Presentation is loading. Please wait.

Presentation is loading. Please wait.

Sfinorman.nosfinorman.no1 WP1 – Robust and Adaptive Manufacturing Systems WP2 - Advanced Process Control and Intelligent Maintenance WP3 - Hybrid Manufacturing.

Similar presentations


Presentation on theme: "Sfinorman.nosfinorman.no1 WP1 – Robust and Adaptive Manufacturing Systems WP2 - Advanced Process Control and Intelligent Maintenance WP3 - Hybrid Manufacturing."— Presentation transcript:

1 sfinorman.nosfinorman.no1 WP1 – Robust and Adaptive Manufacturing Systems WP2 - Advanced Process Control and Intelligent Maintenance WP3 - Hybrid Manufacturing GOAL: Develop system concepts for automated manufacturing with high performance based on integration and adaptivity in manufacturing systems GOAL: Develop knowledge, tools, and concepts for advanced process control and intelligent predictive maintenance of equipment for high performance manufacturing GOAL: Develop the concept and principles for a hybrid manufacturing system RA1: Advanced Manufacturing Technology

2 sfinorman.nosfinorman.no2 WP1 - Robust and Adaptive Manufacturing Systems WP2 - Advanced Process Control and Intelligent Maintenance WP3 - Hybrid Manufacturing WP6 Research area 1: Advanced Manufacturing Technology T3 WP4 Planning and Control WP5 Work Organization T4 T2 T5 Collaboration between WPs

3 sfinorman.nosfinorman.no3 WP1Robust and Adaptive Manufacturing Systems Implications of the concept of the constantly changing manufacturing system for: T1: Study new design methods for manufacturing control based on an agent-oriented bottom-up approach T2:Develop and integrate new agent-oriented design tools in the APROX framework T3: Define operator information and control requirements in highly automated manufacturing environments - work organization and demand for skill development T4:Define handling characteristics for non-rigid materials WP2Advanced Process Control and Predictive Maintenance T1: Sensor and sensor system development and integration for measurement of critical process parameters T2: Control strategies and methods for self-adjusting, -calibrating and -reconfigurable processes T3:Fault diagnosis and prognosis system for preventive maintenance of production equipment T4:3D-object measurement and inspection on the basis of 3D point clouds T5: Operator decision-support: strategies, models and tools for effective problem solving based on a combination of operator/specialist knowledge and monitoring of measured or estimated process parameters WP3Hybrid manufacturing T1: Development of a hybrid manufacturing cell by integration of additive manufacturing with conventional CNC milling T2: Case studies: principles for enhanced tooling capability and high performance parts by incorporation of complex geometries and variable material composition for advanced thermal management and directed part material properties T3: Design for performance: design principles to exploit the possibilities of the Hybrid Manufacturing concept Task in all WP's: International collaboration and network building PhD involvement

4 sfinorman.nosfinorman.no4 WP1Robust and Adaptive Manufacturing Systems Implications of the concept of the constantly changing manufacturing system for: T1: New design methods: symbolic communication between machines/devices. For such communication, both software and hardware of present equipment must be extended. T2: Develop and integrate new agent-oriented design tools: systems, e.g. assembly systems, capable to work in not well structured environment. T3:- work organization and demand for skill development T4:Define handling characteristics for non-rigid materials WP2Advanced Process Control and Predictive Maintenance T1: Sensor and sensor system development and integration for measurement of critical process parameters: Sensor networks capable of acquiring symbolic data T2: Control strategies and methods for self-adjusting, -calibrating and -reconfigurable processes: strategies and methods based on symbolic data mining and optimization. Solutions imitating biological reflexes T3:Fault diagnosis and prognosis system for preventive maintenance of production equipment T4:3D-object measurement and inspection on the basis of 3D point clouds T5: Operator decision-support: strategies, models and tools for effective problem solving based on a combination of operator/specialist knowledge and monitoring of measured or estimated process parameters: HMI communicating with operators on the symbolic level WP3Hybrid manufacturing T1: Development of a hybrid manufacturing cell by integration of additive manufacturing with conventional CNC milling T2: Case studies: principles for enhanced tooling capability and high performance parts by incorporation of complex geometries and variable material composition for advanced thermal management and directed part material properties T3: Design for performance: design principles to exploit the possibilities of the Hybrid Manufacturing concept PhD involvement

5 sfinorman.nosfinorman.no5 5 Control logic verification Before Programming logic in QUEST * syntax Programming logic in QUEST * syntax 'Verified' control logic Programming logic in target language ** syntax Programming logic in target language ** syntax Truly verified control logic in real equipment environment Truly verified control logic in real equipment environment *QUEST simulation software **Python Now Results from RA1 WP1 Robust and Adaptive Manufacturing Systems

6 sfinorman.nosfinorman.no6 Control logic verification Now Programming logic in target language ** syntax Programming logic in target language ** syntax Truly verified control logic in emulated equipment environment Truly verified control logic in emulated equipment environment Switching to real equipment environment Switching to real equipment environment Results from RA1 WP1 Robust and Adaptive Manufacturing Systems

