management for organisational restructuring must go hand in hand with the use of the modules in order to achieve valid analytics results quickly.