Cycle Time Improvement

E211 – Operations Planning II

SSCHOOL OF CHOOL OF EENGINEERINGNGINEERING EE211 211 –– OOPERATIONS PERATIONS PPLANNING IILANNING II

� Recall the utilization versus waiting time:

� The higher the utilization of a process, the longer the queue in front of that process

� In Flexsim, the utilization statistics can be obtained by examining the ‘state’ result.

� However, it is not so straightforward if the arrival

Finding the Bottleneck


� However, it is not so straightforward if the arrival is batched. When there is no item to be processed, obviously there is no utilization! This is not due to bottlenecks occurring upstream.

When the current bottleneck operation is alleviated, other operations with higher utilization may become bottleneck again.

Study of Cycle Time Improvement

� Study each measure one at a time. For example, adding one more operator/forklift; adding one more packaging station, etc.

� Document the improvement in cycle time and cost of implementing the measure.

� If significant improvement is sought, may have


� If significant improvement is sought, may have to combine two or more measures.

� Basically a trial-and-error optimization process!

Simulation Techniques Learnt

Specify exact

arrival of items

using ‘Arrival

Schedule’ under

arrival style


Specify type of item for each arrival

Specify batch size for each arrival

To differentiate two types of items, set a


After items are generated from the source:


types of items, set a unique attribute for each type.

Notify VisualTool of the entry of each item into the processes.

When modeling with mobile resources (operators, transporters), pay attention to the speed, distance as



speed, distance as well as time units.

When using more than 1 operator (transporter) for one route, use a dispatcher or the ‘direct’ Technique(using the <A> key).



To route different

item types to

different objects,

specify a ‘send to

port’ rule under

flow tab of object.



Available/Collected Information from Running Simulation

Production Common Holding Area

Packaging (Running & Trekking)

Storage Rack

(Running)

Common Storage Bin

Storage Rack

(Trekking)

Conveyor

Conveyor

Operator

Forklift

Packaging (Running & Trekking)

ArrivalTime ItemName ItemType Quantity

0 Running shoes 2 30

900 Trekking shoes 1 40







Setup time at

packaging station

Triangular (5, 15, 10) seconds for both

types of shoes

Packaging for

Trekking shoes Normal ~ (60, 25) seconds

Packaging for

Running Shoes Normal ~ (45, 15) seconds

Trekking Shoes

Schedule

Batch of 40 products every 50 minutes, 6

batches daily

Running Shoes

Schedule

Batch of 30 products every 35 minutes,

10 batches daily

Forklift truck 8400 Running shoes 2 30









Current Process Flow

Packaging Station Utilization


Average Cycle Time (based on 10 replications): 1451.7 seconds (24 minutes 12 seconds)

Operator Utilization

Packaging Station has higher utilization rate, and is more likely to be the bottleneck

New Process Flow: Three Test Stations with One Operators





The Operator has now higher utilization, and is more likely to be the bottleneck.

New Process Flow: Three Test Stations with Two Operators




Packaging Station now has higher utilization, and is more likely to be the bottleneck


Statistical Comparison: 2-Sample t-test

� How can you statistically prove that the proposed alternative can improve cycle time by at least 700 seconds?

� Use 2-Sample t-test under the following assumptions:

� Collected data are independent of one another;

� Each of the two samples (current and improved) is drawn from normally distributed population;

Cycle Time (Seconds)

Current3 QC stations + 1

operator

1412.78 675.73

1541.9 694.68

1424.99 681.22

1280.21 661.21


distributed population;

� The two populations have unequal variance

� Statistical hypotheses

� Null hypothesis (H0): The difference in cycle time between current and improved method is less and equal to 700 seconds;

� Alternative hypothesis (H1): The difference in cycle time between current and improved method is greater than 700 seconds.

1280.21 661.21

1592.13 700.21

1475.32 680.04

1501.98 689.56

1456.35 668

1376.8 679.67

1454.24 682.75


Excel>Data>Data Analysis>t-Test: Two-Sample Assuming Unequal Variances.


Level of significanceThe improvement on cycle time (between current and proposed alternative) you want to statistically prove


� Compare t-statistic with critical value: t-statistic > critical value.

� Or compare p-value

t-Test: Two-Sample Assuming Unequal Variances

Variable 1 Variable 2

Mean 1451.67 681.307

Variance 7579.743711 135.8573344

Observations 10 10

Hypothesized


� Or compare p-value with significance level: p-value < 0.05.

� Conclusion: Reject H0 and conclude that the proposed alternative can improve cycle time by at least 700 seconds.

Hypothesized

Mean Difference 700

df 9

t Stat 2.533141595

P(T<=t) one-tail 0.016034819

t Critical one-tail 1.833112923

P(T<=t) two-tail 0.032069637

t Critical two-tail 2.262157158

Conclusion

� Packaging station is the bottleneck of the current packaging and stock-in process.

Configuration Average Cycle Time (based on 10

replications)

Current 1451.7 seconds (24 minutes 12 seconds)

3 packaging stations with 1 operator 681.3 seconds (11 minutes 21 seconds)

3 packaging stations with 2 operators 610.7 seconds (10 minutes 11 seconds)


process.

� However the bottleneck operation also may have higher percentage of idle time. This is because arrivals are batched; sometimes resources may be idle in between the arrival batches.

� By improving the bottleneck operation (add in one more packaging station and/or operator), average cycle time can be improved.

� By statistical comparison, such as 2-Sample t-test, we can conclude whether the proposed alternative can effectively improve the cycle time.

Learning Objectives

� Modeling and simulation of a typical production line using a simulation software.

� Identify bottleneck operations in the process flow through simulation modeling and analysis.

� Recommend how to alleviate bottleneck operations (improve cycle time); and how to simulate proposed alternatives using Flexsim.


alternatives using Flexsim.

� Use statistical test to conclude whether the proposed alternative can effectively alleviate the bottleneck (improve the cycle time).

Documents

Cycle Time Improvement