Challenges and design of a data-oriented complaint and failure management

Abstract

Companies have to address several crucial issues to remain competitive in a fast developing, digitalised and connected world. Due to connected machinery and new sources of complaint and failure data the amount of acquired information is constantly increasing. Furthermore customer requirements experienced a strong tendency to individualised products which led to an increased data complexity. To process this kind of information and prepare it for sustainable improvements in production and product developments a data-driven design of an intelligent complaint and failure management (CFM) is inevitable. This paper builds up on existing approaches for CFM and outlines the global challenges which have to be addressed in terms of a continues improvement process. Therefore a data-driven reference process is introduced. Furthermore an integration of this process requires different enablers (e.g. IT infrastructure, failure coding, key performance indicator sets, etc.). To emphasise how the outlined challenges can be addressed in practice several concrete examples are sketched out. The central findings of this paper are a data-driven reference process for CFM just as the determination of the necessary tools and infrastructure. It exceeds the state-of-the-art process designs in terms of data orientation, the outlined enablers as the necessary supporting background.

Keywords:

• continuous improvement
• failure management
• classification

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The support of the German National Science Foundation (Deutsche Forschungsgemeinschaft DFG) through the funding of the research project ‘Gestaltungsmodell für Reklamationsbearbeitungsprozesse’ (SCHM 1856/20-1) is gratefully acknowledged.