2. SIMANDO is a global management and technology consulting firm with a high
focus on decision support systems and operational excellence. We partner with
client organizations in all industrial sectors to address their most important
challenges and develop complete solutions that will enable them to achieve
their objectives and make significant improvements in their performance. Our
customized approach combines innovative technology, systems thinking and
passion for operational excellence. This ensures that our solutions enable our
clients to achieve sustainable competitive advantage by optimized operations
and responsiveness to the current dynamic business environment.
Founded in 2009, SIMANDO is a private company with its headquarters in
Timisoara, Romania. For more information, please visit:
www.simando.com
3. Outline
About SIMANDO
Services and Products
Factory Performance Optimization Framework
Analytical Methods for Performance Analysis & Improvement
Simulation in Manufacturing
Lean Six Sigma for Manufacturing
2011 3/35
4. About SIMANDO
Company founded in 2009
Privately owned, LLC
Headquarters: Timisoara, ROMANIA
Mission
At SIMANDO, our primary mission is to help our clients make substantial, continuous improvement in their performance. We
accomplish this by providing them with outstanding technology solutions and consulting services to increase their excellence
degree at all levels.
Vision
We strive to be the company that understands perfectly its clients' objectives, always delivers quantifiable results and
maximizes the financial and trust investments made by its clients.
Our Certifications
Certified Six Sigma Black Belt Project Management Professional
(American Society for Quality) (Project Management Institute)
Certificate in Finance Oracle Certified Professional Java
(New York Institute of Finance) Programmer
(Oracle Corporation)
2011 4/35
5. Expertise
Modeling and Simulation Operational Excellence
Systems modeling, simulation and optimization Lean Six Sigma Transformation
All simulation paradigms - discrete events, agent- Design for Six Sigma
based and system dynamics
Toyota Production System
Statistics
Theory of Constraints
Product Development
Software Applications Development Industrial
Advanced algorithms and design patterns Project and product development management
Software architecture
Computer Integrated Manufacturing
Software development lifecycle methodologies
Industrial engineering and factory planning
Functional and object oriented programming
Manufacturing, logistics, supply chain design
Database Management Systems
Transport and distribution systems
MRP/ERP Systems
2011 5/35
6. Services and Products
Services
Production, logistics, supply chain, healthcare engineering , modelling and simulation
Operations optimization
Lean Six Sigma/Design For Six Sigma training and implementation
Training and assistance in simulation models development
Product development and project management
Computer Integrated Manufacturing
Products
Modeling and simulation component libraries
MANSIM™ - general manufacturing
SOLSIM ™ - photovoltaics manufacturing equipment
LOGSIM ™ - warehousing and logistics
Specialized software applications for Lean Six Sigma, planning and scheduling
2011 6/35
7. Factory Performance Optimization
Industrial
Engineering
Information
Six Sigma
Technology
Factory
Performance
TRIZ Lean
Theory of
Constraints
Synergistic framework for continuous significant improvement of production and operations
2011 7/35
8. Factory Performance Leverage Points
1st Dimension
1st Dimension
Products and processes selection
Factory location, size and layout
2nd Dimension
Factory workstations and machines
Factory personnel
Material handling systems
Supplies and spare parts inventory 2nd Dimension
Degree of automation
3nd Dimension
Jobs starts protocol
Preventive maintenance protocols
Personnel allocation protocols
Batching protocols
Dispatching rules and scheduling
Waste reduction programs
The 3 Dimensions of Manufacturing 3rd Dimension
Investment
Manufacturing Performance
2011 8/35
10. Why Simulation ?
What?
Where? Who? The future is of greater interest
to me than the past, since that
is where I intend to spend the
! rest of my life.
When? Why? ~ Albert Einstein
How?
BECAUSE … SIMULATION GIVES US ANSWERS!
2011 10/35
11. Simulation Study Types
Simulation
Studies
System Design Problem Solving Continuous Improvement
New processes Diagnosis Opportunity definition
New facilities Problem definition Performance measurement
New concepts Solution finding Performance improvement
Structural Design Diagnosis Opportunity Definition
Elements Problem definition Benchmarking
Layout
Logic
Logical Design Testing Schemes Test Plans
Flow logic What-if scenarios analysis Feasibility check
Operations sequences
Priority rules
Parametric Design Solution Validation Plan Validation
Cycle times Sensitivity analysis Sensitivity analysis
Reliability requirements
Velocities, rates
2011 11/35
12. Simulation Benefits
Analyze the behavior of
Experiment and get complex systems
Make prompt and
fast feedback
correct decisions
Convince clients of your
operational capabilities Communicate ideas
efficiently and credibly
Teach new Test fast, fail fast, adjust fast.
concepts easily
~ Tom Peters
Discover alternatives to
unexpected roadblocks
Save money in short
and medium term
Safely analyze
dangerous scenarios Implement your decisions
with confidence
2011 12/35
14. How We Do It ?
Continuous improvement is better
than delayed perfection.
~ Mark Twain
Problem formulation
Objectives and plan definition
Control
Model conceptualization
Data collection
Your trajectory to success Implementation
with simulation
Reporting
Model development
Experiments run and analysis
Code verification
Design of experiments
Model validation
2011 14/35
15. Modeling
Reusable models and components encourage continuous improvement!
