EASE-R3 focuses on the selection of the best maintenance strategy, including decommissioning, such as renovation, repair, re-use, according to the minimization of Life Cycle Cost (LCC) and Life Cycle Assessment (LCA) related parameters.
Once the selection is performed, EASE-R3 then investigates different technologies supporting maintenance tasks such as Augmented Reality (AR)-based, Virtual Reality (VR), Condition monitoring, etc.
Current maintenance policies can be useful in answering effectiveness questions such as “How can this particular machine be operated more efficiently?”,
EASE-R3 answers to the 5 top questions of effectiveness:. How can reliability, repair and EOL be included in a robust and integrated Life Cycle Cost and Life Cycle Assessment model of the factory?
PLATFORM A: Integrated Life Cycle Cost and Life Cycle Assessment platform based on Reliability & Maintainability simulations model and techniques Which are the most cost-effective and optimal Repair strategies we should tailor for sets of components/machines of the factory?
PLATFORM B: Repair Decision Support System platform for optimal cost-effective maintenance strategy selection Which machine and/or components should we improve and how can we reduce repair time and cost?
PLATFORM C: Seamless approach to reduce Repair time and cost of machines and components Which are the most environmental-effective EOL strategies we should tailor for sets of components/machines of the factory?
PLATFORM D: Decommissioning Decision Support System (DDSS) platform to select optimal and environmental effective EOL strategies How can we assess the remaining life of Re-usable components and which are most valuable Renovation technologies for the machine tools?
PLATFORM E: Enabling technologies for energy & cost effective Re-use and Renovation of machine tools
|Number of participants:||14|
|Total budget - Public funding:||6 212 662,00 Euro - 4 429 989,00 Euro|
|Call topic:||Innovative strategies for renovation and repair in manufacturing systems (FoF.NMP.2013-8)|
|Instrument:||Collaborative project (generic)|
Demonstrator 2 – DDSS Validation of Life Cycle Cost (LCC) analysis integrated with Life Cycle Assessment (LCA) and Decommissioning Decision Support System. The End OF Life (EOL) decision support requires the maintenance history of a machine tool . A special and dedicated SW module is in charge of collecting the necessary informations related to components directly from the machines control system.
Demonstrator 1 - RDSS Validation of Life Cycle Cost (LCC) analysis integrated with Reliability and Maintainability (R&M) simulation and Repair Decision Support System Tools/methods applies to evaluate the MTBF, MTTR and LCC of machines identified among end-users
- | FIDIA SPA (Coördinator)
- | Budapest University of Technology and Economics
- | Katholieke Universiteit Leuven
- | CE.SI CENTRO STUDI INDUSTRIALI DI TADDEI SIMONA MARIA EC SAS
- | CO.FI.PLAST Srl
- | IK4-IDEKO
- | Mach4 Lab Srl
- | NEWBURGH ENGINEERING CO LIMITED
- | Politecnico di Torino
- | RHEINISCH-WESTFAELISCHE TECHNISCHE HOCHSCHULE AACHEN - WZL
- | TEKS Sarl
- | THE UNIVERSITY OF HUDDERSFIELD
- | EKIN SOCIEDAD COOPERATIVA
- | WIRES ENGINEERING SRL
- | DIN DEUTSCHES INSTITUT FUER NORMUNG E.V.