L4MS | Logistics for Manufacturing SMEs
01-10-2017
-31-03-2021
01-10-2017
-31-03-2021
01-10-2017
-31-03-2021
THe evalaution and assessment of the equipment condition through the predictive manitenance and data analytics of the SERENA project will move towards the preservation of the production equipment in normal workiong conditions ensuring high quality products.
SERENA solutions on predictive maintenance and maintenance-aware scheduling are expected to reduce the overall ratio of cost to perfromance by the on-time scheduling of maintenance operations with the minimum intervention to the production schedule.
Production equipment uses a number of process resources to operate such as water, air, lubricants, other. In time maintenance activities wnabled by the SERENA predictive maintenance platfrom and optimising the scheduling of maintenance operations can have a significant impact on the consumption of such resources when the equipment is not in proper working condition.
The prediction of maintenance needs of the production equipment thorugh the predictive analytics and scheduling of the SERENA project is expected to reduce the defective workpieces caused by manufacturing equipments not in proper working condition.
The predictive maintenance solutions of the SERENA project are expected to contribute to the sustainability of the production equipment ot proper functional condition thus reducing the energy consumption that is present when machine's are close to the end of their life or in a need of maintenance.
Indutrial equipment not in proper working condition consumes greater quantities of input and operational sources than normal. The SERENA data-driven condition evaluation and prediction of potential failures will enabled the sustainability of the production machines to proper operational condition, thus contributing to reduced process resources.
01-10-2017
-30-09-2020
01-10-2017
-31-03-2021
PROGRAMS solution will allow to gain a “10% increased in-service efficiency through reduced failure rates, downtime due to repair, unplanned plant or production system outages and extension of component life.”
•reduced failure rates:All these aspects will reduce the costs related to maintenance activities, thus increasing the sustainability of the production process.
Precise determination of the RUL of components will allow to replace them before their status degrades production equipment performances beyond unacceptable levels.
Reducing failure rates and production equipment unavailability will improve factory productivity.
PROGRAMS solutions will allow a more widespread adoption of predictive maintenance as a result of the demonstration of more accurate, secure and trustworthy techniques at component, machine and system level. In fact one of the biggest obstacles is getting people to change long-held maintenance practices. PROGRAMS will:
PROGRAMS solution will increase accident mitigation capability”
01-06-2017
-31-05-2020
01-01-2021
-30-04-2024
01-01-2021
-31-12-2023
01-10-2016
-31-03-2021
01-10-2016
-30-09-2020
01-01-2015
-31-12-2017
01-01-2024
-31-12-2026
01-01-2024
-31-12-2026
01-04-2020
-30-09-2023
01-01-2024
-31-12-2025
01-01-2024
-31-12-2026
01-12-2023
-30-11-2026
01-01-2024
-31-12-2026
SERENA aims towards the data-driven condition evaluation of machine and production equipment, which through machine learning techniques can provide insight in the remaining useful life of the equipment enabling the avoidance of production stops and thus reducing its overall costs. The combination of data-driven and physics based techniques is envisioned to increase the reliability of the prediction and contribute to a high perfromance production without undesired interruptions.