simulation in manufacturing - simando
TRANSCRIPT
2011 1/32
Think | Simulate | Succeed
Simulation in Manufacturing
2011
Outline
Company overview
Expertise
Products and services
Modeling and simulation
Simulation in manufacturing
Simulation in Lean Six Sigma/Design For Six Sigma
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Company Overview
Founded 2009
Limited Liability Company
Headquarters: Timisoara, ROMANIA
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Our mission:
Our vision:
SIMANDO delivers outstanding simulation, analysis and optimization software applications and services that enable its clients to better understand, design and run their processes and systems.
At SIMANDO, simulation is viewed as an important, multi-purpose component of the value chain. By this approach, we offer to our clients the most effective simulation-based tools and services that will enable them to maximize the results of their enterprises.
Expertise
Software Applications Development
Advanced algorithms and design patterns
Software architecture
Software development lifecycle methodologies
Functional and object oriented programming
2011
Industrial
Project and product development management
Computer Integrated Manufacturing
Industrial engineering and factory planning
Manufacturing, logistics, supply chain design
Transport and distribution networks
Continuous Improvement
Lean principles implementation
Six Sigma/Design For Six Sigma
Modeling and Simulation
Systems modeling, simulation and optimization
All simulation paradigms - discrete events, agent-based and system dynamics
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Expertise
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Our certifications Certified Six Sigma Black Belt American Society for Quality
Project Management Professional Project Management Institute
Certificate in Finance New York Institute of Finance
Oracle Certified Professional Java Programmer Oracle Corporation
Our clients’ benefits
Rapid understanding of their environment and
problems to solve
Solutions based on proven methods and technology
Efficient communication and professional project management
Consideration for a mix of aspects that impact the proposed solutions
Flexible, timely and cost efficient solutions
Products and Services
Products
Modeling and simulation component libraries
MANSIM™ - general manufacturing
SOLSIM ™ - photovoltaics manufacturing
LOGSIM ™ - warehousing and logistics
Specialized components for Lean Six Sigma applications
Services
Production, logistics, supply chain, healthcare, financial modeling and simulation
Training and assistance in simulation platforms and paradigms
Lean Six Sigma/Design For Six Sigma training and implementation
Product development and project management
Computer Integrated Manufacturing
Facilities planning
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Why Simulation ?
SIMULATION GIVES YOU ANSWERS!
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The future is of greater interest to me than the past, since that is where I intend to spend the rest of my life. ~ Albert Einstein
When?
Where?
What?
Who?
Why?
How?
!
Simulation Study Types
Simulation
Studies
System Design
New processes
New facilities
New concepts
Structural Design
Elements
Layout
Logic
Logical Design
Flow logic
Operations sequences
Priority rules
Parametric Design
Cycle times
Reliability requirements
Velocities, rates
Problem Solving
Diagnosis
Problem definition
Solution finding
Diagnosis
Problem definition
Testing Schemes
What-if scenarios analysis
Solution Validation
Sensitivity analysis
Continuous Improvement
Opportunity definition
Performance measurement
Performance improvement
Opportunity Definition
Benchmarking
Test Plans
Feasibility check
Plan Validation
Sensitivity analysis
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Simulation Benefits
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Convince clients of your operational capabilities
Safely analyze dangerous scenarios Implement your decisions
with confidence
Make prompt and correct decisions
Experiment and get fast feedback
Analyze the behavior of complex systems
Communicate ideas efficiently and credibly
Discover alternatives to unexpected roadblocks
Teach new concepts easily
Save money in short and medium term
Test fast, fail fast, adjust fast. ~ Tom Peters
Applicability Areas
Manufacturing
Key Performance Indicators FMEA Production flow design Planning and scheduling Resource estimation Capacity planning Total cost of ownership
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Lean Six Sigma
Stochastic process simulation Statistical analysis Variability elimination Pull mechanism design QOS metrics Dynamic VSM Benchmarking
Logistics and Supply Chain
Transport networks design Fleet planning & maintenance Warehouse design Operations optimization Supply chain planning
IT & Telecom
Wireless networks topology
Protocols design
Agent-based emergent behaviour analysis
QOS
Urban Development
Public utilities planning
Evacuation plans creation
Disaster recovery
Anti-terrorist measures
Healthcare
Resource estimation
QOS
Epidemics dynamics
Operations optimization
How we do it ?
