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PREDICTIVE INTELLIGENT MACHINING AND
MACHINE MONITORING SENSORS
This proposal is prepared with the help of an Exploratory Award which included a Feasibility Study.
Tool and machine condition monitoring is of vital importance to modern industry in its quest for high reliability, quality and efficiency. Machine maintenance is also a major expense throughout every industrial sector. It has been shown that effective predictive maintenance can result in an 8% maintenance cost saving and a further 8% increase in productivity [1]. These figures are borne out across Europe, as shown by the European Benchmark Study on Maintenance [2]. Most condition monitoring systems are unnecessarily complex since they aim to diagnose the nature of faults within machines. For efficient asset management however diagnosis of the nature of a fault is not required. Instead plant operators need to know which machines have problems, where they are and how long specific machines will last before faults lead to terminal failure. The purpose of this project is to develop the understanding to allow a permanently installed instrument to be developed capable of providing an output of remaining life of each bearing or gear within a machine.
The opportunity to be taken advantage of and its relevance to SMEs This project aims to advance the technology currently available for machine condition monitoring by the application of intelligent sensor systems. In particular, this project aims to develop an intelligent acoustic emission (AE) sensor system which will be capable of predicting number of days to failure for a particular machine. The system will primarily take data from AE sensors but will also use vibration and temperature data; an intelligent software module will combine the information to provide a more accurate representation of current machine condition. Such a system will have particular relevance to many SMEs, including the core proposers.
Although it is not possible to develop vibration techniques alone to achieve this goal, the acoustic emission (AE) approach seems ideally suited. In the last three years the high frequency AE technique has been shown to provide a very powerful yet simple means of identifying machines with problems at an early stage.
This is particularly relevant for SMEs in two ways: firstly, the technological and cost problems related to vibration-based condition monitoring systems have proven a major barrier to the uptake of the technology in SMEs, and hence this sector is realising only a fraction of the potential benefits of condition monitoring; and secondly, the proposed system will be aimed specifically at the common plant types used by SMEs (eg gearboxes and machine tools), with a cost level for the system which will make it affordable by SMEs.
1. OBJECTIVES AND STATE-OF-THE-ART
1.1 Industrial, Economic and Social Objectives and Expected Achievements
to be overcome Tool and machine condition monitoring is of vital importance to modern industry in its quest for high reliability, quality and efficiency. In a study [Kuhmonen, M. Dissertation 1997] [3] of four FMS systems including 17 machine tools it was found that the utilization rate was only 68,3% of the planned operating time, due to technical faults (4.3%) or operational faults (9.4%) or organizational disturbances (17.9%). Machine maintenance is also a major expense throughout every industrial sector. It has been shown that effective predictive maintenance can result in an 8% maintenance cost saving and a further 8% increase in productivity [1]. Most condition monitoring systems are unnecessarily complex since they aim to diagnose the nature of faults within machines. For efficient asset management however diagnosis of the nature of a fault is not required. Instead plant operators need to know which machines have problems, where they are and how long specific machines will last before faults lead to terminal failure.
The utilization rate of a machine tool can be improved by an advanced condition monitoring system using modern sensor and signal-processing techniques. In unattended machining, process and tool condition monitoring (tool identification, tool wear monitoring and tool breakage detection) has great potential for increasing the capacity of the machine tool systems. However, existing real time tool monitoring techniques for machine tools do not yet provide satisfactory information.
The purpose of this project is to develop a permanently installed instrument to be developed capable of predicting the remaining life time of tools and of providing an output in remaining life of bearings or gears within a machine.
The opportunity to be taken advantage of and its relevance to SMEs This project aims to advance the technology currently available for tool and machine condition monitoring by the application of intelligent sensor systems. In particular, this project aims to develop an intelligent acoustic emission (AE) sensor system which will be capable of predicting remaining life for a particular machine, and an intelligent multi-sensor tool monitoring system capable of predicting remaining tool life. The machine monitoring system will primarily take data from AE sensors but will also use vibration and temperature data; an intelligent software module will combine the information to provide a more accurate representation of current machine condition. Although it is not possible to develop vibration techniques alone to achieve this goal, the acoustic emission (AE) approach seems ideally suited. In the last three years the high frequency AE technique has been shown to provide a very powerful yet simple means of identifying machines with problems at an early stage. In addition to AE, the tool monitoring system will use data from other sensors such as vibration, force measurements, power consumption, and sound measurement such that the existing sensors in the machine tools will be utilized as much as possible.
A CETIM survey [4]shows that monitoring is not well developed in SMEs in the mechanical industies covered, partly due to the technical complexities of the monitoring techniques. Vibration analysis, the most popular method, is difficult for SMEs to develop because of the difficult methodology in taking good measurements, the lack of information on vibration alarm thressholds, and the resources required to monitor vibration over time. Other techniques such as infrared thermography are seen as too expensive for SMEs to implement.
This project is particularly relevant for SMEs in two ways: firstly, the technological and cost problems related to vibration-based condition monitoring systems have proven a major barrier to the uptake of the technology in SMEs, and hence this sector is realising only a fraction of the potential benefits of condition monitoring; and secondly, the proposed system will be aimed specifically at the common plant types used by SMEs (eg gearboxes and machine tools), with a cost level for the system which will make it affordable by SMEs.
Description and quantification of RTD goals
A aim of the project is to develop an intelligent sensor system which will autonomously extract the underlying curves of Distress and dB levels, using intelligent techniques to remove overlying effects due to machine stoppages and start-ups, process interactions etc., and extrapolate from its current position to enable prediction of the ultimate point at which machine failure will occur. This will be done by using a hybrid of expert systems and neural network technologies. Since the resulting system will be used for both early warning of machine problems and alarming of imminent failures the AE signal will be supplemented with temperature, vibration and other data where appropriate (eg in the machine tool enviroment) to provide the maximum confidence as terminal failure approaches. (Note: temperature and overall vibration are too insensitive to provide early indications of problems, but are very reliable indicators of terminal failure). In order to achieve some of these objectives the project will integrate some of the developments of the FMS-MAINT project as appropriate.
A summary of the objectives of this project are :
-To develop an affordable multi-channel intelligent AE sensor system.
- To develop an intelligent multi-sensor tool condition monitoring system.
Integration of the two systems as appropriate.
-To use artificial intelligence (AI) techniques such as neural networks and expert systems to develop software which will provide a prediction of the remaining life of bearings and gears.
- To research and develop techniques for data fusion, and to produce a detailed research review of these techniques.
-To test the techniques in a real application environment, to provide a benchmark of system performance
-To develop the results of the research in the form of a commercial, exploitable product.
-To publish the findings widely so that adoption across a wide sector is possible.
Prime industrial and
economic objectives The quantifiable objectives of the project are:
-to reduce maintenance costs of SMEs by 50-80%;
- to increase the ulitisation rate of machine tools in SMEs by at least 10%;
- to reduce failure events by 50-60%;
- to increase the service life of machines by 20-30%;
- to reduce production stoppages due to mechanical failures by 50-60%.
Pre-competitive Character The project is pre-competitive because a period of between 9 and 15 months will follow the completion of the research to enable full field trials at client sites throughout Europe to validate the end hardware and software products, and to produce commercially packaged and marketable products. Thereafter, a number of potential products are envisaged, including sensors, modular monitoring systems, software, and full integrated systems. These will be exploited by the SME partners in different ways.
Compliance with the Scope
and Objectives of the
Programme The research fits Areas 1.4.2.M, 1.4.3.M, and 1.4.4.M of the Industrial Materials and Technologies Workprogramme.
1.2 State-of-the-Art and Degree of Innovation
State-of-the-Art
In unattended machining, process and tool condition monitoring (tool identification, tool wear monitoring and tool breakage detection) has great potential for increasing the capacity of the machine tool systems. Existing real time tool monitoring techniques for machine tools do not yet provide satisfactory information, since they do not cover the wide range of different machining situations and machining parameters that normally take place in practice, and they exploit only a limited number of the capabilities of modern sensor and analysis techniques [Kluft 1985, Jantunen et al 1996] [5,6]. It has been shown that vibration, sound and acoustic emission measurements are more reliable for tool wear monitoring than the most common methods, such as power consumption, current and force measurements used in commercially available systems [Jantunen & Jokinen 1995] [7].
