Real-time 3D visualization of queues with embedded ML-based prediction of item processing for a product information management system

Abstract

This paper showcases a prototype system for predicting and visualizing distributed product information queues at one of the largest global appliance companies, BSH Hausgeräte GmbH (BSH). A design science methodology is employed to develop a viable artifact (a prediction and visualization system) as a technology-based solution to an important and relevant business problem (product information updates in a distributed environment) using novel solutions (machine learning and visualization), to demonstrate the value of the design (through user interviews), and to disseminate the results to both technical and managerial audiences. The results contribute to the ongoing academic discourse regarding the applications of artificial intelligence to business and the practical development of prediction and visualization solutions for similar environments in terms of distributed environment complexity and company size.