WORK MEASURMENT

Work Measurement is a term which covers several different ways of

finding out how long a job or part of a job should take to complete. It can

be defined as the systematic determination, through the use of various

techniques, of the amount of effective physical and mental work in terms

of work units in a specified task. The work units usually are given in

standard minutes or standard hours.

Why should we need to know how long a job should take? The answer to

this question lies in the importance of time in our everyday life. We need

to know how long it should take to walk to the train station in the

morning, one needs to schedule the day's work and even when to take

out the dinner from the oven.

In the business world these standard times are needed for:

1.) planning the work of a workforce,

2.) manning jobs, to decide how many workers it would need to

complete certain jobs,

3.) scheduling the tasks allocated to people

4.) costing the work for estimating contract prices and costing the

labour content in general

5.) calculating the efficiency or productivity of workers - and from this:

6.) providing fair returns on possible incentive bonus payment

schemes.

On what are these standard times set? They are set, not on how long a

certain individual would take to complete a task but on how long a

trained, experienced worker would take to do the task at a defined level

of pace or performance.

Who sets these standard times? Specially trained and qualified observers

set these times, using the most appropriate methods or techniques for

the purpose i.e. "horses for courses".

How it is done depends on circumstances that obtain. The toolkit

available to the comprehensively trained observer is described below.

Selecting the most appropriate methods of work

measurement

The method chosen for each individual situation to be measured depends

on several factors which include:

a.)the length on the job to be measured in time units

b.)the precision which is appropriate for the type of work in terms of time

units (i.e. should it be in minutes, hundredths or thousandths of a

minute)

c.) the general cycle-time of the work, i.e. does it take seconds, minutes

or days to complete

The length of time necessary for the completion of the range of jobs can

vary from a few seconds in highly repetitive factory work to several weeks

or months for large projects such as major shutdown maintenance work

on an oil refinery. It is quite clear that using a stop-watch, for example,

on the latter work would take several man-years to time to measure!

Thus, more "overall" large-scale methods of timing must be employed.

The precision is an important factor, too. This can vary from setting times

of the order of "to the nearest thousandth of a minute" (e.g. short cycle

factory work) to the other end of the scale of "to the nearest week" (e.g.

for large project work).

These are the dominant factors that affect the choice of method of

measurement.

The ways of work measurement

PMTS.

At the "precision" end of the scale is a group of methods known as

predetermined motion time systems that use measurement units in ten

thousandths (0.0001) of a minute or hundred-thousandths of an hour

(0.00001 hour).

The resulting standard times can be used directly, for very short-cycle

work of around one minute total duration such as small assembly work.

However, they often are used to generate regularly used basic tasks such

using assembling or disassembling nuts and bolts, using a screwdriver

and similar. Tasks of this type are filed as standard or synthetic data-

banks.

Estimating.

At the other end of the scale (long-cycle and project work) we need

something which is quick to use. Such a method is estimating. This can

exist in three main forms.

a.)Analytical estimating relies on the experience and judgement of the

estimator. It is just of case of weighing up the work content and, using

this experience, stating a probable time for completion, such as "this job

will take about eight days to complete".

b.)Category estimating. This is a form of range estimating and requires

a knowledge of the work. Estimators may not feel comfortable with

overall, analytical estimates upon which may depend the outlay of a great

deal of money. They often prefer giving a range estimate such as "this job

should take between 12 weeks and 14 weeks to complete", which

provides a safety net should things go wrong. Such ranges are not just

picked upon at random but are statistically calculated and based on

probability theory.

c.)Comparative estimating. This is another example of range

estimating. Again, estimators rely on experience of the work in order to

produce estimates. This experience can be augmented by the provision of

each time-range with a few typical, descriptive, jobs that would guide

estimators to the most appropriate range. The estimator would compare

the work to be estimated with those in the various ranges until the most

appropriate fit is found.

Timing.

The intermediate method between the two groups above, is timing the

work in some way, usually with a stop-watch or computerised electronic

study board. This method is retrospective in that the job must be seen

in action in order to be timed whereas the other methods are

prospective and can be used for timing jobs before they start.