In a recent European research project [8] a new approach for tool condition monitoring was developed, utilizing multi-sensor information with a rule-based expert system and an approach based on the adoption of fault and symptom tree databases with sophisticated user interfaces which were used for the definition of relevant fault types together with corresponding monitoring methods. The system is modular and this approach makes it easy to configure the expert system for different types of FM-systems or stand-alone NC machines with different types of tools. However, no commercially available product has yet been developed on the basis of this concept. Such a tool monitoring system utilizing a hybrid expert system including methods based on artificial intelligence such as neural networks or fuzzy logic in addition to the rule-based system would be extremely adaptable to the widely varying machining situations and parameters in normal practice, due to the inherent self learning ability.
Most machine condition monitoring systems in use in industry are based on vibration measurements, with secondary parameters such as temperature, pressure, and relative displacement being measured where appropriate. These systems are unnecessarily complex since they aim to diagnose the nature of faults within machines. For efficient asset management however diagnosis of the nature of a fault is not required. Instead plant operators need to know which machines have problems, where they are and how long specific machines will last before faults lead to terminal failure.
Traditionally vibration analysis has been the most advanced condition monitoring technique but its use is very complex due to the need for sophisticated frequency analysis and detailed machine specific information. For this reason the University of Sunderland (Project Co-ordinator and an RTD performer in this project) have pioneered the application of AI to this complex diagnosis. Even so the technology is still reliant upon diagnosing the nature of machine faults and as a result solutions can be specific to narrow categories of machines. By contrast the AE approach has been shown to allow a generic identification of faulty machines across virtually all rotating machines and fault types. Portable instruments manufactured by Holroyd Instruments are commercially available to do this. The trending of information from such instruments to reveal the proximity of final failure is possible but is labour intensive, requiring conscientious data taking and trend analysis. Increasingly the end-users of CM (eg utilities and the manufacturing industries) are reluctant to invest in such labour intensive routines and the pressure is growing for permanently installed systems which do not require any operator skills. Neural network technology is being applied to this form of monitoring by many researchers with varying degrees of success. Networks have been successfully trained on fault conditions and have responded when the faults re-occur. A system has also been developed which following training only on good condition data can diagnose faults in the machine. The University of Sunderland has extensive experience in this area [9, 10], and is currently a partner in an IMT project (VISION - BE95-1313) [11] which is using neural technology for analysing data from larger plant.
The purpose of this project is to develop the required understanding to allow a permanently installed instrument to be developed capable of providing an output in remaining life of each bearing or gear within a machine.
Technical limitations of existing products and techniques
The major limitations of existing products and techniques are:
l their reliance on a limited number of measuring parameters in tool condition monitoring, power consumption, current and force measurements being the prime parameters measured;
l their associated incapability of reliable prediction of tool wear;
l their reliance on vibration as the prime parameter for measurement in machine condition monitoring;
l the associated problems of sensor configuration and measurement point;
l the problems involved in vibration data analysis and interpretation;
l the relatively high capital cost of vibration monitoring equipment and software.
As a consequence, market penetration of such systems, particulaly in SMEs, throughout Europe is still very low.
Results of the
Literature Survey The literature survey which was carried out for this project revealed the following:
l 69 national and European projects, and some 188 published papers, were evaluated by CETIM, and very few (one project and no papers) discussed the use of acoustic emission for gear monitoring.
l However, the feasibility report which accompanies this proposal shows that their is much in the literature to indicate that acoustic emission is a better paramter than vibration for many monitoring applications;
l The feasibility report discusses many application examples from literature, including rolling element bearing, plain bearing, and gear monitoring.
More detail on the results of the literature survey can be found in the enclosed Feasibility Report.
Results of the Research
Feasibility Study The feasibility study carried out for this project showed that:
l Acoustic emission can often be a better parameter for monitoring machines in noisy environments than vibration;
l It is believed to be technically feasible to develop a sensor and hardware system for both general rotating machinery and for machine tools;
l Neural networks offer an improvement over current techniques in predicting remaining life with this type of data.
The results of the feasibility work are extensively covered in the enclosed Feasibility Report.
Innovation in the project This project is innovative in the following respects:
l The ability to provide a display of the remaining life of a machine by extrapolating from current measurements.
l The ability to provide an indication of the need for tool change based on real-time monitoring of tool wear.
l The achievement of this without the need for any skilled operator input or interpretation through the use of residual life models, artificial intelligence and related techniques.
l The fusion of information from different sensor types (predominantly acoustic emission, but also others such as vibration and temperature) where appropriate so as to extract the most useful data from each input.
Figure 1 below shows a simple schematic of the envisaged system.
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Figure 1 - A simplified view of the proposed system
Complementarity with other
European research Work done in the EUREKA MAINE Project FMS-MAINT (Integrated Condition and Machine Process Monitoring System for Flexible Manufacturing Systems (FMS) and for Stand-Alone NC-Machne Tools - Project No. EU744) forms a good basis for the development of the tool condition monitoring system. The literature survey identified 69 national and European projects have been identified on the monitoring of machines. These are broken down as: EC - 22 projects; Germany - 30 projects; France - 1 project; UK - 1 project. Out of these only eight are about bearing and gear monitoring, and only one is on the use of acoustic emission techniques.
In particular the Brite-EuRam project BRE20949 project is seen as having an influence on the work proposed here. The project is complementary to the BRE20949 project because it combines acoustic emission and vibration monitoring, although it aims at the petrochemical industry predominantly and does not appear to address the machine tool market.
2. SCIENTIFIC & TECHNICAL WORK CONTENT
2.1 Research Approach and Methodology
Brief outline of the
research approach It is not possible to develop vibration techniques alone to achieve the goal of production of a system which will output a simple "days to failure" prediction for bearings and gearboxes, the Acoustic Emission (AE) approach seems ideally suited to the task. In the last three years the high frequency AE technique has been shown to provide a very powerful yet simple means of identifying machines with problems at an early stage (shown schematically in Figure 2). The AE technique has also been shown to provide relatively simple exponentially increasing trends as failure approaches (shown schematically in Figure 3). The underlying curves of Figures 2 and 3 are found to be common across virtually all bearings and gears in rotating machines.
This project will develop an intelligent sensor system which will autonomously extract the underlying curves of Figures 2 and 3 (removing overlying effects due to machine stoppages and start-ups, process interactions etc.) and extrapolate from its current position to the ultimate machine failure. This will be done by using hybrid expert systems and neural network technologies. Since the resulting system will be used for both early warning of machine problems and alarming of imminent failures the AE signal will be supplemented with temperature and vibration data to provide the maximum confidence as terminal failure approaches. (Note: temperature and overall vibration are too insensitive to provide early indications of problems).
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Figure 2 - "Distress" curve
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Figure 3 - dB curve
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2.2 Appraisal of the Level of Technical Risk
Critical appraisal of risk
and factors which may
influence success The high-risk factors in this project are:
· that insufficient data is available from real machines systems in order to effect an adequate statistical analysis of the behaviour and interaction of the various monitored parameters
· that it will not be possible to develop or refine the AE sensors, in the time available
· that the interaction of the parameters is so complex that it is not possible to develop adequate models of the system, and hence be able to predict system behaviour and offer prognosis
· that any resulting system is not practicable through costs considerations
· that machine operators may be reluctant to implement systems
However, the SME participants, the together with the specified R&D performers, have examined these risks carefully and believe that it will be possible to produce systems which meet the concerns of the machine operators and will be affordable and attractive in the market place.
