Performance evaluation of a Hybrid Flow Shop using Jsim | Virtual Learning Factory Toolkit

Virtual Learning Factory Toolkit

The objective is to do the performance evaluation of the given demo case using JMT software

Case Description

The Hybrid flow shop is composed of 5 machines and 5 buffers which are connected accordingly. The processing time of each machine varies according to the part(classes).

Formal model

Performance Evaluation

Open JSIM graph from the various tools in the home panel of JMT software

Select the source and sink icons in the toolbar and then place it in the workspace

Insert machines into the workspace by clicking the queue icon in the toolbar

Click on the connect stations icon and then connect all the stations with regard to the case
Clicking on this icon optimizes the layout

Click on the Add class button in order to the add the parts.
Select open in type option

Click on the edit button under interarrival time distribution
Select Exponential distribution
Enter the generation rate of each part

Select the reference station for each class. In this case all the three parts originate from

the same source.

Modify the station name as M1
Select finite under the capacity and then enter the value of buffer level+1 (11) in max no. customers box

Click on edit under service time distribution
Select the deterministic distribution
Enter the process time value of the part with respect to the machine M1

Select probabilities as the routing strategy for part A in the routing section of the station
Enter the probability as 1 for M2 and 0 for M3

Select probabilities as the routing strategy for part B in the routing section of the station
Enter the probability as 0 for M2 and 1 for M3

Select probabilities as the routing strategy for part C in the routing section of the station
Enter the probability as 1 for M2 and 0 for M3

Modify the station name as M2
Select finite under the capacity and then enter the value of buffer level+1 (8) in max no. customers box

Click on edit under service time distribution
Select the deterministic distribution
Enter the process time value of the part with respect to the machine M2
Select Zero service time as strategy for Part B

Select probabilities as routing strategy for part A and random for part B and part C
Enter probability as 1 for M4

Modify the station name as M3
Select finite under the capacity and then enter the value of buffer level+1 (9) in max no. customers box

Select Zero service time as strategy for part A and part C and load independent for part B
Enter 2.1 in service time distribution tab

Modify the station name as M4
Select finite under the capacity and then enter the value of buffer level+1 (13) in max no. customers box

Click on edit under service time distribution
Select the deterministic distribution
Enter the process time value of the part with respect to the machine M4

Modify the station name as M5
Select finite under the capacity and then enter the value of buffer level+1 (10) in max no. customers box

Click on edit under service time distribution
Select the deterministic distribution
Enter the process time value of the part with respect to the machine M5

Click on Select an index option and select Throughput and Utilization
Add Utilization as index for all the machines
Add Throughput as index for all the classes with respect to the system

Enter 1000000 as the maximum number of samples for running the simulation

Simulation Results

Throughput of:

Part A= 0.3738
Part B= 0.1916
Part C= 0.3020

Utilization of:

M1=1
M2= 0.6957
M3= 0.4092
M4= 1
M5= 0.565