The observer times each element of the work and obtains times that the

observed operator takes to do the elements. Each timing is adjusted

(rated) by the pace at which the operator was working as assessed by the

observer. This produces basic times for the elements and hence the whole

job, which are independent of the operator and can be used as the time

for a trained, experienced worker to carry out the same elements.

Another method of assessing the work is using activity sampling and

rated activity sampling. This is a method based on the observer making

snap observations at random or systematic sample times, observing what

the operator is (or operators are) doing at the times of those observations

Models:

A most useful method for standard or synthetic data-banks of job or

element times is using computer models of the jobs. These are generated

as mathematical formulae in which the observed data are inserted to

compile a time for completion of the task or project. It is a useful method

for recycling time standards for elements of basic work over and over

again, only changing the values of the variables to suit each project

ACTIVITY SAMPLING

What is it ?

Activity Sampling is a statistical technique that can be used as

a means for collecting data. It is defined by BS 3138:41008 as:

A technique in which a large number of observations are made

over a period of time of one group of machines, processes or

workers. Each observation records what is happening at that

instant and the percentage of observations recorded for a

particular activity or delay is a measure of the percentage of

time during which that activity or delay occurs.

It is normally used for collecting information on the

percentages of time spent on activities, without the need to

devote the time that would otherwise be required for any

continuous observation.

One of the great advantages of this technique is that it enables

lengthy activities or groups of activities to be studied

economically and in a way that produces statistically accurate

data.

Fixed and Random Interval Sampling

Activity Sampling can be carried out at random intervals or

fixed intervals. Random activity sampling is where the intervals

between observations are selected at random e.g. from a table

of random numbers. Fixed interval activity sampling is where

the same interval exists between observations. A decision will

need to be made on which of these two approaches is to be

chosen. A fixed interval is usually chosen where activities are

performed by a person or group of people who have a degree

of control over what they do and when they do it. Random

intervals will normally be used where there are a series of

automated tasks or activities as part of a process, that are

have to be performed in a pre established regular pattern. If

fixed interval sampling were to be used in this situation there is

a danger that the sampling point would continue to occur at

the same point in the activity cycle.

Confidence Levels

Remember, that activity sampling is used for assessing the

percentage of time spent on activities.

Because activity sampling conforms to the binomial distribution

it is possible to use a calculation to determine how many

observations will be needed to operate within specified limits of

accuracy.

The formula for the number of observations is as follows:

= 4 x p x (100 - p)

L2

Where p is the estimated % time spent on the activity

Where L is the limit of error, expressed as a %

Once the above calculation has been completed the

observations can begin and activities are recorded at the

agreed time intervals. When they have been completed a

further calculation can be used to determine the error rate, as

follows:

Error Rate = ± 2 x √( p x (100 - p) )

Number of observations

This is very much an overview to the topic of activity sampling,

with a definition of what it is, its advantage over continuous

observation and the formulae that can be used to establish the

confidence levels that can be obtained.

DATA COLLECTION

What is/are data?

One definition of data is: "known facts or things used as a basis

for inference or reckoning":- The OED.

Another is: "facts given from which others may be inferred": -

Chambers Dictionary.

The term "data" more commonly is another word for "statistics"

or numerical facts. The UK Prime minister, Disraeli, is quoted

as saying, "There are lies, damned lies and statistics". Indeed,

statistical data can be presented to mean what you wish them

to mean. ("Data" is a plural word, the singular being datum.

However, through American influence it is acceptable to use

"data" in the singular form rather than "data are".

Forms of data

Data can be separated into three categories of data

(variables):

a.)discrete variables, which are numerical and can only be

particular numbers, such as the number of workers in an

organization (i.e. they are counted in single units)

b.)continuous variables, which are dimensions of items in

units of measurement such as metres, litres, volts and other

units of length, volume, time.

c.)attribute variables, which are descriptive e.g. a machine

"on" or "off", or an employee absent or present.

The main phases in the collection of data using sampling

methods are:

1. The purpose or objective for collecting the data,

2. identification of the entire "population" from which the data

are to be collected (e.g. a sampling frame).

3. decisions on:

o method of collection, or how the data are to be collected

o sample size (i.e. how many readings to collect), and

4. validation of the results, this being a vital part of the

collection/analysis process.