Project Flow Diagram Figure 4 below shows the general flow of activity within the project:
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Figure 4 - General Flow of Activity in the Project
2.3 Description of the Tasks in the Technical Programme
Technical Programme:
Workpackage Definitions The project has been divided into 11 workpackages. The workpackages are:
WP 1: Set Up Data Acquisition Systems
WP 2: Collect Test Data
WP 3: Analyse Test Data
WP 4: Develop Analytical Methods and Models
WP 5: System Design
WP 6: Software Development
WP 7: Definition and Development of Tool Monitoring
System Modules
WP 8: System Integration
WP 9: Dissemination
WP 10: Exploitation and Marketing
WP 11: Project Management
Each of these workpackages has been broken down into a specific set of tasks, and the project partners who will carry out the work have been identified. The deliverables for each workpackage have been specified and a workpackage leader assigned. These are detailed below.
Work Package 1 - Set Up Data Acquisition Systems
Technical Objective: To specify, install and commission sensor and data acquisition systems at the various end user sites.
Description of Technical Work: The data acquisition systems to be used in the project will be modified versions of the MHC Memo system (to be purchsed by the appropriate user companies) or alternative systems to be used for laboratory testing by VTT and Cetim. The modified MHC Memo will give analogue voltage outputs for Distress and dB level. The data acquisition systems will be installed and commissioned at two sites in France, and for a period of time at each of the user sites in Finland. This work is essential to ensure that the data coming from the systems is validated and shown to be consistent before comparisons and analysis are carried out, and therefore allows the test programme to be carried out with confidence.
Note that VTT have a higher input in effort in this workpackage due to the fact that there are a hgher number Finnish companies in the project, and the effort required to set up the data acquisition system with these partners, particularly since the data acquisition system which is to be jointly purchased will be moved periodically between these companies. Also note that the individual effort of each of the end-user companies is relatively small, this does not reflect the importance of their input to the project, which is crucial since the data collected forms the essence of the analysis and modelling which is to be performed. This comment also applies to WP2.
WP Leader: HIL Resources: 5.2 man months
Start Month: 1 End Month: 3
Partner Man Months Contribution
HIL 0.6 Specification, installation and commissioning of test equipment
Cetim 0.2 Specification, installation and commissioning of test equipment
VTT 2 Specification, installation and commissioning of test equipment
Lehtosen Konepa 0.3 Access to plant; installation of test equipment and validation of data
Muottipiste 0.3 Access to plant; installation of test equipment and validation of data
Rej 0.3 Access to plant; installation of test equipment and validation of data
Toolman 0.3 Access to plant; installation of test equipment and validation of data
Teras-Astra 0.3 Access to plant; installation of test equipment and validation of data
Laske 0.3 Specification, installation and commissioning of test equipment
Avionics 0.2 Access to plant; installation of test equipment and validation of data
APV France 0.2 Access to plant; installation of test equipment and validation of data
FOC Transmission 0.2 Access to plant; installation of test equipment and validation of data
Work Package 2 - Collect Test Data
Technical Objective: To collect the necessary test data from the laboratory test arrangements and, most importantly, from the designated machines at the end user sites throughout Europe.
Description of Technical Work: The data required in the project to develop the analytical models and methods, and to determine the signal limit definitions, will be collected in this workpackage. Some data will be acquired from appropriate existing test arrangements at Cetim and VTT; however the most important data will be acquired from the project end users in Finland and France. Since this data will be real-world data, it is essential that this is of the highest quality, sufficient quantity, and contains all the representative information for various typical faults which will be required to develop robust analytical tools and methods in later workpackages. Specific data collection programmes will be compiled for each site. Note that the difference in effort between the Finnish and French partners is largely due to the fact that the French systems will be fixed installations and require less re-configuration, whereas the Finnish system is to be shared and requires more effort. Also note that the relatively small levels of effort do not reflect the importance of the contributions of all of the industrial partners, which are essential to provide the data on which the analysis and modelling will be based.
WP Leader: Cetim Resources: 19.3 man months
Start Month: 2 End Month: 24
Partner Man Months Contribution
HIL 0.6 Advice on data acquisition equipment configuration, data validation
UoS 0.3 Advice on data requirements for modelling
Cetim 1.1 Data validation and fault specification , collection of data from laboratory and end user sites
VTT 4 Collection of data from laboratory and end user sites; data validation
Lehtosen Konepa 2.3 Access to plant, validation of data
Muottipiste 2.3 Access to plant, validation of data
Rej 2.3 Access to plant, validation of data
Toolman 2.3 Access to plant, validation of data
Teras-Astra 2.3 Access to plant, validation of data
Laske 0.5 Advice on data acquisition equipment configuration; data validation
Goodview 0.1 Data validation
Avionics 0.6 Access to plant, validation of data
APV France 0.3 Access to plant, validation of data
FOC Transmission 0.3 Access to plant, validation of data
Work Package 3 - Analyse Test Data
Technical Objective: To analyse the acquired test data in order to determine the optimum parameter monitoring requirements for the final system.
Description of Technical Work: The test data will be analysed using a series of statistical techniques to look for correlations between variables, and in particular to look for multi-parametric, non-linear relationships which are believed to exist. A variety of tools such as MiniTab and MatLab will be used, and the results will form the basis of decisions on how to pre-process the data and which features will be extracted to give the most efficient representation while performing effective diagnosis. In addition, research will be carried out into analytical techniques to transform this data into useful information. This will include the use of artificial intelligence techniques, particularly adaptive computing paradigms such as neural networks and neuro-fuzzy systems.
WP Leader: UoS Resources: 4.9 man months
Start Month: 3 End Month: 10
Partner Man Months Contribution
UoS 2.5 Analyse data to establish relationships within data and determine pre-processing requirements; collate analysis of other partners and report
Cetim 0.4 Analyse data, particularly for residual life modelling
VTT 2 Analyse data, particularly for wear and residual life modelling
Work Package 4 - Develop Analytical Methods/Models
Technical Objective: To develop the analytical models, such as residual life models and intelligent, predictive methods, required in the project.
Description of Technical Work: The project requires advanced models for prediction of residual life in of machine tools and components such as bearings, gears, and spindles to be developed. These will be based on techniques developed by VTT and Cetim, but will be extended and modified in the light of the data collected in the project. The project requires advanced predictive models using intelligent techniques such as neural networks. These models will be developed as extensions of work carried out by the University of Sunderland, using tools such as NeuralWorks, Matlab and NeuFrame.
WP Leader: UoS Resources: 6.1 man months
Start Month: 2 End Month: 13
Partner Man Months Contribution
UoS 2.5 Development of analytical methods
Cetim 0.6 Development of residual life models
VTT 3 Development of analytical methods and wear models
Work Package 5 - System Design
Technical Objective: To describe and design the modular system based on the outcomes of workpackages 1 to 4, and the state-of-the-art in hardware and software development. The outcome of the workpackage will be a system specification, based on end user requirements and technical feasibility.
Description of Technical Work: The project will develop modular systems, building on previous developments of a number of the SME and R&D partners. How the final system will operate will be determined in this workpackage. An end user specification will be drawn up, based on the requirements of the end users in the project. The current state-of-the-art in modular systems design, including developments from within the consortium, will be considered, and a system specification will be devised with defined deliverables in terms of hardware, software, and system outputs.
WP Leader: HIL Resources: 4.4 man months
Start Month: 1 End Month: 12
Partner Man Months Contribution
HIL 0.5 Develop system specification based on end user requirements, particularly the AE sensor and signal processing elements
UoS 0.4 Develop system specification based on end user requirements, particularly the software elements
VTT 1 Develop system specification based on end user requirements
Lehtosen Konepa 0.3 Specify end user requirements; validate system design
Muottipiste 0.3 Specify end user requirements; validate system design
Rej 0.3 Specify end user requirements; validate system design
Toolman 0.3 Specify end user requirements; validate system design
Teras-Astra 0.3 Specify end user requirements; validate system design
Laske 0.5 Develop system specification based on end user requirements
Goodview 0.1 Develop system specification based on end user requirements, particularly the software elements
Avionics 0.4 Specify end user requirements; validate system design
Work Package 6 - Software Development
Technical Objective: To design and develop the required software based on the information gained in WP1, WP2, WP3, WP4, and WP5.
