EfiMA

Efficient troubleshooting for safe, variant-rich machine and plant automation

Project description

In the field of variant-rich machine and plant engineering, heterogeneous and considerably differing machinery imposes high demands concerning professional competence of commissioning and maintenance staff. The involved personnel relies on own broad experience and analytical capabilities during all phases of the life cycle of a system, from initial assembly to commissioning, start up, maintenance, debugging and repair.

To mitigate this problem, EfiMA explores the possibilities of providing supportive measures by largely automated derivation of complete test routines as well as fault identification and correction support tools to increase machine and plant uptime and ensure safe operation. The test routines are automatically derived from technical documents, such as circuit diagrams and plant safety documentation.

Specialized tools developed for test execution and utilization of Augmented Reality subsequently intuitively guide maintenance staff through interactive test procedures. Such features additionally reduce deviations and improve overall test quality while providing detailed documentation by continuous logging.

Failures occurring during commissioning or operation are often difficult to be reproduced or even understood. To ease diagnosis of such plant errors, a method resembling a “flight recorder” on the automation level is to be developed. Combined with preassigned test procedures and linked engineering documents, it aims at supporting maintenance technicians in efficient defect localization and identification.

The concepts are developed in close cooperation with industry partners, thus ensuring industrial applicability and relevance of the approaches for systematic checking and troubleshooting of variant-rich machines and plants.

Industrial partners

- CIM-BASE GmbH Consulting und Engineering

- CODESYS GmbH

- DORST Technologies GmbH & Co. KG

- MULTIVAC Sepp Haggenmüller SE & Co. KG

- Zuken E3 GmbH

Support

Supported by the bayerische Forschungsstiftung (BFS).