Predicted uncertainty Tecnomatix Plant Simulation
Ir. Auke Nieuwenhuis/ 26 May 2015
Agenda
• Introduction to Kahoot • Tecnomatix Plant Simulation Introduction
• Plant Simulation Case Studies • Q&A
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Go to Kahoot
• • • •
Access WIFI network ‘WLAN-PUB’ Go to www.kahoot.it Enter the game PIN (will follow) And join the quiz
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Predicted uncertainty
Tecnomatix Plant Simulation Introduction
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Principle Process Simulation WHAT? • Transparent analysis of dynamic and complex systems • Optimization of process, capacity, lay-out, management and control • Intelligent support of investments
• Virtual process model with real process data
Existing or new system
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Simulation model
Experiments and results
How to Design a New System? Dimensioning: Buffers, machines, #operators?
Process flow: Order of process steps, decoupling points?
Design goals: •
Predictive behavior, reliability
•
Maximize system performance
•
Minimize effort and investment
•
Documents and communicate
Control: Who produces what, when, which resoures, pull or push? Restricted © cards PLM Solutions 2015 All rights reserved. Page 6
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Lay-out: Optimal location for machines, buffers, operators, supply-chain?
In- and Output Simulation Model Input •
Lay-out
•
Product mix, order pattern
•
Routings
•
Timings: set-ups, processing, MTBF, MTTR
•
Capacities
•
Planning, planning rules
•
Failures
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Simulation Model Dimensining: Buffers, machines, #operators
Control: Who, what, when, pull or push?
Process flow: Process flow, decoupling points?
Lay-out: optimal location resources?
Output •
Efficiency
•
Utillization
•
Waiting times
•
Throughput times
•
Costs
•
Revenue
•
Visualisation 2D/3D
Typical Users Plant Simulation WHAT? • Manufacturing companies • Logistics service providers (3pl, warehousing, distribution, supply chain management)
• System suppliers and machine builders (material handling, process lines, etc.) • Consultancy and engineering • Retailers
• Healthcare • Shipyards • Airports, mainports & terminals
• Government (rail, water, road traffic) and defense
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Typical Users Plant Simulation WHAT? • High level design • Conceptual • Schematic and flow based simulation • Low level of visualization, mainly for simulation purposes • High detail design • PLC • Operational system based simulation • High level of visualization, 3D, visualization also for communication purposes
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Advantages of Process Simulation WHAT? • Early detection and elimination of problems • Risk-free experimental environment • Test en compare of alternatives • Minimize investments • Optimize performance • Increase process understanding with visualization • Support on management decisions
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Business Issues Plant Simulation WHAT? • Increase volumes and / or efficiency. Can it be done with current process or are investments required? If investment is required, where to invest?
• Where to invest and what improvements can be expected? • Eliminate the effect of the bottleneck within the system • Dynamic modelling with every day uncertainties. Other tools are static and not visual, it is difficult to understand results or to share them with management and operators • What should the factory of the future look like and is the system flexible to cope with demand and product mix of the future? • Daily planning of resources is fuzzy and general
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Business Drivers Plant Simulation WHAT? • Savings on investments > 5-15%
• Decrease start up costs > 5-20% • Increase volumes > 15-20% • Decrease stock and throughput times > 20-60%
• Rule of Thump: 1 euro invested in simulation will return 12 euro!
