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Chapter 10: Time Studies

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Chapter 10: Time Studies
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Chapter 10: Time Studies

IE 5511 Human Factors

Prof: Caroline Hayes

Time study topics

 What are they?

 What can you accomplish with them?

 What methods and equipment do you need?

 What do data sheets (for recording times)

look like?

 How many observations do you need?

 How do you calculate allowances and

standard times (ST)?

Time Studies

 Time studies are:

– Observations of work and the time it takes to

perform it.

– Method of determining a “fair” day’s work.

 Frederick Taylor popularized times studies

in the late 1800’s. Founder of the modern

time study.

 Work is divided into “elements” which are

timed.

Time Study Methods

 Time studies can be conducted with

simply, low-cost equipment:

– Stop watch (or other time recording devices:

time study board, computer, etc.)

– Video and/or audio tape,

– Time study forms, and other written notes,

 Time study often combined with motion

study (e.g. additionally looks at how

motions are made)

 Early studies analyzed physical work, but

many of the principles/methods apply

equally well to analysis of cognitive work

(e.g. using verbal protocol studies.)

Functions of Time Studies

 Establish work standards: e.g. recommended

times in which tasks should be completed by

qualified, trained operators, without excessive

fatigue,

 Set expectations which are fair to both

employee and company.

 Identify sources of error, difficulties, sub-

optimal aspects,

 Improve existing processes, tools, or work

environments,

Functions of Work Standards

 Establish reasonable productivity targets

for experienced workers,

 Provide productivity goals for training

purposes,

 Eliminate waste,

 Make processes more consistent,

 Reduce variability, improve quality.

Establishing Work Standards

 Need to use “work measurement procedures” (e.g.

time studies) to set accurate work standards.

 Data must be specific to a particular

– process,

– work environment,

– tool set and

– operator population

 Estimates that are not based on data may not be

sufficiently accurate for setting standards which have

a large impact on company and employees.

Preparing for a Time Study

 The steps in the process studied must already

be standardized; e.g. sequences have been

determined.

 Operator must be fully qualified, trained, and

acquainted with standardized process being

studied.

 Must inform supervisor, union steward,

department head.

 Make sure all materials are available for the

process.

Time Study Procedure

 Select operator(s)

 Break task down into elements (before you start

study)

 Observe operators performing task: record time taken

for each element, over several cycles.

 Assign appropriate allowances (e.g. allow time for

necessary but non-productive activities, such as rest,

cleaning eye-glasses, etc.

 Determine appropriate work standards.

Selecting an Operator

 Get supervisor to help in identifying appropriate

operators,

 Ideally, you want someone qualified, trained and

very familiar with process (may need to provide

training before study) if your goal is to set

standards.

 Prefer an average or slightly above average

operator.

 Sometimes you have no choice of operator – only

one person is available who does the job.

Divide Task into Elements

 Work Element: a group of motions that is relevant to the

experimenter’s study objectives.

(For cognitive work, divide verbal protocol into

“utterances” roughly equivalent to a single thought.)

 Watch for several cycles (before study starts) to identify

useful work elements for the task.

 Look for easily identifiable start and end signals, often

auditory or visual. Examples:

– The “clink” of a part being set on the fixture,

– Setting a cup on the counter in front of the customer,

– The moment when a customers hand touches the credit card as the

cashier hands it back.

Divide task into elements (cont)

This is not so easy to do!

 Preparatory observations: Devote a half hour or so to

observation of the task: start to identify relevant

operations, and practice recording them.

 Data sheets: Create a spread sheet or recording scheme to

help you record elements quickly and easily.

 Work element revisions: new elements may keep popping

up over several days! You may also find that two or more

elements should really be combined. Example: for

cashiers, cleaning and organizing, chatting with co-

workers are just different ways of “waiting” for customers.

 Level of abstraction. The size of the divisions between

elements depend on what you need to do in the analysis.

Record Significant Information

 Time Study Observation  Also useful to record:

form provides space for:

– Study date – Machines

– Observer Name – Jigs, fixtures

– Operator Name – Working conditions

– Department, – Sketch of work area

– Study Start Time layout

– Study End Time

Positioning Observer

 Stand slightly behind operator, usually

easier than sitting – easier to follow

movements of operator or get out of way).

 Try not to distract or interfere with operator.

 Avoid distracting conversation that may

upset routines.

Divide Task into Elements

 Smallest unit that can be accurately timed is

about 0.04 minutes (approx 2 to 3 sec).

 Breakpoints: use sound and sight both to

identify breakpoints between elements, (e.g.

sound of a part clinking in “finished” bin,

sound of a latch clicking shut, etc.)