Description of Technical Work: This workpackage will require the design and development of the data storage devices and formats required for the project. The software implementation of the residual life models as well as the various intelligent software components for analysis and interpretation of the data will be designed and developed, taking into account the feasibility work and the work in WP3 and WP4. The user interface will be developed, as will the system output formats, including any direct outputs to feedback control systems. Most of the software engineering effort will use a methodology based around rapid prototyping in order to iteratively take on board the comments of the end users and SMEs involved in the project. Effort in this workpackage will take full account of the exploitation requirements of the main exploiters.
WP Leader: UoS Resources: 6.7 man months
Start Month: 8 End Month: 19
Partner Man Months Contribution
HIL 0.3 Input into software design
UoS 5 Design and write prototype software modules, and integrate
Laske 0.3 Input into software design
Goodview 0.1 Input into software design
VTT 1 Input into software design
Work Package 7 - Definition and Development of Tool Monitoring System Modules
Technical Objective: To define the fault and symptom tree modules for the current applications and to develop the software module for the tool condition diagnostics, and to integrate the machine monitoring and tool monitoring PIMMS systems where appropriate.
Description of Technical Work: In this workpackage the existing fault and symptom tree modules, developed in the EUREKA FMS MAINT -project, will be defined and configured to suit to the machine tool applications in the participating SMEs. Test data from the SMEs will then be used to set the limits for the signals, to be used in the diagnostics. The data obtained in WP1 - WP5 will be used in designing and developing the software module that carries out the tool condition diagnosis, applying both rule based methods as well as other techniques based on articial intelligence. When the tool condition monitoring modules are complete, they will be integrated with the machine monitoring modules where appropriate. This may involve both hardware and software components, especially those specific to the diagnosis of particular types of faults in the machine tool environment.
WP Leader: VTT Resources: 8.1 man months
Start Month: 3 End Month: 19
Partner Man Months Contribution
HIL 0.3 Input into integration, particular with respect to integrating the AE sensors and signal processing hardware
UoS 3 Input into evaluation; software design and integration
Cetim 0.1 Input into integration, particularly hardware
VTT 3.8 Fault and symptom tree module definitions; software design; software and hardware integration
Laske 0.3 Input into integration
Goodview 0.2 Input into software design and integration
FOC Trans 0.2 Input into integration
APV 0.2 Input into integration
Work Package 8 - System Integration
Technical Objective: To fully integrate the various software and hardware components developed into a final, prototype, modular system.
Description of Technical Work: The output of previous workpackages will be brought together in workpackage 8. Although each workpackage will have produced deliverables with a view to their role in a final, overall system, these modular components will need be integrated to produce the final prototype. The workpackage will include functional testing by the system developers and by the project end users, to identify and rectify any bugs which might exist in operation of the system. The workpackage will also include end user evaluation of the integrated system, to determine performance levels and if necessary identify improvements which need to be made.
WP Leader: VTT Resources: 6.1 man months
Start Month: 16 End Month: 24
Partner Man Months Contribution
HIL 0.3 Input into system integration
UoS 1 Software integration and testing
Cetim 0.2 Input into system integration
VTT 1 Hardware and software integration and testing
Lehtosen Konepa 0.5 System testing and validation
Muottipiste 0.5 System testing and validation
Rej 0.5 System testing and validation
Toolman 0.5 System testing and validation
Teras-Astra 0.5 System testing and validation
Laske 0.3 Input into system integration
Goodview 0.2 Input into system integration
Avionics 0.4 System testing and validation
FOC Trans 0.1 System testing and validation
APV 0.1 System testing and validation
Work Package 9 - Dissemination
Technical Objective: To educate industrial end users on the need and potential for the PIMMS system; and to disseminate information on the project through a variety of means.
Description of Technical Work: The PIMMS project consortium wish to disseminate information on the project as widely as possible. A programme of seminars will be conducted, which will discuss the objectives and results of the project, and will educate industrial end users in the need for, and potential of, the PIMMS system. A World Wide Web site will be constructed. A European PIMMS conference will be held, attracting delegates from around the European Union. Academic and technical papers will be published in national and international journals and conferences.
WP Leader: IITT Resources: 3 man months
Start Month: 3 End Month: 24
Partner Man Months Contribution
HIL 0.3 Conference and exhibition presentations
UoS 0.4 Conference and journal publications
Cetim 0.8 Conference and journal publications
VTT 1 Conference and journal publications
Laske 0.3 Publicity material and seminars
Goodview 0.2 Publicity material and seminars
Work Package 10 - Exploitation and Marketing
Technical Objective: To develop the exploitation strategy for the PIMMS project.
Description of Technical Work: This workpackage develop the exploitation and marketing strategy to be implemented after the end of the research project, and will include the construction of an Intellectual Property Rights Agreement between all relevant partners, and the development of a full marketing plan for the various developments within the project, such as instruments, software, and integrated systems. Patent and literature searches will be conducted on an on-going basis throughout the project. Patent applications will be submitted as appropriate at various stages within the project. The project partners are committed to exploitation of the results of this collaborative research, and distribution and service systems will be developed to support this goal, including a "Help Desk" both within the project and eventually accessible to those customers who purchase systems and system components. A dissemination strategy will be developed for the publication of commercial and academic papers throughout the project. In order to ensure that the objectives for exploitation are properly met, the Project Co-ordinator will appoint an Exploitation Manager for the project from within the project partnership.
WP Leader: HIL Resources: 6 man months
Start Month: 13 End Month: 24
Partner Man Months Contribution
HIL 0.8 Development of IPR agreements, and marketing of project results
UoS 0.4 Exploitation in accordance with the IPR agreement
Cetim 0.3 Exploitation in accordance with the IPR agreement
VTT 1 Exploitation in accordance with the IPR agreement
Lehtosen Konepa 0.5 Exploitation in accordance with the IPR agreement
Muottipiste 0.5 Exploitation in accordance with the IPR agreement
Rej 0.5 Exploitation in accordance with the IPR agreement
Toolman 0.5 Exploitation in accordance with the IPR agreement
Teras-Astra 0.5 Exploitation in accordance with the IPR agreement
Laske 0.5 Exploitation in accordance with the IPR agreement
Goodview 0.1 Exploitation in accordance with the IPR agreement
Avionics 0.4 Exploitation in accordance with the IPR agreement
Work Package 11 - Project Management
Technical Objective: To ensure that the project produces all deliverables on time and to the required quality as determined by the project partners. To ensure that the project is completed successfully, on time and within budget, and meets the project objectives as set out in this document.
Description of Technical Work: The Project Co-ordinator (University of Sunderland) will be responsible for the overall management of the project. Each project partner will appoint a Technical Manager, who will be responsible for the managment of that partner's work within the project. A Project Steering Group will be set up, which will include the Technical Managers of all SME partners, plus the key R&D performers, who will decide on the strategic management of the project. A schedule of meetings will be drawn up, some of which will only involve the Steering Group, whereas others will be full project meetings. Inter-parter communication systems will be set up, including the use of electronic conferencing to help improve communications while keeping travel costs down. Project reporting requirements and standards will be defined, and a project management "Help Desk" will be set up. More detail is given on Project Management in Section 4. At the end of the project Final Reports will be submitted to the Commission for approval.
