Article in Proceedings INPROC-2016-54

BibliographyTokola, Henri; Gröger, Christoph; Järvenpää, Eeva; Niemi, Esko: Designing Manufacturing Dashboards on the Basis of a Key Performance Indicator Survey.
In: Proceedings of the 49th CIRP Conference on Manufacturing Systems (CIRP CMS).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
Procedia CIRP; 57, pp. 619-624, english.
Elsevier, May 2016.
Article in Proceedings (Conference Paper).
CR-SchemaJ.1 (Administration Data Processing)
KeywordsDashboards; Key Performance Indicators (KPIs); Scorecard
Abstract

Target-oriented and real-time information provisioning across all hierarchy levels, from shop floor to top floor, is an important success factory for manufacturing companies to facilitate agile and efficient manufacturing. In general, dashboards – in terms of digital single-screen displays – address this challenge and support intuitive monitoring and visualisation of business performance information. Yet, existing dashboard research mainly focus on IT issues and lack a systematic study of the dashboard content. To address this gap, in this paper, we design three representative dashboards for manufacturing companies based on a comprehensive survey that focuses on suitable key performance indicators for different manufacturing target groups. The paper consists of three parts. First, the paper provides a literature review about design principles of dashboards. Second, it publishes the results of a survey of manufacturing companies on preferred key performance indicators (KPIs) for dashboards and the use of dashboards. Third, using the results obtained from the survey, three representative manufacturing dashboards are designed: an operational dashboard for workers, a tactical dashboard for managers and a strategy dashboard for executives. The results underline that different KPIs are preferred for dashboards on different hierarchy levels and that mobile usage of dashboards, especially on tablet pcs, is favoured.

Department(s)University of Stuttgart, Institute of Parallel and Distributed Systems, Applications of Parallel and Distributed Systems
Project(s)GSaME-NFG
Entry dateJuly 18, 2017
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