Problem formulation
Objectives and plan definition
Model development
Data collection
Model conceptualization
Code verification
Model validation
Control
Implementation
Reporting
Experiments run and analysis
Design of experiments
Your trajectory to success with simulation
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Continuous improvement is better than delayed perfection. ~ Mark Twain
Modeling
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Specialized component libraries
Domain specific library components
2D/3D customizable animation
Fast and easy drag-and-drop layout modeling
Reusable models and components encourage continuous improvement!
Simulation models input/output data
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Text
Excel
Database
Webservice
XML
Text
Excel
Database
Webservice
XML
Run-time Charts
Simulation Model
Input Data
Output Data
CAD
Simulation in Manufacturing
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Assembly line simulation model
Creativity is thinking up new things. Innovation is doing new things. ~ Ted Levitt
Simulation in Manufacturing
Plant layout optimal design
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Detection and management of bottlenecks
60 sec
Rework Loop
Rework Loop
Rework Loop
A
B
30 sec
60 sec
60 sec
120 sec
120 sec
120 sec
120 sec
120 sec
120 sec
?
Simulation in Manufacturing
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Simulation in Manufacturing
Equipment ROI Calculation
Golden Equipment Silver Equipment Bronze Equipment
Cycle Time ………....... 30 sec MTBF_1 …..………… 5000 hrs MTTR_1 ……………........ 1 hrs MTBF_2 ……………… 7500 hrs MTTR_2 ………………… 0.5 hrs Yield ………………………. 99.6% Energy …………………. 10 kWh Price …………….… $1,500,000
Cycle Time ………....... 60 sec MTBF_1 …..………… 4000 hrs MTTR_1 ……………........ 2 hrs MTBF_2 ……………… 8500 hrs MTTR_2 ………………… 3 hrs Yield ………………………. 98.9% Energy …………………. 8 kWh Price ……………….… $850,000
Cycle Time ………....... 80 sec MTBF_1 …..………… 5000 hrs MTTR_1 ……………........ 1 hrs MTBF_2 ……………… 8000 hrs MTTR_2 ………………… 2 hrs Yield ………………………. 97.2% Energy …………………. 14 kWh Price ……………….… $450,000
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Simulation in Manufacturing
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Total Cost of Ownership
𝑻𝑪𝑶 =𝑻𝒐𝒕𝒂𝒍 𝑪𝒐𝒔𝒕𝒔 ($)
𝑻𝒐𝒕𝒂𝒍 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑮𝒐𝒐𝒅 𝑷𝒓𝒐𝒅𝒖𝒄𝒕𝒔 𝑶𝒗𝒆𝒓 𝑺𝒚𝒔𝒕𝒆𝒎′𝒔 𝑳𝒊𝒇𝒆
𝑻𝒐𝒕𝒂𝒍 𝑪𝒐𝒔𝒕𝒔($) = 𝑭($) + 𝑳($) + 𝑹($) + 𝒀($)
Where: F ($) = fixed costs for purchasing the system L ($) = fully burdened labor cost R ($) = recurring costs (consumables, maintenance, specialized support etc.) Y ($) = yield loss cost 𝒀($) = 𝑵 ∗ 𝑷($)
Where: N = number of defective product entities P ($) = value of the product entities in the specific production stage
Simulation in Manufacturing
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Total Cost of Ownership
𝑻𝒐𝒕𝒂𝒍 𝑵𝒖𝒎𝒃𝒆𝒓 𝒐𝒇 𝑮𝒐𝒐𝒅 𝑷𝒓𝒐𝒅𝒖𝒄𝒕 𝑬𝒏𝒕𝒊𝒕𝒊𝒆𝒔 = 𝑳 ∗ 𝑻 ∗ 𝒀 ∗ 𝑼 𝑷𝒓𝒐𝒅𝒖𝒄𝒆𝒅 𝑶𝒗𝒆𝒓 𝒕𝒉𝒆 𝑺𝒚𝒔𝒕𝒆𝒎′𝒔 𝑳𝒊𝒇𝒆
Where: L = lifetime of the production system T = throughput rate Y = composite yield U = equipment utilization
𝑼 = 𝟏 − 𝑺𝑴 + 𝑼𝑺𝑴 + 𝑨 + 𝑺 + 𝑸
𝑯
Where: SM = scheduled maintenance USM = unscheduled maintenance A = assist time S = standby time Q = qualification time H = total number of scheduled production hours per week
Simulation in Manufacturing
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Total Cost of Ownership
All variable/probabilistic elements in the formula can be tracked
and calculated by simulating realistically the system under study.