Example

Caribou coffee study: Corporate Goals

 Stated goals: To streamline operations so that

employees will have more time to interact with the

customers.

 Additional benefits: customers will be happier if

they do not have to wait as long.

Example

Caribou coffee study: Analysts’ Goals

 To understand how long each activity took,

 To identify what “typical” processes were,

 To streamline processes, where possible,

 To set work performance standards, and customer

expectations,

– How long should customers expect to wait for a cup of

coffee?

– How should performance of stores be assessed?

– What performance goals should trainee’s aim for?

Identifying work elements

 It can take several hours or days of

observation to identify all work elements

and to come up with a consistent naming.

 New elements may keep appearing, over

time,

Two methods for recording

element times

 Snapback method: after recording the end of an

operations, “snapback” or reset the stopwatch to

zero.

– Advantages: don’t need to compute element duration,

don’t need to record delays or “foreign elements.”

– Disadvantages: may loose some time during

“snapback”

 Continuous method: Start timer at zero at start of

all observations, let it run continuously. Record

elapsed time at element breakpoints.

– Advantages: all time is recorded, operators and unions

like that, makes method easy to sell,

– Disadvantages: may take more computational effort

Data recording sheets

 You may need to devise data recording sheets that

fit the study goals, the task and the type of data.

 You may use the example data recording sheets in

the book, but they are not meant to fit all

situations,

 Examples:

– Recording a fixed sequence of operations.

– Recording a variable sequence of operations,

– Recording arrival and wait times in a line,

Recording a

fixed sequence

of operations

Repeated cycles of

the sequence





Foreign Elements

Examples of Data Recording Sheets:

for recording operations that happen in an unpredictable

order: custom assembly of one-off products



Time and Motion Study. Site 2: Regular Machine Page







Barista: employee observations Friday, mo/day/year



T 2.35 3.56 4.31 5:04 5:23 5:42



Op Wash Fill Steam Wait Pour C Check M



T 5:55 6:14 6:21 7:55



Op Pour M Finish Place Super.



T



Op

Examples of data recording sheets:

for sampling length of time customers wait in a line



Time and Motion Study. Site 3: Drive Thru page ________





Coffee Order Line: customer observations Date ____, 20__

Entry clock Short description "X" if car No# already

time (in min (color, type: turns in first Order Clock

and sedan, station away part of Time (in min

second) wagon, SUV, from line line. and

when car pick-up, etc.) or exits seconds)

enters line line when car

or turns prematur stops at

away ely order kiosk.

Other types of data

Chanhassen: Customer Arrival Rates

Ave. for 1/30/06 and 1/31/06, 6:30 - 10:30 AM

Number# Entering Cashier Line









50

38 39 39

40

32

27 28

30

23 20

20



10



0

9







9









9







9







9







9

9









30

:5







:2









:2







:5







:2







:5

:5









0:

-6







-7









-8







-8







-9







-9

-7









-1

30







00









00







30







00







30

30









10

6:







7:









8:







8:







9:







9:

7:









Tim e

How many cycles should be

observed?

There are several ways of estimating the

number of cycles that should be observed in

order to obtain accurate standard:

 The statistical method.

 The General Electric (G.E.) method,

The Statistical Method

Estimate numbers of observations required

 Goal: to limit the error in the estimate for the mean

operation time (OT) to plus or minus a given

percentage, k.

 Equation to estimate n, no# of observations needed:

2

n= t s

kx

 Problem: If you haven’t taken any observations yet, how can

you know x and s ?

 You can’t. Must estimate them first with a small pilot study.

The Statistical Method

Estimate numbers of observations required

 Goal: to limit the error in the estimate for the mean

operation time (OT) to plus or minus a given

percentage, k.

 Equation to estimate n, no# of observations needed:

2

n= t s

kx

 Problem: If you haven’t taken any observations yet, how can

you know x and s ?

 You can’t. Must estimate them first with a small pilot study.

The Statistical Method

Estimate numbers of observations required

 Goal: to limit the error in the estimate for the mean

operation time (OT) to plus or minus a given

percentage, k.

 Equation to estimate n, no# of observations needed:

2

n= t s

kx

 Problem: If you haven’t taken any observations yet, how can

you know x and s ?

 You can’t. Must estimate them first with a small pilot study.

The Statistical Method

Estimate numbers of observations required

 Procedure: it takes two steps to calculate sample size:

1. Pilot study: Take small set of observations or use historical

data to estimate the parameters:

 Mean OT: xp (mean operation time observed in the pilot study), use

xp as an estimate of x for the full scale study

 Sample standard deviation, s.

2. Full scale study. Use these parameters to calculate sample

size of a larger study.

