AIN Navarre Industry Association

Transcription

1 AIN Navarre Industry Association Seventh Platform Event of RIM Plus Optimising and Automating Manufacturing Processes in European Factories José Luis Gironés Remírez Business Development Director Seventh Platform Event of RIM Plus Brussels (14 November 2016)

2 Index o o o o WHO WE ARE NAVARRE REGION: RIM report for Industry 4.0 & Smart systems ENGINIERING: Condition Monitoring integration in advanced manufacturing R&D PROJECTS: Industry 4.0, Smart systems, Advanced manufacturing

3 WHO WE ARE 3

4 Background The Association of Industry of Navarre was founded by a group of local entrepreneurs. It evolves through its history together with companies of the region. Navarre 1963 Companies in Navarre have diverse needs A GLOBAL SOLUTION: Association of Industry of Navarre

5 Near 135 members from all industrial sector Partners

6 Facilities AIN is setup over a floor of m 2 (8.262 m 2 of building) at 4 km far from Pamplona ( population). Laboratories m 2 Surface Engineering Information Technologies (Communications, Aerial Robotics) Training - 16 class-rooms Devoted to training and workshops. Associated companies can use them under special condicitions. Auditorium 300 people Equiped for any kind of public or private wokshop, commercial presentation, etc.

7 Global support Technology Engineering Training Consultancy Competitiveness Offers a global support and is trusted for society and companies Diversification Research Innovation

8 Differentiation Our team, our difference 72 employees with multidisciplinary profiles and extensive experience More than 80% University graduates Over 10% Doctors

9 Technological expertise Differential Added Value AIN works in collaboration with other Technological Centers, Universities and Companies in the development of projects aimed at increasing the competitiveness of our customers by offering products and services with a differential added value: Cross approach expert advice in technology development and industrial implementation Advanced Surface Engineering Information Communication Technologies Mechatronics Advanced Engineering

10 NAVARRE REGION RIM report for Industry 4.0 & Smart systems 10

11 Navarre s industry main figures

12 Comparison with Spain Weight of industrial sector in de GDP vs GDP rate reduction ( ) External Trade. Coverage rate (Exports/Imports)

13 Comparison with Spain Industry sector turnover , in million ) R&D expenditure/ GDP, (%)

14 Challenges Advanced Manufacturing: Industry 4.0 & smart systems 1. Social awareness and dissemination of the concept Industry Navarra s Industry digitalization. Towards Industry Fostering new competences and skills aligned to the needs of the new industry 4. Generation of an Industry 4.0 s services basis supporting the industrial sector Regional Innovation Performance Trends, Governance and Instruments 1. Promoting cooperation for innovation between Science - Technology - Enterprise system 2. Improving the placement market of the innovation via cooperation results 3. Increase the participation rate in European projects Future Actions and Opportunities 1. Maintaining and increasing efforts in research, development and innovation 2. Reinforcing the access to the Information Society 3. Fostering regional SMEs competitiveness and strengthen its presence in international markets Most of the interviewed are interested in implementing industry 4.0 solutions but gradually. Some priority fields (big companies): Operational efficiency, predictive maintenance and intelligent Information exploitation.

15 ENGINIERING Condition Monitoring integration in advanced manufacturing 15

16 Condition Monitoring In the search for the ideal of the maintenance function: maximum availability ( "zero breakdown") at the lowest cost, "condition monitoring" (CM) and predictive maintenance concepts are becoming more and more relevant. CM philosophy (50s) is to carry out maintenance tasks only when necessary: "hands off. So far it has had a limited success due to: ü Lack of convincing in the advantages of prediction ("other costs at the moment") ü Distrust ( "false alarms" and "bad reputation" in some cases) ü Instrumentation costs (sensors / HW) However things are changing: ü Failure anticipation "saves money" and mentality is changing ü When applied correctly the results are very good. There is a great development in new technologies of prognosis (Eg: Data-Mining, AI, etc.) ü The cost of all associated hardware (sensors / acquisition, etc.) has decreased significantly and will still decrease further ü The digitization of the industry and smart factories push in favor of CM in order to attain production lines with self-diagnosis capabilities

17 MEMs Vibration sensors New LOW COST SENSORS for CONDITION MONITORING EXPANSION Vibration sensors based on MEMS for condition monitoring aplications ü Low / High frequencies applications ü Wireless implementation ü Expected cost reduction : 40% per measurement channel compared to the current piezo technology

18 FBGS integration New LOW COST SENSORS for CONDITION MONITORING EXPANSION FBGS ( Fiber Bragg Gratings) interrrogators for condition monitoring applications ü Electrical immunity ( EMC) ü Good accuracy and long-term stability ü Multisensorial capabilities ( strain, temperature, vibration ) ü Multisensor capability per optical line ü Cost interrogator target : 1000