𝑻𝑪𝑶 =𝑭 $ + 𝑳 $ + 𝑹 $ + 𝒀($)
𝑳 ∗ 𝑻 ∗ 𝒀 ∗ 𝑼
Due to variable costs and probabilistic events associated with complex production systems, only simulation-based methods of calculating the TCO can provide correct and accurate estimates therefore.
Simulation in Manufacturing
Detailed modeling of components and manufacturing scenarios
Accurate timing and behavior of the modeled systems
Manual work, worker-machine and fully automated manufacturing modeling possibilities
Any type of production environment: jobbing, intermittent, mass production
Resources behavior described by state machines according to client/industry standards
Any type of Key Performance Indicator can be defined and tracked
Maintenance planning support
Ramp-up scenarios analysis
Inbound/outbound logistics and supply chain analysis and integration
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Simulation in Manufacturing
Line balancing and materials handling
Dispatching rules:
critical ratio, shortest processing time, FIFO, due date, etc.
Conveyors vs. Automated Guided Vehicles vs. Humans
Material flow optimization
Buffers capacities & policies (FIFO, LIFO, FEFO, custom)
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Simulation in Manufacturing
Lean manufacturing speed and quantity control and Six Sigma quality
Simulation offers support in reducing: Transport times
Inventory and buffers
Employee motion
Waiting
Overproduction
Defects
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Simulation in Manufacturing
Optimization of Key Performance Indicators
Work in process (WIP)
Manufacturing lead time
Equipment cycle times
Queuing, blocking, waiting, transport time
Throughput
Takt time
Equipment and human resources utilization
Energy, consumables, spare parts, waste
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Simulation in Manufacturing
Design and optimization of complex equipment
Utilization, throughtput, cycle time for cluster tools
Equipments with M:N mapping of process resources to handling units
Optimization of handling units movement and process resources allocation
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Process Chamber
Process Chamber
Process Chamber
Process Chamber
Process Chamber
Process Chamber
Process Chambers
IO Ports Multiple handling units on the same rail
Simulation in Manufacturing
Production planning and scheduling
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Production Planning
Forecast
Simulation
Feedback
Simulation in Lean Ops Implementation
Static Value Stream Map
Dynamic Value Stream Map (Simulation)
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Nature does constant value stream mapping – it's called evolution. ~ Carrie Latet
Simulation in Lean Ops Implementation
Single piece flow vs. batch processing analysis
Kanban (pull) mechanism design
Production leveling (heijunka)
Cycle, safety and buffer stocks calculation
Just In Time (JIT), Just in Sequence (JIS) inventory strategy design
Cellular operations design
Overall Equipment Effectiveness (OEE) calculation
Relation between demand and takt time analysis
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Define
Measure
Improve
Control
Analize
Simulation in Lean Six Sigma
Define Project Scope
Define Lean
Measures
Define Structure
and Variables
Develop Current State
VSM
Develop Simulation Model
Develop Dynamic
VSM
Identify Sources of Variation and
Waste
Optimize Process Parameters
Apply Lean
Techniques
Validate Improvement
Develop Future State
VSM
Develop DOE Plan Run Simulation
Experiments Analyze Process
Flow
Develop Control Strategy
Test Control Plans
Implement Control Plans
Monitor Performance Over
Time
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Simulation-based Lean Six Sigma Project Roadmap
Simulation in Design For Six Sigma
Design Produce/Build Deliver Support
Time
Cost vs. Impact
Impact
Potential is positive
(Impact > Cost)
Cost
Potential is negative (Impact < Cost)
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Impact of design stages on life cycle
Simulation in Design For Six Sigma
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Data collection Model building
Simulation model
Model analysis
Conclusions and reporting
Valid ?
Verified ?
Identify
Conceptualize
Optimize
Validate
Yes
No
No
Simulation-based DFSS Project Roadmap
SIMANDO Team
Thank you for your attention!
SIMANDO 9 Republicii Blvd Timisoara, TM 300159 ROMANIA Tel: + 40 356 172 021 Fax: + 40 356 172 017 [email protected] www.simando.com
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