Objective
Task 1.1. Decomposition of the Machine Tool for R&A analysis, machine tool builders and end-users view on critical components and events.
Task 1.2. Definition of suitable information required for R&A design, Life Cycle Cost trade-off analysis, choice of critical components, failures and needed signals for condition monitoring.
Task 1.3. Development of the REACH database SW and the link between the database and existing CAD systems.
Task 2.1. Definition of sampling plans and procedures for the machine tool builders and end-users data collection, preliminary analysis of the necessary statistical algorithms for components R&A evaluation.
Task 2.2. Definition and development of two test benches for accelerated life tests on machine tools critical components.
Task 2.3. Development of the CNC data acquisition SW for condition monitoring, integrating control internal signals and external sensors.
Task 3.1. Preliminary evaluation of collected data, development of an integrated test and simulation model for R&A performance evaluation and design platform, development of new R&A design guidelines and methodologies.
Task 3.2. Development of the condition monitoring modules for improvement of the R&A performances of existing machine tools, development of the lifetime estimating algorithms based on load history and of the MMI extension for parameterization and display of the results. This is a running task.
Task 4.1. Verification of the new design methodology, the integrated test and simulation model for R&A performances, redesign of machine tool parts.
Task 4.2. Verification of the developed Condition Monitoring system in the partners machine tools.
High maintenance costs and production losses resulting from machine breakdowns are pressing problems for today's manufacturers. In order to increase the reliability and availability (R&A) of machine tools and manufacturing systems, two major problems must be solved: - How to take the right design decision for maximum reliability, starting from the early stages of machine development? - How to continuously obtain in-process data about the actual state of the machine and its components as a basis for targeted and highly efficient maintenance? Both issues are closely linked. Taking the proper design decisions requires information about the behaviour of the machine components under realistic loads. These loads are today widely unknown, except for laboratory data which does not reflect actual load cases, load history and interdependencies between components. Based on a powerful system for large-scale measurements of real operating loads new design methods and supporting software-systems can close the information gap between machine tool design and real process loads. On the other hand, such a system can be used as well to continuously monitor the actual machine conditions during operation. Thus machine downtime for unpredictable breakdowns can be prevented. It is the objective of this project to improve the R&A of machine tools by using control-internal signals for solving the mentioned two problems. At modern machine tools signals of digital drives are easily accessible and can be processed by control-intemal software applications. This makes it easy to apply such a software to many machines at little costs. Thus these control-internal signals will be used by the here to be developed system in two ways: - for new design methodologies taking reliability and availability into account. This enables a prediction and planning of R&A supported by here developed software tools; and - for a condition monitoring system being directly implemented into the control and thus enabling direct access to important information. This also contains the data acquisition for the design process. It is expected that with the help of this integrated two-fold approach the following results can be achieve within a period of two-three years after the end of the project: - Increase of the actual average machine tool Availability from 90-93% to 99% - Increase of the actual average production systems Availability from 75-80% to 90-95% - Reduction of about 20% (for the end-users) of the operating, support and lack of production total costs.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences databases
- humanities history and archaeology history
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
- natural sciences computer and information sciences software software applications
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Coordinator
10095 GRUGLIASCO
Italy
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.