Example

Estimation of number of Observations

1. Pilot study: you take n = 25 readings for an element. You get 25

readings, x1 through x25: 0.28, 0.24, 0.33, 0.33, etc.

When you summarize your data, you find:

 xp = Σ xi /25 = 0.30, where xp is the average time required

to perform the work element.

 s= Σ (xi – xp)2 = [(.28-.30) + (.24-.30) + …]2 = 0.09

√ n–1 √ 25 – 1

 Use s = 0.09 from the pilot study to estimate s for the

larger study.

Example

Estimation of number of Observations

1. Pilot study: you take n = 25 readings for an element. You get 25

readings, x1 through x25: 0.28, 0.24, 0.33, 0.33, etc.

When you summarize your data, you find:

 xp = Σ xi /25 = 0.30, where xp is the average time required

to perform the work element.

 s= Σ (xi – xp)2 = [(.28-.30) + (.24-.30) + …]2 = 0.09

√ n–1 √ 25 – 1

 Use s = 0.09 from the pilot study to estimate s for the

larger study.

Example

Estimation of number of Observations

1. Pilot study: you take n = 25 readings for an element. You get 25

readings, x1 through x25: 0.28, 0.24, 0.33, 0.33, etc.

When you summarize your data, you find:

 xp = Σ xi /25 = 0.30, where xp is the average time required



 s= Σ (xi – xp)2 = [(.28-.30) + (.24-.30) + …]2 = 0.09

√ n–1 √ 25 – 1

 Use s = 0.09 from the pilot study to estimate s for the

larger study.

Example

Estimation of number of Observations

1. Pilot study: you take n = 25 readings for an element. You get 25

readings, x1 through x25: 0.28, 0.24, 0.33, 0.33, etc.

When you summarize your data, you find:

 xp = Σ xi /25 = 0.30, where xp is the average time required



 s= Σ (xi – xp)2 = (.28-.30)2 + (.24-.30)2 + … = 0.09

√ n–1 √ 25 – 1

 Use s = 0.09 and xp from the pilot study to estimates to

“jump start” the calculation for the larger study.

Example (continued)

Estimation of number of Observations

1. Full scale study: how many observations of an element do you need to take in

a larger time study, in order be 95% confident that your measurement of x is

within k = 5% of the true value?

 k = 5% (acceptable error)

 α = 1 – confidence level = 1 - .95 = .05

 From pilot study we estimated: xp = Σ xi = 0.30, s =0.09

 Now you need to look up t. You can look up t if you know α and the

degrees of freedom (d.o.f):

d.o.f. = np - 1 = 25 – 1 = 24

2 2

n= t s = 2.064 x 0.09 = 153.3 observations



kx 0.05 x 0.30 (round up to integer)

Example (continued)

Estimation of number of Observations

1. Full scale study: how many observations of an element do you need to take in

a larger time study, in order be 95% confident that your measurement of x is

within k = 5% of the true value?

 k = 5% (acceptable error)

 α = 1 – confidence level = 1 - .95 = .05

 From pilot study we estimated: xp = Σ xi = 0.30, s =0.09

 Now you need to look up t. You can look up t if you know α and the

degrees of freedom (d.o.f):

d.o.f. = np - 1 = 25 – 1 = 24

2 2

n= t s = 2.064 x 0.09 = 153.3 observations



kx 0.05 x 0.30 (round up to integer)

Example (continued)

Estimation of number of Observations

1. Full scale study: how many observations of an element do you need to take in

a larger time study, in order be 95% confident that your measurement of x is

within k = 5% of the true value?

 k = 5% (acceptable error)

 α = 1 – confidence level = 1 - .95 = .05

 From pilot study we estimated: xp = Σ xi = 0.30, s =0.09

 Now you need to look up t. You can look up t if you know α and the

degrees of freedom (d.o.f):

d.o.f. = np - 1 = 25 – 1 = 24

2 2

n= t s = 2.064 x 0.09 = 153.3 observations



kx 0.05 x 0.30 (round up to integer)

The t-distribution (pg. 701)

Look up t-value in the table (or use the Excel function)



Alpha, α









Degrees of

freedom,

d.o.f.

