simulation in manufacturing - simando

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

2011 2/32

Company Overview

Founded 2009

Limited Liability Company

Headquarters: Timisoara, ROMANIA

2011 3/32

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

2011 5/32

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!

2011 7/32

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

2011 8/32

Simulation Benefits

2011 9/32

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

2011 10/32

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

2011 11/32

Continuous improvement is better than delayed perfection. ~ Mark Twain

Modeling

2011 12/32

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

2011 13/32

Text

Excel

Database

Webservice

XML

Text

Excel

Database

Webservice

XML

Run-time Charts

Simulation Model

Input Data

Output Data

CAD


2011 14/32

Assembly line simulation model

Creativity is thinking up new things. Innovation is doing new things. ~ Ted Levitt


Plant layout optimal design

? 2011 15/32

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

?


2011 16/32


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

2011 17/32


2011 18/32

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


2011 19/32


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


2011 20/32


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.


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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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 22/32


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

2011 23/32


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

2011 24/32


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

2011 25/32

Process Chamber

Process Chamber

Process Chamber

Process Chamber

Process Chamber

Process Chamber

Process Chambers

IO Ports Multiple handling units on the same rail


Production planning and scheduling

2011 26/32

Production Planning

Forecast

Simulation

Feedback

Simulation in Lean Ops Implementation

Static Value Stream Map

Dynamic Value Stream Map (Simulation)

2011 27/32

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

2011 28/32

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

2011 29/32

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)

2011 30/32

Impact of design stages on life cycle

Simulation in Design For Six Sigma

2011 31/32

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

2011 32/32

simulation in manufacturing - simando

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