WP Leader: UoS Resources: 8.4 man months
Start Month: 1 End Month: 24
Partner Man Months Contribution
HIL 0.8 Project management
UoS 2.5 Project management and overall project co-ordination
Cetim 0.3 Project management
VTT 1 Project management
Lehtosen Konepa 0.5 Project management
Muottipiste 0.5 Project management
Rej 0.5 Project management
Toolman 0.5 Project management
Teras-Astra 0.5 Project management
Laske 0.5 Project management
Goodview 0.2 Project management
Avionics 0.2 Project management
APV France 0.2 Project management
FOC 0.2 Project management
3. PROJECT MILESTONES AND DELIVERABLES
3.1 List of Deliverable Items
Deliverables for each
workpackage
WP
No Timing (Month No)
Type
Description
1 3 Hardware installation Data acquisition systems installed and commissioned
2 24 Test data Test data from test arrangements and end user sites
3 10 Report Analysis of test data
4 13 Software and reports Residual life models; prototype analytical tools
5 12 Report System design specification
6 19 Prototype software Prototype software including analytical models and interface
7 19 Prototype software Prototype software modules for tool monitoring
8 24 Integrated system Fully integrated software and hardware system in prototype form
9 24 Seminars etc Web site, seminars, conference
10 24 Exploitation plans and publications Exploitation plans to ensure proper exploitation of results; academic and commercial publications
11 24 Successful project Project delivered on time, in budget and to required quality
3.2 Major Milestones
The assessment of the progress towards the objectives will be carried out at the following milestones:
Project Milestones
WP
No Timing (Month No)
Type
Criteria
1 3 Hardware installation Data acquisition systems installed and commissioned in all end user sites
5 12 Report Full system specification incorporating information from WP3 and WP4
7 19 Prototype software Prototype software for both WP6 and WP7
11 25 Final reports Completion of project and submission of Final Reports to Commission
Mid Term Review A Mid-Term Assessment Report on the progressof the research and the partner's plans for future exploitation strategy is to be submitted before the end of Month 13 from the dateof commencement.
The Project Co-ordinator will organise a Mid-Term Assessment meeting at the end of Month 14 with all partners and the Commission's representative. The purpose of this meeting will be to report on the progress to date and to re-define (if necessary) the Project Programme for the remaining part of the contract. Procedures for managing future exploitation of results will be discussed and approved. A decision whether or not to continue the contract will be taken before the end of Month 15 having regard to the specified objectives at this stage for the technical and scientific progress and having regard to the industrial and exploitation perspectives of the project.
a) Technical and
Scientific Progress The Mid-Term Assessment is to made against the satisfactory completion of the following programme items before Month 13:
i) Data acquisition systems will have been acquired, installed and commissioned at each of the sites which will provide data for the project.
ii) Data will have been collected from each of the sites providing data, representing a range of machine states and from a variety of different machine types. This data will be of sufficient quantity and quality to allow the data analysis required to develop diagnostic models.
iii) The test data will have been analysed to and conclusions drawn on the nature of the distributions within the data sets, correlations between variables which might prove useful in diagnosis, data pre-processing and feature extraction. These will form the basis of the diagnostic models which will be developed.
iv) Wear and residual life models which will be used in the diagnostic tools will have been developed and evaluated; these will be based on work previously done by VTT, Cetim and University of Sunderland, but will have been extended and modified in the light of the data collected in the project.
v) The system design and specification will have been completed for the prototype system which is to be developed and implemented at the identified sites.
b) Industrial and
Exploitation Perspectives The existence of positive and realistic perspectives for the industrial exploitation of the results and the continuing commitment of the partners to the objectives of the research project (especially the industrial partners in this respect) will also be critically assessed at the Mid-Term Assessment. For the exploitation aspects, please refer also to the chapter "Exploitation Plans" in this Project Programme.
4. PROJECT MANAGEMENT
4.1 Management Capability of the Co-ordinator
Capability of University of
Sunderland to lead
the project The University of Sunderland is a British higher educational institution based in the north east of England with some 17,000 students and several hundred academic staff. The University, and in particular the School of Computing & Information Systems (the faculty which will be involved in this project) has a strong research culture; the faculty has some 80 researchers on full- and part-time research programmes, including MPhil and PhD work. The University has been involved in many collaborative research projects, including many European projects in various programmes including IMT, Esprit, Eureka, and others. The faculty is currently taking a leading role in managing a large project (VISION) in the IMT programme. Dr. MacIntyre, who will act as Project Co-ordinator, has experience in managing IMT projects, is currently involved in the PLAN Thematic Network, and is on the Experts List for project evaluations. Other individuals within the faculty, such as Professor Peter Smith, have years of experience of running EU projects.
4.2 Organisation and Management Structure
Project Steering Group,
and Technical Managers The project will be managed through a heirarchical management structure as shown in Figure 5 below. The Project Co-ordinator will be Dr. John MacIntyre, who will have overall responsibility for project management and communications with the Commission. Each project partner will appoint a Technical Manager to have responsibility for management of that partner's activities within the project. A Project Steering Group will be made up from the Project Co-ordinator and the Technical Managers of the key SME partners and the R&D performers. The Steering Group will have responsibility for developing strategic plans and ensuring that the project is meeting its technical and commercial objectives. The Steering Group will also be responsible for binding decisions within the project, such as where arbitration on project disputes is required.
![[Image]](pict4.jpg)
Figure 5 - Project Management Structure
Responsibilities of the
Project Co-ordinator The Project Co-ordinator will be responsible for the execution of the workprogramme, communication with the European Commission, reporting (both technical and commercial), delegation of workpackages, motivation of the project team, encouragement of creativity, correct problem solving procedures and corrective actions.
Communication between
Partners The project partners recognise the importance of good communication in order to conduct a successful collaborative research project of this nature. Modern communication systems will be used to enhance the schedule of meetings which will be conducted in the project. In particular, electronic conferencing will be used on a weekly basis to maintain contact between the technical teams of the partners, whilst at the same time reducing travel costs within the project. Some of the project partners have experience of using these systems on other collaborative projects, to great effect. Other forms of communication, such as e-mail and World Wide Web, will be used extensively, and a project communications hub will be established, with secure ftp site for project documentation and data. A project "Help Desk" will be established to assist all partners to use these means of communication effectively.
4.3 Methods for Monitoring and Reporting Progress
Progress Monitoring The Project Co-ordinator will take the main role in monitoring progress against the objectives and milestones as set out in the workprogramme. This will be done by site visits and progress reports from each of the Technical Managers on a regular basis, to be determined by the Steering Group. Formal reports will be sent to the European Commission to meet the six-monthly pattern expected by the Commission, together with financial statements. Report formats and software used for project management and reporting will be determined by the Steering Group, and will be standardised across the project.
4.4 Project Management Task
Workpackage 11 -
Project Management Workpackage 11 in the workprogramme specifically details the effort, resources, and objectives for the task of project management to be undertaken in the project. This has been identified as a separate workpackage because of the importance of efficient and effective management of a collaborative project of this nature, and this is recognised by the project partners. This workpackage covers the effort and resources needed to ensure the overall management of the project; preparation of the detailed planning for the individual technical workpackages, and the preparation of the technical reports and deliverables for those workpackages, is included in the effort and resources indicated for the individual workpackage. It should be noted that the Project Co-ordinator will appoint an Exploitation Manager for the project, who will assist in ensuring that the results of the project will be properly exploited, and this individual will have an influence both on Workpackages 10 and 11.
4.5 Project Bar Chart
Figure 6 below shows the bar chart for the project, with the duration of each Workpackage shown by month number.
M o n t h s
WP 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
1
2
3
4
5
6
7
8
9
10
11
Figure 6 - Project Bar Chart
4.6 Project Manpower Allocation Table
The manpower allocation table for the workpackages in this project is given in Figure 7.
