TY - CHAP
T1 - Cyber-physical approach for integrated energy and maintenance management
AU - Neef, Benjamin
AU - Schulze, Christopher
AU - Posselt, Gerrit
AU - Herrmann, Christoph
AU - Thiede, Sebastian
PY - 2019
Y1 - 2019
N2 - 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”.
AB - 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”.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85062897838&partnerID=MN8TOARS
U2 - 10.1007/978-3-319-93730-4_6
DO - 10.1007/978-3-319-93730-4_6
M3 - Chapter
SN - 978-3-319-93729-8
T3 - Sustainable Production, Life Cycle Engineering and Management
SP - 103
EP - 125
BT - Eco-Factories of the Future
A2 - Thiede, Sebastian
A2 - Herrmann, Christoph
PB - Springer
CY - Cham
ER -