The Simulation Project

1
The Simulation Project
2
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

3
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

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Manufacturing Systems Simulation
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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

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Characteristics ofManufacturing Systems

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

• Production Control
• Supplies
• Storage
• Packing and Shipping

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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

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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?

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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

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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

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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

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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

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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

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Example

• Single server resource with processing time
  exponential (mean 7.5 minutes)
• Interarrival time also exponential (mean 10
  minutes)
• Time to failure, exponential (mean100 min)
• Repair time, exponential (mean 50 min)

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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

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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

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A sampler of manufacturing models from WSC98

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

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A sampler of manufacturing models from WSC98
-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

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A sampler of manufacturing models from WSC98
-contd

• Scheduling
• Batch loading and scheduling in heat treat
  furnace operations
• Schedule evaluation in coffee manufacture
• Manufacturing cell design

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A sampler of manufacturing models from WSC98
-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

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A sampler of manufacturing models from WSC98
-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

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A sampler of manufacturing models from WSC98
-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

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Manufacturing Simulators

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

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