W P N o
Partner Country 1 2 3 4 5 6 7 8 9 10 11 Tot
HIL UK 0.6 0.6 0 0 0.5 0.3 0.3 0.3 0.3 0.8 0.8 4.5
UoS UK 0 0.3 2.5 2.5 0.4 5 3 1 0.4 0.4 2.5 18
Cetim FR 0.2 1.1 0.4 0.6 0 0 0.1 0.2 0.8 0.3 0.3 4.0
VTT FIN 2 4 2 3 1 1 3.8 1 1 1 1 20.8
Lehtosen FIN 0.3 2.3 0 0 0.3 0 0 0.5 0 0.5 0.5 4.4
Muottipiste FIN 0.3 2.3 0 0 0.3 0 0 0.5 0 0.5 0.5 4.4
Rej FIN 0.3 2.3 0 0 0.3 0 0 0.5 0 0.5 0.5 4.4
Toolman FIN 0.3 2.3 0 0 0.3 0 0 0.5 0 0.5 0.5 4.4
Teräs-Ast FIN 0.3 2.3 0 0 0.3 0 0 0.5 0 0.5 0.5 4.4
Laske FIN 0.3 0.5 0 0 0.5 0.3 0.3 0.3 0.3 0.5 0.5 3.5
Goodview FIN 0 0.1 0 0 0.1 0.1 0.2 0.2 0.2 0.1 0.2 1.2
Avionics UK 0.2 0.6 0 0 0.4 0 0 0.4 0 0.4 0.2 2.2
APV Fr FR 0.2 0.3 0 0 0 0 0.2 0.1 0 0 0.2 1
FOC Trans FR 0.2 0.3 0 0 0 0 0.2 0.1 0 0 0.2 1
Total 5.2 19.3 4.9 6.1 4.4 6.7 8.1 6.1 3.0 6.0 8.4 78.2
Figure 7 - Project Manpower Allocation Table showing Man Months per Partner per Work Package
4.7 Durable Equipment
Most of the major durable equipment is already held within the consortium. Only the items shown in Figure 8 below need to be purchased.
Partner Equipment to be Purchased Workpackage in which Required
UoS 1xDesktop Computer; communications boards 2,3,4,5,6,7
Lehtosen Konepa Contribution towards 1xMHC Memo 1,2,7,8
Muottipiste Contribution towards 1xMHC Memo 1,2,7,8
Rej Contribution towards 1xMHC Memo 1,2,7,8
Toolman Contribution towards 1xMHC Memo 1,2,7,8
Teräs-Astra Contribution towards 1xMHC Memo 1,2,7,8
APV France 1xMHC Memo 1,2,7,8
FOC Transmission 1xMHC Memo 1,2,7,8
Figure 8 - Durable Equipment to be Purchased for the Project
5. THE PARTNERSHIP
5.1 Overview of the Consortium
The total consortium consists of seven core SME proposers, four other proposers, and four RTD performers. These partners cover four member EC nations. The consortium is summarised in Figure 9 below.
Partner Type Size Country Business Activity R&D Function in the Project
HIL IND 2 GB Condition monitoring Data collection systems, system design and evaluation, exploitation
UoS EDU 6 GB Higher education Project Co-ordination; sstem design and evaluation, model development; dissemination
Cetim ROR 7 FR Industrial research System design and evaluation; data collection; model development; dissemination
VTT ROR 6 FIN Industrial research System design and evaluation; data collection; model development; dissemination
Lehtosen Konepa IND 2 FIN Manufacturing Data collection and system evaluation
Muottipiste IND 1 FIN Maunfacturing Data collection and system evaluation
Rej IND 1 FIN Manufacturing Data collection and system evaluation
Toolman IND 1 FIN Manufacturing Data collection and system evaluation
Teräs-Astra IND 1 FIN Manufacturing Data collection and system evaluation
Laske IND 1 FIN Manufacturing Data collection systems, system design and evaluation
Goodview IND 1 FIN Manufacturing System design and evaluation; exploitation
Avionics IND 1 GB Manufacturing Data collection and system evaluation
APV France IND 3 FR Manufacturing Data collection and system evaluation
FOC Transmission IND 1 FR Manufacturing Data collection and system evaluation
Figure 9 - Summary of the Project Consortium
5.2 Profile of the Individual Partners
Profile of the
Core Proposers Holroyd Instruments Limited is a British SME, with five employees and is wholly owned by its staff. The company specialises in the industrial application of acoustic emission, primarily to the detection of faults in machinery and variations in production processes. The companys principal revenue comes from the manufacture and sale of portable acoustic emission instruments such as the MHC-Memo, the MHC-Classic and the Portable UDE, which are widely used in British industry by maintenance engineers. The company designs and manufacturers all of its acoustic emission sensors and instruments.
Lehtosen Konepaja Oy is a Finnish SME with 76 employees. They carry out subcontracting work on machine and component production, with modern and diverse facilities for CNC-machining. In this project they will collect data and evaluate the tool monitoring system applied on a vertical turning mill (Mazak Mega Turn 16N). With a machine tool monitoring system they wish to increase their productivity and reduce costs, regarding maintenance and tools as well as downtime costs.
Muottipiste Oy is a Finnish SME manufacturing high-quality injection moulds for the electronic industry, the household appliance industry, the automotive industry and the forest and gardening industry. They employ 22 people. The tool monitoring system will be installed and tested on a CNC-Deckel FP5 milling machine.
Oy Rej Ab is a Finnish SME employing 27 people. They are both a manufacturer of drying frames and racks and a subcontracting machine shop, the core business being demanding CNC machining. The tool monitoring system will be tested on Mazak Integrex 40 ATC Mill Center with a magazine for 60 tools and a GL400 portal charger. At the moment the machine is equipped with a simple monitoring system which stops the machine in case of tool breakage. The strategy for tool changing relies completely on a specified value for tool life, which does not take into account any variations in work piece properties. They wish to increase the utilization rate of the machine tool and to obtain a reliable tool condition monitoring system. The objective is to enable unattended production to as high degree as possible, and to increase the machine capacity and the reliability of deliveries as well as to shorten the refunding time of the machines.
Toolman Oy is a Finnish SME machine shop with 27 employees. They specialize in tool manufacturing the products including die-casting dies, injection moulds and cutters. In this project they will install the machine tool monitoring system in a vertical machining centre Mazak FJV-20, with the prime interest in tool condition monitoring.
Oy Teräs-Astra Ab is a Finnish SME machine shop designing and manufacturing special machinery and special equipment, tools and metal components for the individual needs of their customers. The number of employees is 44. They wish to increase their productivity and improve their operational reliability by advanced machine tool monitoring. They employ a quality assurance system that meets the standards of ISO 9001.
Laske Oy is a Finnish SME with 10 employees. They produce digital signal processing data acquisition and analysis systems and electronic design. Their DMAS unit will be installed as a part of the tool condition monitoring system, to collect and process signals from various sensors on real-time basis, and to forward the pre-processed data to the PC. They wish to evaluate the functionality of their unit in this kind of monitoring application and to develop it further to exploit it as a part of such a system.
APV France is a French (non-eligible) SME with 200 employees, manufacturing machines for the agronomy, alimentary and pharmacy industries, and providing machine maintenance services for their clients. APV France will benefit from the development of intelligent acoustic emission sensor systems.
Société Nouvelle FOC Transmission is a French (non-eligible) SME with 47 employees, manufacturing variable speed drives. FOC Transmission with benefit from development of intelligent acoustic emission sensor systems.
VTT (Technical Research Center of Finland) is an independent polytechnic research center with a staff of over 2600. It is the largest contract research organization in the Nordic countries. VTT Manufacturing Technology with its more than 370 employees is one of the nine VTT research institutes. It works in a close cooperation with customers in order to increase their competitiveness through the application of new know-how and technologies to process and machine operability and safety as well as to products and manufacturing methods. The main activities include Safety Engineering, Production Engineering, Materials Technology, Operational Reliability, Materials and Structural Integrity and Maritime Technology. The main customers are metals, engineering, and process industry, and energy production. VTT Manufacturing Technology has several years experience in research and development of machine and tool condition monitoring systems, and this experience will be utilized in this project. VTT Manufacturing Technology has been participating in many Nordic and European research programmes, such as Brite-EuRam, ESPRIT, EUREKA and COST.