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Plant Simulation Software Solution Data fit
2D, 3D, CAD, FactoryCAD
Generic modelling objects
Modeling
Data analyze
Simulation
Visualization
Generic Simulation Tools Statistic Wizard, Bottleneck Analyzer, Sankey chart, Attribute Explorer, Gantt Wizard
Process analyze
Generic Algorithm, Optimization Wizard, Layout Optimizer, Neural Networks, Sequencing Wizard
Optimization
Experiment Manager, Neutral Networks, Factor Analysis, Automatic Experiment Generation
Experiment Draft
PLC Testing, OPC Server
Process Automation
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Users Plant Simulation WHAT? Automotive OEMs
System Suppliers
Machine Builders
Shipyards
Audi Autovaz BMW DaimlerChrysler Honda Mazda Mitsubishi Nissan PSA Rolls-Royce Suzuki Vauxhall Volkswagen
Bosch EBM Papst Faurecia Hella Magna Modine Recticell SKF St. Gobain ZF
Comau Duerr Eisenmann Hoermann ibk Krones Kuka Nothelfer Thyssen Krupp TMS Voest Alpine
Babkock Chantier de l’Atlantique Fincantieri Flensburger Schiffsbau Gesellschaft Kockums Kvaerner Warnow Werft Meyer Werft Papenburg Thyssen Nordseewerke
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Users Plant Simulation WHAT? Engineering
Airports
DRC EDAG Fraunhofer Icarus Industrie Planung Fischer Isilog Life Sciences Logplan Pitotech PPI Protema
Dallas Denver Frankfurt Munich Schipol Aviation Airbus Rolls-Royce MTU BAE Systems Fairchild Dornier
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Heavy Industry
Process Industry
Caterpillar Freightline Volvo Trucks MAN Iveco Daimler Chrysler Trucks DAF Trucks Mack Trucks
BASF Bayer Ciba Henkel Proctor & Gamble Ratiopharm Wacker Semiconductor
Logistics SSI Schaefer Duerr Hoermann psb UPS PPI iSILOG Healthcare Erasmus MC LUMC Vreelandgroep AMC UMCG
DAF Trucks Challenges • Simulation of a complex production line • Check the proposed investments • Optimization of the batch sizes and automation rules Approach • Plant Simulation software (realistic and complete model) • Customized training for DAF Trucks personnel • Modelling done by DAF Trucks users Results • Very accurate and realistic models of a complex line • Investment in additional production equipment not necessary (€ 800.000 saving) • Extension of material handling necessary to reduce and relieve manual tasks • Highly improved knowledge of the production process Restricted © cards PLM Solutions 2015 All rights reserved. Page 16
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Procter & Gamble - warehousing Challenges • Simulation of several newly build warehouses world wide • Optimization of strategies and early validation • Required capacity definition Approach • Plant Simulation software (realistic and complete model) • Warehousing and Logistics Library • Modelling and simulation done by cards, result analysis by cards and P&G Results • Investment of construction work reduced to minimum • Early identification of bottlenecks and precise elimination if needed • Reduce startup time for new processes Restricted © cards PLM Solutions 2015 All rights reserved. Page 17
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Constellation Brands – Corona case 1 Challenges • Simulation of LGV transportation from bottle and can filling lines to the ASRS • Over 100 LGVs work in a tight and limited space • Validation that the proposed system can work Approach • Plant Simulation software (realistic and complete model) • Warehousing and Logistics Library • Modelling and simulation by cards, result analysis by cards en CBi Results • Savings on the number of LGVs needed (over $450.000 savings) • Allocation algorithm of LGV trip improved • In depth knowledge on system behavior during the implementation (predictive) Restricted © cards PLM Solutions 2015 All rights reserved. Page 18
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Constellation Brands – Corona case 2 Challenges • Simulation of train movements around brewery • Over 360 train lorry movements per day • Stress test and sensitivity analysis of train movements and connected processes Approach • Plant Simulation software (realistic and complete model) • Modelling and simulation by cards, result analysis by cards and CBi Results • Define the maximum process timing of the sub-processes • Define the daily throughput and relocation of the train lorries • Improve the negotiation position of CBi with the train operator
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Nuplex Challenges • Simulation of a continuous flow process • Increase of the capacity of a complete plant • Validate the effect the proposed of investments Approach • Plant Simulation software (realistic and accurate model) • Runtime model and user interface • Modelling done by cards, simulation done by cards and Nuplex Results • Realistic and accurate model of a continuous process • Nuplex gets the maximum benefit of their investments at lowest cost • Strong increase in process knowledge
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Marel Challenges • Simulation of two alternative welding robots • Proof the need for the robot cell with the expected growth Approach • On site modelling of the two options with the same input data • Modelling done by cards, simulation done by cards and Marel Results • Models proofs by quantitive and qualitative numbers what cell is preferred with respect of throughput and WIP • Model demonstrates the importance of throughput and WIP
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Questions?
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International user meeting Upcoming events
Plant Simulation International User Meeting Siemens offices, Stuttgart, Germany June 16 and 17 Complementary
Plant Simulation Warehouse and Logistics training Siemens offices, Stuttgart, Germany June 18 Complementary
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Contact Auke Nieuwenhuis Business Development cards PLM Solutions De Maas 22a | 5684PL Best T: +31 499 371990 | F: +31 499 372690 | M: +31 6 224 85984
[email protected] | www.cardsplmsolutions.com
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