Because of nowadays complex and highly automated industrial production lines, every stoppage involves the danger of a massive economic harm. That’s why companies use already various production, quality and maintenance methods to reduce—or at least to handle—unforeseen stoppages. This paper presents a novel approach to improve the reliability of production fields by supporting predictive maintenance under the combination of systems from energy and maintenance management. Wireless sensor networks and mobile devices are integrated into a cyber-physical system to gain real-time transparency of energy demands within production environments. Being aware of challenges introducing cyber-physical systems into the brownfield, the proposed solution considers needs of data standardisations, IT security, staff participation, big data handling, long-term technical risk and cost-benefit estimations. The developed methods are considered by user-oriented design principles to deliver role-specific information. Therefore, the derivation of these informational requirements is based on production unique job activities. Allocating time and component-based energy demands whilst taking machine and environmental conditions into account enables a basis of comparison and a continuous improvement process of energy efficiency and maintenance. These demands are fulfilled by the methods of a continuous energy value stream mapping, an energy efficiency tracker and an integrating energy and maintenance monitoring. This proposed approach is based on the ESIMA project funded by the German Federal Ministry of Education and Research. The project aims for “Optimised resource efficiency in production through energy autarkic sensors and interaction with mobile users”.
|Title of host publication||Eco-Factories of the Future|
|Editors||Sebastian Thiede, Christoph Herrmann|
|Place of Publication||Cham|
|Publication status||Published - 2019|
|Name||Sustainable Production, Life Cycle Engineering and Management|