Objective
Task 1: During this preparatory task all the details for the project start-up were identified. Thus, separate sections were dedicated to collect both requirements as well as to elaborate a draft of the infrastructures of the monitoring aspects, the diagnosis ones as well as the CNC implantation aspects. End users provided information on the relation among machines' functions and failures that are affecting these factions. The investigation was based on a questionnaire described inside the deliverable of this task. As described inside the project work program, the structure of the monitoring/diagnosis system is based on the OSACA standard.
Task 2: Based on data collected in task 1, where machine functions were linked to failures. During this task the combination of signal values describing a failure was investigated.
Based on this data, (collected inside a questionnaire included into the deliverable of this task), the main requirements for the monitoring module could be identified. For the two machines examined inside the project (GEMINIS lathe and Fidia milling machine) signals were divided into signals already available from the CNC/PLC and signals that needed external sensors or additional data acquire boards.
An OSACA gateway for the Fidia CNC capable to show CNC/PLC internal signal in an OSACA compliant way was created. OPC interfaces of personal computer data acquisition boards has been analysed. Also form them a gate to the OSACA platform has been implemented. The result of this development is that the monitoring module can be plugged into the OSACA platform and it can monitor machine failures collecting signal data independently from their source (type of numerical controller or card to collect sensor signal). A module to predict machine failures based on the trend analysis of available signals has been also designed. An additional module (Data Logger) was implemented. This module includes all required functions to perform a back up of signal data. Other applications can command to it a certain type of storing operation or the retrieval of stored data. Task results were validated by industrial partners by practical test of the above mentioned modules on the project demonstrators.
Task 3: During this task different modules were implemented. The purpose of these modules is to collect data from the OSACA interfaces to signals and provide to the machine operator the necessary instruction to repair a machine failure that has been reported by the monitoring module.
Once a failure occurs, a module helps the operator to describe what occurred on the machine.
A module that select the best diagnosis candidate out of explicit information (a fault tree analysis of the system) and a module that extract the best diagnosis candidate out of past experience (a similar case already solved) have been implemented. In co-operation with the interface to the user and to a module that extract also the information that is implicit into the PLC of the machine, these modules can provide the best diagnosis of an occurred failure. Once identified the failure by these modules, a repairing module guide the operator in repairing the failure and a test module will support the operator in controlling that the failure has been properly repaired. All modules are available in an edit version as well as in runtime version. The editor version can be used by the MTB to input all data to these modules (fault tree of the machine, repairing and testing data in different multimedia format). The runtime version is running on the controller. Task results were validated by industrial partners by practical test of the above mentioned modules. A minimum set of information describing machine failures and the related repairing and testing sequences have been given as input to them. The proper reaction of the system to a simulated failure has been tested.
Objectives and content
The main objective of the project is to increase the
ability of the machine tool operators to identify and
repair most of the faults in their machines. To
accomplish with this objective we must consider:
The development of inexpensive and configurable
monitoring modules.
To engineer diagnosis tools that employs all the
sources of information available and learn from past
experiences.
The fully integration of these tools in the CNC of the
machine.
To provide repairing instructions to the operator by
means of annotated CAD drawings, video, etc.
A methodology to select sensors, to create parameters
for the monitoring modules and to compile diagnosis data.
Information needed for the successful diagnosis of
typical machine failures must first be acquired with a
monitoring software tool capable of supporting various
types of sensors. This tool should deliver the maximum
amount of information with the minimum number of external
low cost sensors. It benefits from the new capabilities
of open CNCs with standard hardware like an integrated PC
offer.
Starting from these monitoring data, and in close
relation with the machine operator, the next step
provides a diagnosis about the actual problem. The
troubleshooting system employs explicit information
(expressed as rules and fault trees) and previous
experiences (by means of Case-based Reasoning) to find
out the most probable causes.Once the failure is
identified, the last step is to provide repairing
instructions to the machine tool operator. Multimedia
tools, integrated in the CNC of the machine, are provided
to accomplish with this goal.As ultimate resort, an
enhanced telephonic link permits to connect the technical
assistance service of the machine tool builder with the
advanced CNC, allowing the collaboration between the
machine operator and the expert technician to solve the
most complex situations.
Brite Euram III Areas covered by the proposals are:
1.1.6.M 1.4.2.M 1.4.1.S.
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 software
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering sensors
You need to log in or register to use this function
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
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.
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.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Data not available
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Funding Scheme
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.
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
10099 SAN MAURO
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.