Specialized
component
libraries
2D/3D
customizable
animation
Domain specific
library components
Fast and easy
drag-and-drop
layout modeling
2011 15/35
16. Simulation Models Input/Output Data
CAD Run-time Charts
Text Text
Excel Excel
XML Simulation Model XML
Input Output
Database Database
Data Data
Webservice Webservice
2011 16/35
17. Simulation in Manufacturing
Creativity is thinking up new things.
Innovation is doing new things.
Assembly line simulation model
( http://simando.com/resources/applications/35 ) ~ Ted Levitt
2011 17/35
21. Simulation in Manufacturing
Total Cost of Ownership
������������������������������ ������������������������������ ($)
������������������ =
������������������������������ ������������������������������������ ������������ ������������������������ ������������������������������������������������ ������������������������ ������������������������������������′ ������ ������������������������
������������������������������ ������������������������������($) = ������($) + ������($) + ������($) + ������($)
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
������($) = ������ ∗ ������($)
Where:
N = number of defective product entities
P ($) = value of the product entities in the specific production stage
2011 21/35
22. Simulation in Manufacturing
Total Cost of Ownership
������������������������������ ������������������������������������ ������������ ������������������������ ������������������������������������������ ������������������������������������������������ = ������ ∗ ������ ∗ ������ ∗ ������
������������������������������������������������ ������������������������ ������������������ ������������������������������������′ ������ ������������������������
Where:
L = lifetime of the production system
T = throughput rate
Y = composite yield
U = equipment utilization
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
2011 22/35
23. Simulation in Manufacturing
Total Cost of Ownership
������ $ + ������ $ + ������ $ + ������($)
������������������ =
������ ∗ ������ ∗ ������ ∗ ������
All variable/probabilistic elements in the formula can be tracked
and calculated by simulating realistically the system under study.
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.
2011 23/35
24. 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 controlled by highly detailed state machines according to machine specs
Any type of Key Performance Indicator can be defined and tracked
Ramp-up scenarios analysis
Inbound/outbound logistics and supply chain analysis and integration
Declustering of job starts and maintenance
Load management scheme design
2011 24/35
25. 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)
2011 25/35
26. Simulation in Manufacturing
Lean manufacturing speed and quantity control and Six Sigma quality
Simulation offers support in finding solutions to reduce:
Transport time
Inventory and buffers
Employee motion
Waiting
Overproduction
Defects
2011 26/35
27. Simulation in Manufacturing
Optimization of Key Performance Indicators
Work in process (WIP)
Load-adjusted cycle time efficiency
Manufacturing lead time
Equipment cycle times
Queuing, blocking, waiting, transport time
Throughput
Equipment and human resources utilization
Energy, consumables, spare parts, waste
Spares and supplies inventory levels and variability
2011 27/35
28. Simulation in Manufacturing
Design and optimization of complex equipment
Utilization, throughput, cycle time for cluster tools
Equipment with M:N mapping of process resources to handling units
Optimization of handling units movement and process resources allocation
Process Process Process Chambers
Chamber Chamber
Process
Chamber
Multiple handling
units on the same rail IO Ports
Process
Chamber
Process Process
Chamber Chamber
2011 28/35
29. Simulation in Manufacturing
Production planning and scheduling
Feedback
Simulation
Production Forecast
Planning
2011 29/35
30. Simulation in Lean Implementation
Static Value Stream Map
Nature does constant value stream
mapping – it's called evolution.
~ Carrie Latet
Dynamic Value Stream Map (Simulation)
2011 30/35
31. Simulation in Lean 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
2011 31/35
32. Simulation in Lean Six Sigma
Define Define Define
Define Project
Scope
Lean
Measures
Structure
and Variables
Develop Develop Identify Sources
Measure Current State
VSM
Develop
Simulation Model
Dynamic
VSM
of Variation and
Waste
Analize Develop DOE Plan
Run Simulation
Experiments
Analyze Process
Flow
Apply Develop
Improve Optimize Process
Parameters
Lean
Techniques
Validate
Improvement
Future State
VSM
Test Implement Monitor
Control Develop Control
Strategy
Control
Plans
Control
Plans
Performance Over
Time
Simulation-based Lean Six Sigma Project Roadmap
2011 32/35
33. Design For Six Sigma
Cost vs. Impact Cost
Potential is negative
(Impact < Cost)
Potential is positive
(Impact > Cost)
Impact
Time
Design Produce/Build Deliver Support
Impact of design stages on life cycle
2011 33/35
34. Simulation in Design For Six Sigma
Identify Simulation-based DFSS Project Roadmap
Model building Data collection
Conceptualize Simulation model
No
Verified ?
Optimize No
Yes
Valid ?
Model analysis
Validate Conclusions and reporting
2011 34/35
35. Thank you for your attention!
SIMANDO Team
SIMANDO LLC
9 Republicii Blvd
Timisoara, TM 300159
ROMANIA
Tel: +40 356 172 021
Fax: +40 356 172 017
E-mail: info@simando.com
Web: www.simando.com