The t-distribution (pg. 701)

Alpha, α









Degrees of

freedom,

d.o.f.





t = 2.064

d.o.f = 24

Example (continued)

Estimation of number of Observations

1. Full scale study: how many observations of an element do you need to take in

a larger time study, in order be 95% confident that your measurement of x is

within k = 5% of the true value?

 k = 5% (acceptable error)

 α = 1 – confidence level = 1 - .95 = .05

 From pilot study we estimated: xp = Σ xi = 0.30, s =0.09

 Now you need to look up t. You can look up t if you know α and the

degrees of freedom (d.o.f):

d.o.f. = np - 1 = 25 – 1 = 24. From table: t = 2.064

2 2

n= t s = 2.064 x 0.09 = 153.3 observations



kx 0.05 x 0.30 (round up to integer)

The General Electric (G.E.) Method

Assumes more error in smaller measurements – not much

attention to typical variability in the operation itself)

Using the data

from our in-class pilot study



 Task: collating & stapling 3 sheets of paper

 Operations:

1. Assemble sheets 1, 2, 3

2. Hand-off/Align/Staple

Can you the data from our in-class pilot study to estimate no#

observations needed to insure that we are:

– 95% confident (α = 0.05) that our answer is within:

– 10% error (k=.10)

Time Study Data Sheet

Process: Collating and Stapling

Day: Wed. November 17, 2010





Start time: 11:14 AM



Location: Room 108, Mechanical Engineering Bldg., Minneapolis, MN

cycle Operation 1 Operation 2

1 5 2

2 5 4

3 6 5

4 5 5

5 4 4





Average 5.0 4.0

StDev 0.7 1.2

Calculate n, sample size needed

for operation 1

xp = 5.0

s = 0.71

k = 0.10 (10% error); Let alpha = 0.05

n = t s 2 = ? *0.71 2

k xp .10 * 5.0



What value should we use for t?

Calculate n, sample size needed

for operation 1

xp = 5.0

s = 0.71

k = 0.10 (10% error); Let alpha = 0.05

n = t s 2 = 2.776 * 0.71 2 = 15.4 obs.

k xp 0.10 * 5.0



What if we decrease k to 5% ?

Calculate n, sample size needed

for operation 1

xp = 5.0

s = 0.71

k = 0.05 (5% error)

n = t s 2 = 2.776 * 0.71 2 = 62.7 obs.

k xp 0.05 * 5.0



The no# of observations greatly increases!

“Foreign” Elements

 A foreign element is one that does not explicitly

belong in the sequence

 Typically one subtracts them from observations

(when possible) to get a more “true” time.

 Examples:

– Worker has to adjust glasses,

– Must speak to supervisor,

– Rest break, lunch break,

– Equipment search: must find new wrench.

Foreign Elements

 Some foreign elements can be eliminated,

 But others cannot or should not be:

– Foreign elements can an idea of how much

extra time (e.g. allowances) is reasonable to

allow in an operation.

Allowances

 Allowances refers to extra time allowed,

beyond completion of the task itself

 Some allowances are necessary for health

and long term efficiency (like rest breaks),

 Others are pragmatically necessary, (like

time for picking up dropped tools or

consulting with supervisor)

Computing Standard Times

 A standard time is a combination of:

– The time it takes to complete a task

– Allowances.

 This approach recognizes that it is not

possible to work at top efficiency all day, all

the time.

Methods for computing

standard times

 Method 1: Add in allowances: compute required

rest.

ST = NT + NT x allowance

= NT (1 + allowance)

 Method 2: Compute allowances as a % of task time.

ST = NT / (1 – allowance)

ST = Standard Time: the time in which you expect workers to complete an operation

NT = Normal Time: time required to complete an operation for a given operator

OT = Mean Observed Time to complete an operation (from time study).

For an experienced operator who works at a 100% rate (R), OT = NT, and

NT = OT x R/100 where R = the performance rating of the operator.

Example: Method 1

 Suppose that your time study shows that it takes

3.5 minutes on average to complete a task. Rule

of thumb for manual tasks: 15% allowances.



ST = NT + (NT * allowance)

= 3.5 min + (3.5 min * .15)

= 3.5 min + 0.525 min

= 4.03 minutes.



Experienced operators will be expected to complete

the task in this time.

But how can you estimate

allowances?

 Observe foreign elements – what percentage

of total time do they comprise?

 Chapter 11 outlines many additional

methods for calculating allowances:

– For personal needs,

– For fatigue reduction

Next, identify possible sources

of fatigue

 Abnormal posture,

 Muscular force,

 Ventilation,

 Lighting,

 Visual strain

 Mental strain,

 Etc.

(see check list, Table 11 – 2).

Question:

 Does it make sense to estimate:

– Allowances

– Standard time

– Efficiency

for a cashier who may spend much time

waiting for customers to arrive?

How should Standard Times be used

to Evaluate and Motivate People?



 What happens when you set up a reward

system?

– All jobs have same standard time, but some are

more difficult,

– Busy-time often results in slower production

because you are exceeding capacity,

 Do you always get the behavior you expect?

Time Sheet

Date: Study start time:



Operation Start time End time Total time









Average:


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