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Exercise 5.A

Sequencing

5 part types are entering to a typical system with equal probability. Time of arrival is

exponentially distributed with a mean of 1 minutes the following processes are to be

undergone by the parts inside the plant. All the parts will not follow the same set of 

operations and all operations are not needed for the parts. The operations available in the

 plant are !rilling" #ainting" $inishing and #ac%ing.

Part A  follows !rilling" #ainting" finishing and pac%ing as the sequence of operations.

Similarly Part Bfollows !rilling & finishing & painting & finishing &pac%ing.Part C follows

#ainting &finishing and pac%ing.Part D follows #ainting & finishing & painting' pac%ing and

Part E follows drilling & #ainting' finishing & painting and pac%ing.

The #rocessing time in !rilling was T()A *"+"5, minutes" #ainting #rocessing time was

uniform with a mean of - inutes. $inishing processes consumes a normal time with 1/ and

0 at the mean and standard deviation. #ac%ing time is very little and can be negligible in this

case. (un the simulation for +/ hours and collect the statisticsof various part types arrival

and exit" machine utili2ation and average queue times.

E3E(4)SE 5'

67S S87# 7!E9):;

A layout for our small manufacturing system is shown in fig. The system to be modeledconsists of part arrivals" four manufacturing cells" and part departures. 4ells 1" 0" and + each

have a single machine< 4ell has two machines. The two machines at 4ell are not

identical< one of these machines is a newer model that can process parts in /= of the time

required by the older machine. The system produces three part types" each visiting a different

sequence of stations. The part steps and process times *in minutes, are given in table. All

 process times are triangularly distributed< the process times given in table at 4ell are for the

older *slower, machine.

The )nter'arrival times between successive part arrivals *all types combined, are

exponentially distributed with a mean of 1 minutes< the first part arrives at time /. The

distribution by type is 0-=" #art 1< +=" #art 0< and 0-=" #art . #arts enter from the left"exit at the right and move only in cloc%wise direction through the system. $or now we>ll

assume that the time to move between any pair of cells is two minutes" regardless of the

distance *we>ll fix this up later,. ?e want to collect statistics on resource utili2ation" time and

number in queue" as well as cycle time *time in system" from entry to exit, by part time.

)nitially" we>ll run our simulation for 0 hours.

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#art Type 4ell@Time 4ell@Time 4ell@Time 4ell@Time 4ell@Time

11 0 +

-""1/ 5""1/ 15"0/"05 "10"1-

01 0 + 0

11"1"15 +"-" 15"1"01 -""10 0B""

0 1

B""11 B"1/"1 1"0"0

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ASS);:E:T 5

67S S87# 7!E9):;

A part arrives every ten minutes to a system having three wor%stations *A" " and 4," where

each wor%station has a single machine< the first part arrives at time /. There are four part

types" each with equal probability of arriving. The process plans for the four part types are

given below. The entries for the process times are the parameters for a triangular distribution.

*in minutes,

#art

Type4ell@Time 4ell@Time 4ell@Time

1A 4

5.5".5"1.5 .5"1+.1" 1.B

0A 4

."1.5"1.1 "15"01 15"1"01

A

.+"10"15.- 5." .5" 1.B

+ 4

.0" 10.-" 1- .-" 11.+" 1+.0

Assume that the transfer time between arrival and the first station" between all stations" and

 between the last station and the system exit is three minutes. Cse the Sequence feature to

direct the parts through the system and to assign the processing times at each station. Cse theSets feature to collect cycle times *total time in system, or each of the part types separately.

Animate your model *including part transfers, and run the simulation for 1/"/// minutes.