The University of Sunderland is a higher educational establishment in the UK, with an award-winning new campus on the banks of the River Wear in North East England. The University has some 17,000 students and more than 600 academic staff in nine faculties. The School of Computing & Information Systems has around 2,300 students, 80 academic staff and some 80 researchers, making it one of the most research-active faculties in the University. Within the School, the Centre for Adaptive Systems operates as a focused research group with a national and international reputation for applied research in the field of neural networks, genetic algorithms, fuzzy logic and neuro-fuzzy systems, and related techniques. These techniques have been applied in engineering, commercial, financial, and medical domains. The Centre has two directors, several academic staff, and 14 researchers working on a variety of projects, including European and UK funded projects as well as direct contract research for industry. The University of Sunderland has a proud tradition of working closely with industry and recognising industrial needs, and is committed to transfering these "smart" technologies from academia into real industrial applications. The School, including members of the Centre for Adaptive Systems, have worked on many collaborative projects, including taking a major role in project management. The University will bring unique skills to the project in modelling and development of artificial intelligence-based analytical tools.
Cetim is a French research organisation which conducts research and development on behalf of a wide range of French industries. Cetim has wide experience of European and other collaborative projects, and has specific experience in the areas of machine tool monitoring and residual life assessment of mechanical components. Cetim will contribute this expertise to the project.
IITT is a French SME, with six employees. The company was formed in 1985 carries out research and technology transfer in mechanical industries, as well as having a small manufacturing base for the construction industry. In addition to manufacturing specialist items for the construction industry, the company organises technical seminars and conferences in Europe and world-wide, and provides direct technical assistance to industry. IITT will be subcontractors to Cetim in the PIMMS project, and will conduct many of the dissemination activities for the project.
Profile of the
Other Proposers Oy Goodview Ab is a small Finnish company employing 3 persons, and its core business is in designing monitoring systems. It does not have enough R&D resources for developing this type of condition monitoring system on its own. Goodview has already previously worked in cooperation with Laske Oy, and it's role in the project is to give input in the system development and integration and, finally, to exploit the results by selling the product on the Scandinavian market area under a license agreement
Avionics Components was founded over 30 years ago and today is part of Hampson Industries plc. Precision manufacturing of a wide range of components is currently carried out on more than 20 CNC machine tools, and a number of conventional machines. As well as CNC machining to very fine limits, other services offered include grinding, milling, turning, drilling and tappling. Inspection stations within the machine shop ensure step-by-step procedural control and quality assessment as the products are manufactured.
5.3 Structure of the Proposers Group
Complementarity of the
Project Partners The project consortium has been constructed to bring together a team of organisations which have complementary skills in the key technological areas. Holroyd Instruments, Cetim and VTT Manufacturing Technology have experience in acoustic emission for mechanical monitoring. The University of Sunderland and VTT Manufacturing Technology bring experience in artificial intelligence and mathematical modelling techniques, as well as experience in modelling based on real industrial data. Cetim, and VTT have experience in residual life modelling, and together with IITT have experience of mechanical wear modelling. The various SME and other industrial partners bring a variety of expertise and skills in different applications, giving the project a diverse application base. This combination of organisations gives strength in all of the key areas, and it is this combination which offers the greatest chance of success in the project. It also offers clear routes for exploitation on a variety of levels; the modular instruments, the analytical software, and the integrated system all offer opportunities which can be exploited by members of this group.
Role of the Non-Core
Partners The non-core partners in the consortium have a key role to play in the success of the project. It is essential that a large body of data, from as many machine types and configurations as possible, is acquired to fully develop the residual life and wear models, and to properly develop the artificial intelligence models which will be used for diagnosis. The core proposers alone cannot provide sufficient data for this purpose; it is therefore essential to the success of the project that the "B" proposers provide a significant body of additional data. Goodview has good backround in designing monitoring systems and in system integration in industrial applications and their help and advice in the system development is essential. Also, successful marketing and sales of the product in Scandinavian countries requires the participation of such a Scandinavian company. Avionics provides invaluable resources in terms of testing facilities and a practical viewpoint on the viability of the technology in the real world. The project could not be carried out without the data from these partners, nor without their contribution to evaluation of the systems developed.
6. EUROPEAN DIMENSION AND RELATED BENEFITS
6.1 Subsidiarity
The nature of this project requires contributions from organisations with a variety of expertise and abilities. The mix of industrial and research skills, hardware and software development, and in particular data from different environments with different characteristics, would be very difficult to achieve without a truly trans-European project consortium such as has been constructed here. The consortium offers the opportunity to demonstrate the viability of the technology throughout Europe.
Added value of carrying
out the research at a
European level SMEs throughout Europe have been particularly slow to address the problems of condition monitoring and mechanical failures, partly due to the technical difficulty of collecting, analysing and interpreting vibration data, which is the most common technique. This has resulted in the potential benefits of condition monitoring for European SMEs in many industries not being realised. This project will develop a system ideally suited to both the technical skills and budgets of SMEs, and therefore will open an opportunity in the market place which SMEs have previously not been able to take advantage of.
6.2 Technical Co-operation among SMEs
The research is to be co-operative since no SME has the necessary research and development resources to carry out the research in isolation. As the research matures beyond the scope of this project, it will be necessary for wider exploitation to be achieved through co-operation with larger groups of SMEs througout Europe. This wider co-operation will involve sensor and instrument manufacturers, telecommunications hardware and software providers, software development houses, machine manufacturers, and manufacturing organisations. This represents a large potential market for SME co-operation in Europe in the medium term. This includes the"B" proposers, without whom the project could not be carried out.
6.3 European Social and Economic Cohesion
Social and economic cohesion within Europe will, in the first instance, be enhanced by the co-operation of 15 partners in four member countries. This will be taken further through the technology transfer and dissemination activities within the project, which will publicise as widely as possible the work and achievements of the project. Beyond the scope of the project, the wider SME co-operation discussed in 7.2 above will significantly increase social and economic cohesion by bringing together large and diverse groups of SMEs in a common purpose or interest. No one SME partner could carry out this work, and it is only with a truly trans-European consortium that the benefits of the project will be disseminated throughout the European Community. Such a partnership will strengthen both the economic and social cohesion of the Community by improving the competitiveness and technological base of European SMEs, and by moving these companies towards best practice in the area of corrosion monitoring and control. The project could be used as a platform for the development of best practice guidelines for SMEs in this area, and also new standards for corrosion monitoring and control.
6.4 Codes of Practice and Standards
As discussed in 7.3 above, the project will move the project partners and other companies towards best practice in the area of condition monitoring. The project could be used as a platform for the development of best practice guidelines for SMEs in this area, and also new standards for condition monitoring.
7. ECONOMIC, INDUSTRIAL, SAFETY, SOCIAL AND
ENVIRONMENTAL IMPACT
7.1 Economic and Industrial Opportunities
Expected measurable
economic and industrial
benefits for the SME
proposers, other
organisations and other
sectors The potential economic benefits for European SMEs in adopting advanced techniques in condition monitoring are huge. The potential benefits in terms of reduced operational costs, improved efficiency, and reduction in capital expenditure on repair and replacement of plant across Europe equates to hundreds of millions of ECUs.
The proposed system would help European SMEs by developing new market opportunities for sales and consultancy in the maintenance sector. This market is expected to expand in the late 1990s and the early part of the next century as the cost of monitoring equipment is reduced. In addition, SME manufacturers will benefit by adoption of the technology to improve their operational efficiency and reduce maintenance and downtime costs.
There are other opportunities for exploitation, through patent applications on new modular instruments and integrated systems. The project partners are committed to examining the potential for exploitation of any "spin-off" products which might come out of the research project.
The proposers will benefit in a number of ways; through sales of the sensor and software systems, through the application of the systems in end user proposers' industrial sites, and through dissemination and publicity for the developed technology. Holroyd Instruments will be the main exploiter in terms of sales, and have carried out preliminary market survey which indicates that the European market for such technology in SMEs is very large, with potential sales in excess of 12 MECU per annum once the technology is brought to a commercially marketable level. Holroyd Instruments will also co-operatew with other core group members to develop licencing arrangements for onward sale of the technology. The individual end user partners will benefit through implementation of the developed technology on their plant, thus reducing maintenance costs, improving reliability and product quality. The R&D performers will benefit by utilising the results of their continung research programmes.