19 CM integration Towards CONDITION MONITORING INTEGRATION in ADVANCED MANUFACTURING

20 R&D PROJECTS Industry 4.0, Smart systems, Advanced manufacturing 20

21 KET Key Enable Technologies

22 Project VAMAD Description: defects detection and classification by Support Vector Machines Cooperative project among Spanish research centers and VMS (Verteilte Messsysteme) Technische Universität München. Stroboscopic illumination synchronized with capture (90 img/s) Key aspects: ü No cooperative surfaces ü Stroboscopic illumination ü Image fusion (captured with different illumination) ü 16 pixels/mm in real time Output ü 1 Spanish patent / 1 German patent

23 Project DMWind Description: Data Mining techniques applied on SCADA system for prediction and knowledge discovery of fault patterns in wind turbines. Sensors SCADA System Fault modes experts knowledge WP1.2 DM-Wind PROJECT DATA Heterogeneo us historical data repository WP2 Data preparation Training cases WP3 Fault Mode Predictive Models Building Different levels of prediction WP4 Component Health Predictive Models Evaluation WP5 DATA Existing DATA SOURCES WP1.1, WP 6, WP7

24 Modelling, Measurement and Improvement of the water management environmental impact in the food industry Objetive: is to minimize the environmental impact related to water management in the subsectors with highest water consumption through effective demonstration Proposed implementation methodology: Production efficiency monitoring system Wirelessly monitors and calculates the production efficiency of the equipment It includes simultaneous water and energy consumption Does not interfere in the production processes Expected impact: Reduction of water consumption -30% at meat industry -25% at canned vegetables industry -26% at juice industry Project MCUBO Mathematical modelling and simulation LIFE MCUBO LIFE15 ENV/ES/ Mathematical models able to reproduce the production process and wastewater treatment processes will be employed This enables having simulations before implementation in real plant Validate the proposed solutions Transfer of knowledge about optimization processes

25 Project: NAVARMDI-HUB: For the establishment of a feasibility study for a Regional Digital Manufacturing Innovation (RDMI) Hub Main concept : to exploit the synergies and capabilities already organised in the Regional Innovation Ecosystem in Navarre, in terms of industrial innovation, effective technology transfer, business engagement and regional value chain activation tools in order to define a strategy to establish a Regional Digital Manufacturing Innovation (RDMI) Hub. Focused on: Cyber-Physical Systems and Internet of Things ICT Innovation for manufacturing SMEs

26 Project EVOLINDUSTRIA: Application of evolutionary computing algorithms for the design of plants for the extractive industry Input: Initial granulometry Output: Production Tm/h and required granulometry Input? Optimal model Output COMPANY TRIMAN: plant design for a quarry installation. Key aspects: Optimization problem Select machines, machine parameters and topology Use of Genetic Programming Results: Optimal solutions that ARE NOT OBVIOUS for the experts Objective: to design the plant topology and tuning machines parameters Plant in the phenotypic and genotypic space

27 Application: Perceptive system to avoid collisions Title: Perceptual and autonomous robotics. See/sense & avoid Robot/vehicle Images sequence for motion estimation Sense&Avoid project: Use of Optical Flow to compute the risk of collision (Time To Collision- TTC) MOVEMENT ANALYSIS Computation of Optical Flow(OF) Segmentation of indep. movements Key aspects: Optical flow computation by different techniques Navigation with monocular vision Egomotion (T, R) OBSTACLES EVASION TTC Maps Remove rotation from OF Time to collision maps

28 Project Fusión sensorial: Sensor fusion for robot navigation and characterization of unknown and dynamic environments Sensor Fusion: For independent moving objects detection and characterization Mapping by means of occupancy grids Key aspects: Perception improvement by fusing information Sensors: 1 camera + 2D lidar + GPS + IMU Capture GPS /IMU Camara Calibration LIDAR Synchronization Extrinsic Calibration + Lidar data

29 Proyect ECM: Efficient Condition Monitoring Intelligent System based on vibration analysis and other signal processing techniques as well and Artificial Intelligence algorithms for automatic failure detection in drive train wind turbines.

30 Project FASYS: Full Safe and Healthy Factory FASYS project: The FASyS project proposes the development of a new knowledge and technology that guarantees, from the design phase, the welfare and comfort of workers in future machining, handling and assembly factories so the workers will become key factors of competitive and differentiation in the new production model Key aspects: Implantation of sensors to monitorize the physical and psychological state of the worker, of its working environment and the equipment that uses

31 THANK YOU VERY MUCH FOR YOUR ATTENTION!! José Luis Gironés Remírez Business Development Director / jlgirones@ain.es Asociación de la Industria Navarra Ctra. Pamplona, 1 - Edificio AIN Cordovilla, Pamplona. Spain