Toy Airplane Manufacturing

Ted PelzerTodd Madole

Christian Mickelson

Outline

Problem statement Assumptions Deterministic Modeling As-is model To-be model Best solution

Problem Statement A toy company produces 3 types of

planes Expected demand increase of 30% Travel in batches of 24 using AGVs 8 hours of production in one day Determine the total machines, AGVs

and operators required

Given Data

Opn Description Operation Time Resource Move Logic

10 Die Casting 3 min (outputs 6 parts) Automated die caster.3 min

20 Cutting Triangular(.25,.28,.35) Cutter none

30 Grinding Sample Times: .23 .22 .26 .22 .25 .23 .24 .22 .21 .23 .20 .23 .22 .25 .23 .24 .23 .25 .47 .23 .25 .21 .24 .22 .26 .23 .25 .24 .21 .24 .26

Grinder .2 min

40 Coating 12 min per batch of 24 Coater .2min

50 Inspection and Packaging Triangular(.27,.30,.40) Packager exits with 88% yield

Assumptions Ignored statistical outliers Move times determined speed and

distances Batches consist of similar plane type Operation times are the same for each

plane Any retooling is assumed in operation time

Number of operators must equal number of machines

Deterministic Modeling

(Assuming worst case scenario for operation times)

Processing Time * Total Planes = Total minutes required Total Minutes required /Total time in day = Total Machines

needed

Cutter: .35 min * 4300 planes = 1505 minutes required 1505/480 = 3.1 machines => 4 Cutting

machines

As-Is Model

As-Is Model Every 30 minutes a Die Casting machine

needed to be serviced Repair time is N(8,2)

Resource Quantity Average UtilizationDie Caster 8 63.67%Cutter 4 74.49%Grinder 3 78.47%Coater 5 78.00%Packager 2 82.10%

AGV 3 6.08%Mechanic 3 42.58%

AGV Analysis

Analyzed AGV path networks Both needed 3 AGVs

Utilization % Notes:1-Path Network 30.40% Less safe, more area

is covered

3-Path network 8.01% More Safe, small area covered. Also no collisions possible

To-Be

Demand increase of 30%

Resource Quantity Change Average UtilizationDie Caster 10 +2 67.12%Cutter 5 +1 78.22%Grinder 4 +1 77.46%Coater 6 +1 84.89%Packager 3 +1 71.58%

AGV 3 0 8.01%Mechanic 3 0 63.42%

Best Model

Reduce downtime to every 120 minutes

Percent Yield Increased to 3-Sigma Reduced scrap from 805 to 63 planes Resource Quantity Change Average Utilization

Die Caster 8 -2 74.30%Cutter 4 -1 86.89%Grinder 4 0 68.79%Coater 5 -1 90.36%Packager 2 -1 94.61%

AGV 3 0 7.15%Mechanic 1 -2 42.36%

Conclusion Implement the creative solution if possible. Increasing the efficiency Reducing the overall number of machines in

the facility and increasing quality will Reduce machine costs Reduce workforce costs Reduce material costs Reduce WIP