SMEs in other sectors will also benefit from the results of this project. For example, some of the modular instrument design will have applications outside the water industry, and both the project partners and other organisations whom they deal with will have the opportunity to exploit these application markets. The project consortium is committed to exploring every possible avenue for exploitation of the results from this research.
7.2 Safety, Social and Environmental Impact
The proposed system would have positive benefits in the areas of safety and the environment. An effective system would reduce wastage of valuable resources, both in terms of spares and energy - inefficient operation of plant costs the European Union millions of ECUs, and the PIMMS system will help to identify and reduce this cost.
The social impact of the project would be in the areas of integration of SMEs across Europe in a consortium working towards improvements which would bring benefits to a large section of European industry, and also in the development of best practices and standards for European SMEs in condition monitoring.
8. EXPLOITATION AND DISSEMINATION
Intentions and capability
of the SME proposers
to exploit the results The proposers are well versed in developing and marketing technology in the field of monitoring, maintenance and reliability, and specifically corrosion monitoring and control. The proposers intend to develop a commercial product based on the results of this project, and to market the product throughout the European Community. To ensure that the benefits and capabilities of the product are widely disseminated throughout Europe, the proposers will undertake a programme of technology transfer seminars to demonstrate to SMEs how the product can benefit them. The end user proposers will employ the developed technology at their sites throughout Europe, thus reducing their operating costs and improving efficiency and reliability.
Holroyd Instruments intend to develop strategic partnerships with companies in the consortium, such as Goodview in Finland, to market the resulting products. Holroyd Instruments has extensive experience of marketing products into the condition monitoring market to customers, including blue chip companies, in many industrial sectors in the UK. However, the company does not have the required experience to market the results in Europe, and the strategic partnerships will provide a network of exploitation outlets with good knowledge of their own market area. For example, Goodview has a good knowledge of the market in Finland, Norway, Sweden, Denmark, Estonia, and the Soviet Union; other strategic partners will be sought to market the results in Northern and Sourthern Europe.
These partnerships will be formed under licensing agreements with Holroyd Instruments and the other core proposers who have an interest in exploiting the results, such as Laske. However, since Holroyd Instruments will be the main exploiter, they will manage licensing arrangements with any companies from outside the consortium which are used to market the results. Holroyd Instruments will use the network of contacts of other partners such as VTT, Cetim (and their subcontractor, IITT) and the University of Sunderland to identify potential companies who have the resources and facilities to market the results effectively.
Within the consortium, and IPR agreement will be drawn up between the core proposers which will specify how the benefits of exploitation will be assigned. It is envisaged that the main interest from within the consortium for exploitation other than for use in companies' own activities will be from Goodview. However, Laske may have an interest in exploitation of any hardware which is developed, or which is based on their products.
It is intended that the products developed should be low cost in order to be affordable for SMEs throughout Europe, and target costs will be provided. The consortium is committed to marketing the results widely throughout Europe.
The results of the research will then be published through a variety of media, such as journals, conferences, trade exhibitions, and electronic media such as the World Wide Web in order to encourage further research and to widen the field of application for the technology.
The product will be publicised through the media, trade associations, the technology transfer seminar programme described above, and exhibitions throughout the world.
1. March Consulting Group, 'Managing Maintenance into the 1990's', April 1989.
2. The European Benchmark Study on Maintenance (EBSOM), 1994.
3. [Kuhmonen, M. Dissertation 1997]
4. CETIM Survey
5. Kluft, 1985
6. Jantunen, E., Jokinen, H. & Milne, R. Flexible Expert System for Automated On-Line Diagnosis of Tool Condition, Integrated Monitoring Diagnostics & Failure Prevention, Technology Showcase. MFPT 50th Meeting, April 22-26, 1996. Mobile, Alabama, USA.
7. Jantunen, E. & Jokinen, H., Automated On-Line Diagnosis of Cutting Tool Condition, 5th Inter-national Conference of Flexible Automation & Intelligent Manufacturing, FAIM 95, June 28-30, 1995, Stuttgart, Germany
8. FMS-MAINT Project Final Report, full reference needed
9. MacIntyre, J., Development of an Off-Line Condition Monitoring System at a Coal-Fired Power Station, Condition Monitor No. 75, 1993.
10. Littlefair, G., MacIntyre, J., Development of Comprehensive Condition Based Maintenance Systems - Two Practical Industrial Examples, Condition Monitoring 94, University of Swansea, 1994.
11. MacIntyre, J., and Jennings, I., Condition Monitoring Software that Thinks for Itself, Proceedings of the MAINTEC Conference, Birmingham, 1997.
OTHER RELATED REFERENCES
Jantunen, E., Jokinen, H. & Holmberg, K., Monitoring of Tool Wear, 8th International Con-gress on Condition Monitoring and Diagnostic Engineering Management, COMADEM 95. June 26-28, 1995, Kingston, Canada
Holmberg, K., Jokinen, H., Malinen, P. & Torvinen, S., Integration in Virtual Factory - Flexibility and Reliability in Manufacturing, Invited Keynote Paper, European Information Technology Pro-gramme (ESPRIT), Conference on Integration and Manufacturing (IiM), 13.-15.9.1995, Vienna (Laxenburg), Austria
Jantunen, E. & Jokinen, H., Reduction of Data Needed in an Expert System for Condition Monitoring of FMS Using Regression Analysis Techniques, 9th International Con-gress on Condition Monitoring and Diagnostic Engineering Management COMADEM 96. July 16-18, 1996, University of Sheffield, UK.
M. CHERFAOUI, F. ZHANG, D. SANCHEZ, G. VENNETTILLI - La détection de fuite par EA dans le circuit primaire des centrales PWR : Bilan de 12 ans d'application. 6th European Conference on Non destructive Testing. Nice 1995.,p557-560.
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M. CHERFAOUI, M. DESCHAMPS - Evaluer en temps réel l'usure des roulements. CETIM Informations, n° 154, Juin 1997, p 45-46.
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M. CHERFAOUI - Les réseaux de neurones appliqués à la reconnaissance des signaux. 6th European Conference on Non Destructive Testing. Nice 1995, p489-491.
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M. CHERFAOUI, C. HERVE - Acoustic Emission in pressure vessels. 7th ECNDT, Copenhagen 26-29 may 1998.
M. CHERFAOUI, F. ZHANG, J.C. GERMAIN, D. PROVOST - Guide de détection de fuite par émission acoustique dans les centrales nucléaires. Congrés COFREND 22-26 Septembre 1997.
L. COUTURIER, F. ZHANG, J.F. FLAVENOT, J. LU - Suivi de l'endommagement par fatigue d'un matériau composite à matrice métallique à l'aide des ultrasons et de l'émission acoustique. Congrés COFREND 22-26 Septembre 1997.
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OTHER RELATED EUROPEAN PROJECTS
BRITE PROJECT O2094-4 : TEMOS - Development of an expert system for tool wear monitoring in milling, drilling and blanking using multisensor systems and machinability studies using acoustic emission. 1989-1993.
ESPRIT PROJECT 2092 : ANNIE - Applications of Neural Networks for Industry in Europe. 1993-1995.
BRITE EURAM II - BRE - 20197 : EDMOND - Integrated system for predictive and preventive maintenance of aggregate production plants. 1994-1996.
BRITE Project N° BE-7100, N° contrat BRE2-CT94-0911 : The determination of the main sources of acoustoc emission during machining of metallic materials. 1994-1996.
CRAFT N° Project proposal CR1625, n° contact BRE2-1525 : Non destructive real time control of the quality of electrical spot welding . 1995-1997.
CRAFT N° contract BRST - 5047 : Inspection and surveillance of metallic pressure vessels during the proof test. 1996-1998.