Module 4 - Capacity Planning & Queuing Analysis

Question 1

Which kind of forecasting methods are based on management intuition, sales force observations, a customer focus group, etc?
Note: They tend to be affected by biases, desires, and recent events and therefore are only useful for very innovative products or services

Answer 1

Judgmental forecasting

Question 2

Which kind of forecasting methods are based on when suppliers and producers work together to predict demand, including taking actions to coordinate product launches and promotions?

Answer 2

Collaborative forecasting

Question 3

A forecasting model is chosen based on its ability to accurately predict what?

Answer 3

the past

Question 4

The four most important characteristics of forecasts are:

Answer 4

1. The forecast will be wrong. (ie - it will rarely be exactly equal to actual demand)
2. A forecast is more accurate for larger groups
3. Forecast accuracy is inversely proportional to the time horizon (ie - more accurate in the short term than in the long term)
4. A forecast is useful only when a realistic range of uncertainty is provided

Question 5

What is the range of uncertainty?

Answer 5

The span of values within which the forecaster expects actual demand to fall (with a high degree of confidence)

Question 5

What is the the systematic component of the forecast?
What greek letter?
How is it calculated?

Answer 5

the forecast

denoted by the Greek letter mu, μ

It is, in effect, the mean value of the predicted demand

Question 6

What is the the random component of the forecast?
What greek letter?
What is it based on?
How is it calculated?

Answer 6

the margin of uncertainty.

denoted by the Greek letter sigma, σ

It is based on how well the forecasting model would have performed under conditions similar to those anticipated for future demand.

It is quantified as the standard deviation of the predicted demand

Question 7

Formula for coefficient of variation (CV)?
Why is it useful?

Answer 7

CV = (standard deviation/mean)*100
= (random component / systemic component) *100

It tells us how much variation there is relative to the predicted demand

Question 8

The intention of a forecaster is to provide two components associated with a future demand prediction. What are the two components?

Answer 8

systematic component and random component

Question 9

When demand cannot be predicted without significant uncertainty, responsiveness needs to be:
(a) fast
(b) doesn’t matter
?

Answer 9

a. fast

it should be a key element of the production system when there’s less certainty

Question 10

At a call center where calls for troubleshooting are categorized by reason, why would the CV for total calls per day tend to be less than the CV for calls for each reason?

Answer 10

Because the total calls would combine the uncertainty across each reason.

Question 11

What are the four terms are critical in a capacity analysis?

Answer 11

(1) Effective Capacity
(2) Unit Load
(3) Utilization
(4) a bottleneck

Question 12

Effective Capacity is:

Answer 12

the amount of work (flow rate or throughput) that a resource produces

Question 13

Unit Load is:

Answer 13

the time to process one flow unit
(the inverse of capacity)

Question 14

Utilization is:

Answer 14

the percentage of time a resource is working (calculated as the time spent processing divided by the capacity)

Question 15

A bottleneck is:

Answer 15

the slowest resource in a process with multiple resources – the process cannot output units faster than the bottleneck

it’s the resource with the highest utilization

Question 16

The size of a capacity buffer is based on:

Answer 16

1- the amount of demand uncertainty
2- the service time variation
3- the targeted performance of the resource

Question 17

Utilization formula

How much is a worker being utilized?

Answer 17

the ratio of demand to capacity
= demand / capacity

ie - a demand of 3 customers/hour divided by a capacity of 4 customers/hour = 75%

Question 18

What is a methodology for planning resource allocation that is based on the management of flow unit queues? It focuses on the deployment of resources so that queue waits are acceptable

Answer 18

waiting line management, or queue management

Question 19

Name 2 technical models for predicting performance

Answer 19

analytical queueing models and Monte Carlo simulations

Question 20

Markovian

Answer 20

In these cases, both the time for arrival times and service times follow an exponential probability distribution.

Question 21

In the standard coding system established for analytical queuing model categorization, the code is as follows: A/B/S/D/N/K.
What does each stand for?

Answer 21

A is the arrival time distribution
B is the service time distribution
S is the number of parallel servers
D is the queue discipline
N is the system capacity
K is the size of the population

Question 22

Exponential arrivals with rate λ (lambda) is expressed as:

Answer 22

arrivals per time interval

Question 23

Exponential service with rate μ (mu) is expressed as:

Answer 23

service completions per time interval

Question 24

P0 is the probability that the server is idle. What is this formula?

Answer 24

P0 = 1−(λ / μ)
λ = arrivals per time interval
μ = service completions per time interval

Question 25

Use the M/M/s model to determine the average wait time for customers to a motor vehicle driving test department, where customers arrive at a rate of 9.5 per hour and service times average 17 minutes per customer (exponentially distributed). Assume that 3 service providers are present.
Identify all the elements of the formula; this is done using excel sheet.

Answer 25

demand = 9.5cust/hr
service time = 17min/customer
capacity = 60min/hour divided by 17min/customer = 3.53cust/hour
utilization = demand/(capacity*n of servers)
= 9.5c/hr div by (3.53c/hr * 3servers)
=.871

The average waiting time would be 44.8 minutes.

Question 26

If a target server utilization threshold of 85% is used, would this be considered a 15% buffer for the service system?

Answer 26

Yes, because it is guarding against the effects of demand variation on system responsiveness.

Question 27

What is capacity?

If service time is 15 minutes, what is the capacity?

What does a person have the capacity to handle?

Answer 27

It is the rate that the items are made or customers are served.
It is the inverse of service time.

Example: if the average service time is 15 minutes
60min/hour divided by 15 min/customer
the capacity is 4 customers per hour

If there are 2 nurses both with a capacity of 4 customers/hour, then together they have a capacity of 2*4 = 8 customers/hour

Question 28

When we have a Poisson arrival process, the time between arrivals is represented with:

Answer 28

an exponential distribution

Question 29

What does M/M/s stand for?

Answer 29

M - arrival process is Markovian (the time between arrivals are exponentially distributed)
M - service time is Markovian (the time between arrivals are exponentially distributed)
s - number of servers in your system

Question 30

At a call center where calls for troubleshooting are categorized by reason, why would the CV for total calls per day tend to be less than the CV for calls for each reason?

Answer 30

Because the total calls would combine the uncertainty across each reason.

Question 31

What’s the recommended target effective capacity for:
1- reliable operating systems with little or not activity time variation
2- unreliable operating systems with highly variable activity times

Answer 31

1- 95%
2- 85%

Question 32

On a graph that shows resource utilization and target utilization, we want the resource to utilization to be __ than the target utilization for a feasible capacity plan

Answer 32

less than (or equal to)

Question 33

Monte Carlo simulations are: __ .
They are useful when the operating system: __

Answer 33

computer programs that mimic the operating system; it uses random number generators to mimic uncertainty within the simulation logic

is too complex for analytical modeling

Question 34

The effectiveness of a queuing system is generally measured according to two perspectives; both perspectives are important to a decision maker. They include:

Answer 34

1 - from the customer’s POV – waiting time in queue or time in system
2 - from the server’s perspective – predicting server utilization

Question 35

Service time variation is usually similar to the exponential distribution in that it tends to be skewed __.

Why would the variation in durations for a repair service be skewed ^ this way?

Answer 35

“right” (also known as a positive skew)

Because if the service is at all unusual or challenging, the repair time would typically be longer, rather than shorter, to the average repair time. That is, longer than average repair times would be more likely than shorter than average repair times.