29/04/2014 Comment numériser efficacement la machine du futur afin d en optimiser le fonctionnement? Jean-Michel Taladriz Regional Director LMS France, a Siemens Business Smarter decisions, better products.
Agenda 1 From testing to simulating 2 Numerical answers to optimize the machines 3 A high relevant instance : PICANOL 4 Conclusion Page 2
From testing to simulating Delivering Transformational Solutions Leading Partner in Transforming is Test and Mechatronic Simulation Addressing the Future Problems of our Customers 2010 2020 Hybrid TEST/CAE Partner NVH-Acoustics-Durability-Dynamics TEST Partner 1995 2010 1980 1995 Page 3
V-cycle in 3 Dimensions Enabling Model Based Closed-loop System Driven Product Development Integrating Multidisciplinary Activity... Adopting Model Based Product Development In all Stages of Development enabled by Closed-loop Performance Verification Page 4
Industry 4.0 Vincent Jauneau : «Vice Président de Siemens France en charge du secteur Industrie» «Nous allons vers une convergence, une fusion, entre le monde virtuel et le monde réel. Nous sommes en pleine accélération» «Les industriels seront obligés de faire collaborer des équipes qui jusqu ici travaillaient chacune de leur côté il faudra une collaboration forte» «Pour aller vers l industrie 4.0, les industriels doivent faire collaborer les équipes IT, les BE et les équipes de production et les fédérer autour d un projet. C est le critère de réussite pour la mise en place de l industrie 4.0 dans une entreprise. C est toute la chaîne qui doit être prise en compte» Siegfried Russwurm: «Membre du directoire de Siemens AG et CEO du secteur Industry» «Les systèmes actuels s appuient toutefois encore principalement sur des disciplines techniques individuelles pour générer et tester les modèles. Il faut donc ensuite relier ces systèmes aux modèles qu ils élaborent. Les systèmes modernes doivent être envisagés du point de vue de leur interaction fonctionnelle. C est pourquoi Siemens a récemment fait l acquisition, entre autres, de la société Belge LMS.» «Ce changement porte en lui la promesse de gains de productivité tellement importants que les entreprises tournées vers l avenir le placent en tête de leurs priorités» «Dans ce contexte, Siemens est à la fois fournisseur et client. Notre vision naturellement holistique de l ensemble du processus de création de valeur d une entreprise qui conçoit et fabrique des produits exerce une influence déterminante sur le choix et le développement Page 5 des logiciels que nous proposons.»
Agenda 1 From testing to simulating 2 Numerical answers to optimize the machines 3 A high relevant instance : PICANOL 4 Conclusion Page 6
Industrial Heavy Machinery => increased performances Performances Quality precision, repeatability, product specific characteristic (surface finishing for grinding machines, constant thickness for paper manufacturing, etc) Low operation cost (per unit of final product): high throughput reduced consumption of major cost items, such as power, water and use of raw material. speed Energy Management and Mechatronic - Potential vibrations - acoustics issues Page 7
Frontloading Functional Performance Engineering Integrating Physical and Virtual Prototyping Cost Multiplier 100 1x 10x 100x 1000 x upfront engineering detailed engineering Upfront Engineering Detailed Engineering Refinement Engineering refinement engineering % Problems Solved 80 60 40 20 Stages of Development Process Pre S1 S2 S3 S4 S5 S6 S7 S8 1st Proto Stage 2nd Proto Stage 0 Early identification of critical areas Hybrid Engineering Accelerating refinement Page 8 1D Simulation 3D Simulation TEST
Agenda 1 From testing to simulating 2 Numerical answers to optimize the machines 3 A high relevant instance : PICANOL 4 Conclusion Page 9
Projet ESToMaD ESToMaD : Energy Software Tools for sustainable Machine Design Production machinery High ecological footprint Consume a lot of energy and resources Should be reduced for sustainable production Energy efficiency Important aspect of ecological footprint Should increase without losing machine performance Solution Take energy efficiency into account during the design of machines Page 10
Project Description Objective Develop a methodology and ICT tools to model, simulate, analyse and optimize energy flows and minimize losses throughout the whole machine Consortium Website www.estomad.org Page 11
Description of the system rapier wheel with gripper 3D mechanism cam&follower mechanism gearbox 3D mechanism Page 12
Differents Modeling Step to optimize the mechanism Component loss models with reasonable level of accuracy Accurate description of the dynamic behavior of the system Non Linear Advanced Analysis Page 13
1 2 3 4 5 6 7 Define the system and the subsystems to analyze. Simplify the system: remove subsystems with no contribution to energetic behavior. Equip each subsystem with power sensors at its physical ports. Define additional useful results/variables for the dashboard. Add the necessary sensors. Choose which graphic primitive will be used for each chosen result / variable. (e.g. arrows to represent power flows). Arrange the primitives on the scene in accordance with sketch layout or physical phenomena. Link primitive properties to chosen results/variables. Check the consistency of arrow directions and use post-processing functions to avoid scaling problems. Page 14
Energetic Analysis Usage of the model to asses energy loss distribution Gain insight in how dynamics/components influence energetic behavior Use the model to formulate design guidelines Page 15
Differents Modeling Step to optimize the mechanism Component loss models with reasonable level of accuracy Accurate description of the dynamic behavior of the system Non Linear Advanced Analysis Page 16
3D MECHANISM 3D mechanism Model dynamics (loads, velocities) Rotation vectors change in magnitude and orientation Need for multibody software AMESim calculates friction torque Page 17
Description of the numeric model cosimulation Page 18
Differents Modeling Step to optimize the mechanism Component loss models with reasonable level of accuracy Accurate description of the dynamic behavior of the system Non Linear Advanced Analysis Page 19
Inventing Direct Warp Control using Challenge Re-engineer the weaving machine backrest by a Direct Wrap Control DWC. Model a 5-meter-plus air-pressurized backrest (big deformation). Compute the stiffness performance under varying pressures Solutions LMS Samtech Samcef Solver Suite Benefits LMS Samtech Samcef offers reliable nonlinear analysis Ability to simulate the entire spectrum : per cycle, contact analysis as well as big deformation analysis Ability to create your own programming (time saver for specialized modeling exercises) «Today we work in NX with various LMS Samtech Samcef and other Siemens licenses. In the future it would be really nice if everything converges into one streamlined software environment.» Dimitri Coemelck - R&D engineer at Picanol Page 20 20XX-XX-XX Restricted Siemens AG 2014 All rights reserved.
VIDEO Page 21 20XX-XX-XX Restricted Siemens AG 2014 All rights reserved.
Agenda 1 LMS, A Siemens Business 2 Des solutions numériques pour optimiser vos machines 3 Un exemple concret : PICANOL 4 Conclusion Page 22
Complete product information visibility What If You Could Optimize These Attributes Across the Organization? NVH and Acoustics Durability Energy Management Safety Motion Dynamics Automation Controls Machine Frame Drives Electrical & Fluids Full Machine Multi-attribute balancing Machine integration Page 23
Thank you Smarter decisions, better products.