The Simulation Project

Simulation Project Steps

a.- Problem Definition

b.- Statement of Objectives

c.- Model Formulation and Planning

d.- Model Development and Data Collection

e.- Verification

f.- Validation

g.-Experimentation

h.- Analysis of Results

i.- Reporting and Implementation

Basic Principles of Modeling

• To conceptualize a model use– System knowledge– Engineering judgement– Model-building tools

• Remodel as needed

• Regard modeling as an evolutionary process

Manufacturing Systems Simulation

Manufacturing Systems• Material Flow Systems

– Assembly lines and Transfer lines– Flow shops and Job shops– Flexible Manufacturing Systems and Group

Technology

• Supporting Components– Setup and sequencing– Handling systems– Warehousing

Characteristics ofManufacturing Systems

• Physical layout• Labor• Equipment• Maintenance• Work centers• Product• Production Schedules

• Production Control• Supplies• Storage• Packing and Shipping

Modeling Material Handling Systems

• Up to 85% of the time of an item on the manufacturing floor is spent in material handling.

• Subsystems– Conveyors– Transporters– Storage Systems

Goals and Performance Measures

• Some relevant questions– How a new/modified system will work?– Will throughput be met?– What is the response time?– How resilient is the system?– How is congestion resolved?– What staffing is required?– What is the system capacity?

Goals of Manufacturing Modeling

• Manufacturing Systems– Identify problem areas– Quantify system performance

• Supporting Systems– Effects of changes in order profiles– Truck/trailer queueing– Effectiveness of materials handling– Recovery from surges

Performance Measuresin Manufacturing Modeling

• Throughput under average and peak loads

• Utilization of resources, labor and machines

• Bottlenecks

• Queueing

• WIP storage needs

• Staffing requirements

• Effectiveness of scheduling and control

Some Key Modeling Issues

• Alternatives for Modeling Downtimes and Failures– Ignore them– Do not model directly but adjust processing

time accordingly– Use constant values for failure and repair times– Use statistical distributions

Key Modeling Issues -contd

• Time to failure– By wall clock time– By busy time– By number of cycles– By number of widgets

• Time to repair– As a pure time delay– As wait time for a resource

Key Modeling Issues -contd

• What to do with an item in the machine when machine downtime occurs?– Scrap– Rework– Resume processing after downtime– Complete processing before downtime

Example

• Single server resource with processing time exponential (mean = 7.5 minutes)

• Interarrival time also exponential (mean = 10 minutes)

• Time to failure, exponential (mean=100 min)

• Repair time, exponential (mean 50 min)

Example 5.1 -contd

• Queue lengths for various cases– Breakdowns ignored– Service time increased to 8 min– Everything random– Random processing, deterministic breakdowns– Everything deterministic– Deterministic processing, random breakdowns

Trace Driven Models

• Models driven by actual historical data

• Examples– Actual orders for a sample of days– Actual product mix, quantities and sequencing– Actual time to failure and downtimes– Actual truck arrival times

A sampler of manufacturing models from WSC’98

• Automotive– Final assembly conveyor systems– Mercedes-Benz AAV Production Facility– Machine controls for frame turnover system

A sampler of manufacturing models from WSC’98 -contd

• Assembly– Operational capacity planning: daily labor

assignment in a customer-driven line at Ericsson

– Optimal design of a final engine drop assembly station

– Worker simulation

A sampler of manufacturing models from WSC’98 -contd

• Scheduling– Batch loading and scheduling in heat treat

furnace operations– Schedule evaluation in coffee manufacture– Manufacturing cell design

A sampler of manufacturing models from WSC’98 -contd

• Semiconductor Manufacturing– Generic models of automated material handling

systems at PRI Automation

– Cycle time reduction schemes at Siemens

– Bottleneck analysis and theory of constraints at Advanced Micro Devices

– Work in process evolution after a breakdown

– Targeted cycle time reduction and capital planning process at Seagate

A sampler of manufacturing models from WSC’98 -contd

• Semiconductor Manufacturing - contd– Local modeling of trouble spots in a Siemens

production facility– Validation and verification in a

photolithography process model at Cirent– Environmental issues in filament winding

composite manufacture– Order sequencing

A sampler of manufacturing models from WSC’98 -contd

• Materials Handling– Controlled conveyor network with merging

configuration at Seagate– Warehouse design at Intel– Transfer from warehouse to packing with

Rapistan control system– Optimization of maintenance policies

Manufacturing Simulators

• ProModel• Witness• Taylor II• AutoMod• Arena• ModSim and

Simprocess

• SimSource• Deneb• Valisys (Tecnomatix)• Open Virtual Factory• EON• Simul8