7 sfinorman.nosfinorman.no7 1.Flexible, automated sewing further developed: +A software has been developed for integration of control of robot, PyMoCo and ROS +Real time control has been tested and promising results have been achieved for 8 milliseconds control. +A new speed sensor (mechanics and electronics) has been developed. The sensor will be used for measurements required for further development of the control system for the sewing cell. =Sew together parts of different shapes and materials, without prior knowledge of the part geometries Results from RA 1 WP2 Advanced Process Control and Predictive Maintenance 2.A predictive maintenance model has been established in order to obtain optimal maintenance scheduling based on the condition of the equipment. 3.RFID techniques in condition monitoring has been researched, and a demo of RFID application in production system has been established. 4.A dual arm robot installation is being built

8 sfinorman.nosfinorman.no8 1.A new method for preparing the substrates for additive manufacturing in a CNC milling machine has been developed. 2.The cohesion of the AM section to the base part has been tested with excellent results (Marlok C1650+ CL 50WS AM tool steel). 3.Porous sections built into the tool insert derived as a valuable complement to other practical solutions 4.A prototype integrated control system for the hybrid cell (OMOS) has been further developed, in collaboration with exchange student from Slovenia. 5.A prototype of the hybrid cell control system has been developed. Results from RA 1 WP3 Hybrid Manufacturing

9 sfinorman.nosfinorman.no9 Other results New projects: Autoflex - Flexible automated manufacturing of large and complex products: Partners: Rolls- Royce Marine AS, Benteler Aluminium Systems Norway AS, Intek Engineering AS, SINTEF Raufoss Manufacturing AS and NTNU. SmartTools: Partners: Sandvik Teeness AS, SINTEF ICT, SINTEF Raufoss Manufacturing and NTNU IPK Contribution to education: The Framework of IFDPS becomes a part of a course (TPK 4155 Applied Computational Intelligence in Intelligent Manufacturing) The RFID application demo for Production System becomes a practice study for a course called PK8106 Knowledge Discovery and Data Mining

10 sfinorman.nosfinorman.no10 International collaboration within RA1 in 2012: Chairman from Industry for Joining Sub-Platform: SFI Norman and SINTEF Raufoss Manufacturing AS have worked actively in Manufuture by participating in the HLG. As a result Kristian Martinsen now holds the chair, as an industry representative, for the new sub-platform for Joining. Exchange agreement with four students from Ensiame Engineering School, Valenciennes, France. Have been working on design of a flexible jig for assembly of components for Sandvik Teeness and a dual arm robot installation. Collaboration through the development of the new ISO standard on additive manufacturing technology does now include the chair for ISO/TC261 WG1 Terminology for additive manufacturing. DTI (Denmark), VTT (Finland), Acreo (Sweden), Fraunhofer (Germany): collaboration on coatings, integrated sensors and new business models for injection molding industry. Two new EU-projects have been granted, SASAM and Diginova, where SINTEF Raufoss Manufacturing is a partner. Diginova, short for Innovation for Digital Fabrication, is a coordination and support action project under NMP 7th FP, Networking of materials laboratories and innovation. SASAM, which is short for Support Action for Standardisation in Additive Manufacturing, is a similar type of project. Collaboration on a EU-proposal "VITAMIN", where Sandvik Teeness was partner together with SRM and SINTEF ICT from Norway. Not granted.

11 sfinorman.nosfinorman.no11 Planned international collaboration within RA1 for 2013: Polytechnic Institute of Braganca, Portugal: Prof. Paulo Leitaõ: workshop around holonic manufacturing, common publication or similar. The University of Manchester, UK: Dr. Yi Wang: establishing projects on Intelligent systems and Predictive Maintenance. Common publication: a book on data mining for zero-defect manufacturing VTT Technical Research Centre of Finland, +rest of consortium EU proposal for call FoF.NMP "New hybrid production systems in advanced factory environments based on new human-robot interactive cooperation": University of Ljubljana: Prof. Slavko Dolinsek and student David Homar, continue collaboration on development on OMOS (Optimized Manufacturing Operation Sequence) University of Berlin (???? ): Prof. Günther Seliger: workshop around flexible automation and possibly researcher exchange?

12 sfinorman.nosfinorman.no12 More detailed on results

13 sfinorman.nosfinorman.no13 Flat milling produces a glossy surface; –Low-friction for powder spreading –Reflective to laser beam Standard procedure: Sand blasting, -unsuitable for the hybrid cell Hybrid cell procedure: Extra sharp cutting tool inserts "scratch" the substrate –Provides an exact z = 0 -point for starting the AM building Some results from RA1 Substrate preparation Edge radius: 0 – 0.1 mm; Cutting depth: 0.1 mm; Feed rate: 0.05 mm/O

14 sfinorman.nosfinorman.no14 14 OMOS: Optimized Manufacturing Operation Sequence

15 sfinorman.nosfinorman.no15 Results: Cooling time for conventional insert and “old” design 70 sec. –Estimated cooling time with new design approximately +25 sec. = 95 sec. Cooling time with new design and conformal cooling insert: 48 sec. Cost of machining AM produced insert similar to conventional production, however the cost of AM makes this an expensive insert Industrial need: reduced cost of production by AM closer to final shape Some results from RA1 WP3: Industrial case studies: insert for a bracket to an office chair

16 sfinorman.nosfinorman.no16 Working principle: Demonstrator development

17 sfinorman.nosfinorman.no17 Demonstrator development Example: System Frame of IFDPS – Intelligent Fault Diagnosis and Prognosis System


Download ppt "Sfinorman.nosfinorman.no1 WP1 – Robust and Adaptive Manufacturing Systems WP2 - Advanced Process Control and Intelligent Maintenance WP3 - Hybrid Manufacturing."

Similar presentations


Ads by Google