Job Shop Optimization

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Job Shop Optimization

• December 8, 2005
• Dave Singletary
• Mark Ronski

2
Introduction
3
Problem Statement

• Open Ended
• Optimize a job shop
• Utilize Pro Model software to optimize
• Cost Model
• SimRuner Module

4
Problem Statement (Cont.)

• Optimized Model For
• Delivery Schedule
• Q Size
• Takt Time
• Number of Workers

5
Outline

• Overview Pro Model
• Job Shop Model
• Optimization Terms
• Results

6
Pro Model Overview
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Pro Model

• Process optimization and decision support
  software model
• Serving
• Pharmaceutical
• Healthcare
• Manufacturing industries.
• Helps companies
• Maximize throughput
• Decrease cycle time
• Increase productivity
• Manage costs.

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Pro Model Cont

• Pro Model technology enables users to
• Visualize
• Analyze
• Optimize
• Helps make better decisions and realized
  performance and process optimization objectives.

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What Pro Model Is

• Create 3-D Simulation of Shop Space
• Machines X-Y Coordinates
• Time
• Alter Machine, Worker, and Cost Parameters to
  Simulate Outcome
• Tools to Optimize Shop Model

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Pro Model Simulation
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Job Shop Model
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Default Shop Layout
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Parts to Be Manufactured

• 3 Parts to be Manufactured
• 5 Machining Processes
• 4 Process Per Part

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Machining Processes
Part N101
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Machining Process (Cont.)
Part N201
DEBURR 7 min
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Machining Process (Cont.)
Part N301
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Machining Process Summary
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Process Variability

• Default Job Shop Model
• Constant Setup Time
• Constant Machining Time
• No Machine Failure
• Introduce Variability to Mimic Actual Conditions

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Process Variability (Cont.)

• Normally Distributed
• Setup Time
• Machining Time
• Machine Failure
• Average Time Default Value
• Standard Deviation ¼ Average Time

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Normal Distribution

• In a normal distribution
• 50 of samples fall between 0.75 SD
• 68.27 of samples fall between 1 SD
• 95.45 of samples fall between 2 SD
• 99.73 of samples fall between 3 SD

Xbar Mean
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COST
Machine Cost and Life
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COST
Man Power Cost and Initial Part Cost
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COST
Tool Cost, Tool Life, and Hours Down to Change
Part
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Workers

• Speed 120 feet per minute
• With or Without Carrying a Part
• Pick Up or Place Object in 2 seconds
• Logic
• Stay at Machine Until Q is Empty
• Go to Closest Unoccupied Machine
• Go to Break Area When Idol

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Optimization Terminology
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Takt Time

• Takt Time ratio of available time per period to
  customer demand.
• Longest operation must not exceed Takt time.
• If Takt time exceeded customer demand is not met.

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Kanban Capacity

• Kanban Maximum number of parts allowed between
  stations
• Size of Deburr Q, Mill Q, Drill Q
• When Q is full machine prior to Q must shut down
• Pull manufacturing controlled by Kanban
• Open slot in the Q causes the previous machine to
  make a part.

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Kanban Capacity (Cont.)

• Each part in Q has value added
• Parts in Q are not earning the company money
• Increase in Kanban capacity increases production
  rate.
• Upper limit exists

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Just In Time (JIT) Production

• Receive supplies just in time to be used.
• Produce parts just in time to be made into
  subassemblies.
• Produce subassemblies just in time to be
  assembled into finished products.
• Produce and deliver finished products just in
  time to be sold.

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Optimization and Results
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Takt Time Optimization

• Slowest process must be faster than required Takt
  time.
• Checked if job shop can meet demand of 229 parts
  per week.
• Determines if
• More Machines Required
• Faster Machines Required

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Takt Time Calculations

• Takt Time for job shop
• Longest Operation 7 minutes
• Drill N101 and Deburr N201
• Conclusions
• Current machine process times less than Takt time
• Margin provided for variability and failure.

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Kanban Capacity Optimization

• Default Simulation
• Run to Detect Inadequate Kanban Capacity
• Optimized Simulation
• Smallest Allowable Kanban Capacity Resulted in Q
  0 Full Over 1 Month of Production
• Run for Default Receiving Delivery Schedule

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Kanban Capacity Default
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Optimized Kanban Capacity
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Delivery Schedule Optimization

• Delivery Schedule
• The Timed Arrival of Raw Material to Receiving.
• Default Simulation
• Run to Determine the Effect of Delivery Schedule
  on Production

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Default Production Rate
Waiting For Parts to Arrive
158 Hours to Make All Parts
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Delivery Schedule Optimization

• Optimized Simulation
• Delivery Schedule Altered to Simulate Just in
  Time Production
• All Parts for 4 Weeks Received at Start of Week

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Optimized Production Rate
No Breaks in Production Due to No Parts in
Receiving
136 Hours to Make All Parts
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Delivery Schedule Conclusions

• Option 1 3 Full Time Employees Not Required for
  Part Demand
• Cost Savings
• Option 2 Increase Production
• Only if Market Demand Will Meet Increased
  Production

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Resource Optimization for Max Production

• Default Model Setup
• 3 Workers
• Optimized Model
• Maximize Production
• Minimize Worker Down Time
• Get Maximum Value Out of Workers
• During Worker Down Time No Value Added

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Resource Optimization Model

• Pro Model Sim Runner
• Optimizes Macro
• Varies Number of Workers 110
• Maximizes Weighted Optimization Function F
• A and B are Weighting Constants
• N101, N201, N301 is Average Time in System for
  Each Part
• Pworkers Percent Utilization of Workers ()

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Resource Optimization Model (Cont.)

• Values of Constants
• A Ave. Time in Sys. Constant
• Set Equal to 1
• B Percent Utilization of Workers Const.
• Equal in Importance to Ave. Time in Sys.
• Calculating B Through Default Values

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Resource Optimization Results

• Sim Runner Calculated 3 Workers to Optimize Job
  Shop
• Current Default Value
• Important Result
• Increasing Workers Will Increase Production But
  Decrease Return on Worker Cost
• Must Buy New Machines to Stay Optimized and
  Increase Production

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Conclusions
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Job Shop Optimization

• Optimize for Currant Demand
• Alter Q Size
• Increase Deburr and Mill, Decrease Turning and
  Grinding
• Remove Bottle Necks
• Decrease Lost Profits Due to Parts Sitting in
  System
• Switch to Just In Time Production
• Decrease Shop Downtime Due to Waiting for Parts

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Job Shop Optimization (Cont.)

• Optimize for Increased Demand
• Purchase New Machines
• Increase Production Not at the Expense of Worker
  Utilization
• Switch to Just In Time Production
• Decrease Shop Downtime Due to Waiting for Parts
• Revaluate Takt Time
• Ensure Demand Will Be Met

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Pro Model Recommendation

• Sim Runner Difficult to Use
• Non Robust Optimization Technique
• Difficult to Compare Parameters that have
  Different Units
• Good At Modeling Shop Layout and Work Flow
• Easy to Find Bottle Necks

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Questions ?
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References

• Schroer, Bernard J. Simulation as a Tool in
  Understanding the Concepts of Lean Manufacturing.
  University of Alabama Huntsville.
• Gershwin, Stanley B. Manufacturing Systems
  Engineering. Prentice Hall New Jersey, 1941.
• Kalpakjian, S. and Schmid, R. Manufacturing
  Engineering and Technology. Fourth Edition,
  Prentice Hall New Jersey, 2001.