Sampling

One important thing to bear in mind is that something in the

system must be random. This could be the situation which is

random or a sampling method which contains a random

element for picking the components of the sample. Some of

these follow.

The choice of sampling method depends on the type of data

being sampled.

Random sampling:

A common method is simple random sampling or the lottery

method. One of the most convenient ways is to allocate

numbers to all components of the population to be sampled

and obtain the required amount of numbers to constitute the

sample size. The ways of obtaining a random sample of

numbers range from drawing numbers blindly "from a hat", (or

the mechanized version of agitated balls being ejected from a

drum), to the use of computer generated numbers.

Systematic sampling.

Often known as the constant skip method, this form of

sampling is based on taking every nth reading from the random

population. For example, in a survey, taking every 9th house in

a street, for example, numbers 3, 12, 21, 30, 39 and so on).

Care must be taken to avoid bias, so in the UK, taking every

10th house means they would all be on the same side of the

road, and this might be significant.

Stratified sampling.

In order to ensure that all groups in a population are properly

represented, this method separates the population into strata

and allocates proportional representation to each stratum. With

people, the strata may be occupations, or social classes, ages,

or income groups for example. Once selected, one of the other

two methods may be used within the strata.

Other methods.

These include quota sampling, cluster sampling and multi-stage

sampling.

Validation

It is of little use if the sample collected does not represent the

whole population. Clearly no sample can exactly reflect the true

result had the whole population been surveyed. Therefore,

probably there the sample result will differ from the true

situation. What is important is that we are aware of the

probable statistical errors which inevitably arise because the

whole population was not investigated. Provided that the

population is relatively large, the magnitude of the statistical

error depends not on the size of the population but on the size

of the sample. The error can be calculated (dealt with

elsewhere in this Managers-net Web-site) or alternatively, the

sample size can be calculated prior to data collection if we

decide on the size of the error which we can tolerate. If the

subsequent error is too large, then a bigger sample size must

be taken, i.e. a further set of observations to add to the

existing ones. At least, we can be aware of the statistical error

to which our results are subject due to sampling and use the

data appropriately.

STATISTICAL PROCESSING CONTROL

The fundamentals of Statistical Process Control (though that

was not what it was called at the time) and the associated tool

of the Control Chart were developed by Dr Walter A Shewhart

in the mid-1920’s. His reasoning and approach were practical,

sensible and positive. In order to be so, he deliberately avoided

overdoing mathematical detail. In later years, significant

mathematical attributes were assigned to Shewharts thinking

with the result that this work became better known than the

pioneering application that Shewhart had worked up.

The crucial difference between Shewhart’s work and the

inappropriately-perceived purpose of SPC that emerged, that

typically involved mathematical distortion and tampering, is

that his developments were in context, and with the purpose,

of process improvement, as opposed to mere process

monitoring. I.e. they could be described as helping to get the

process into that “satisfactory state” which one might then be

content to monitor. Note, however, that a true adherent to

Deming’s principles would probably never reach that situation,

following instead the philosophy and aim of continuous

improvement.

Explanation and Illustration:

What do “in control” and “out of control” mean?

Suppose that we are recording, regularly over time, some

measurements from a process. The measurements might be

lengths of steel rods after a cutting operation, or the lengths of

time to service some machine, or your weight as measured on

the bathroom scales each morning, or the percentage of

defective (or non-conforming) items in batches from a supplier,

or measurements of Intelligence Quotient, or times between

sending out invoices and receiving the payment etc., etc..

A series of line graphs or histograms can be drawn to represent

the data as a statistical distribution. It is a picture of the

behaviour of the variation in the measurement that is being

recorded. If a process is deemed as “stable” then the concept

is that it is in statistical control. The point is that, if an outside

influence impacts upon the process, (e.g., a machine setting is

altered or you go on a diet etc.) then, in effect, the data are of

course no longer all coming from the same source. It therefore

follows that no single distribution could possibly serve to

represent them. If the distribution changes unpredictably over

time, then the process is said to be out of control. As a

scientist, Shewhart knew that there is always variation in

anything that can be measured. The variation may be large, or

it may be imperceptibly small, or it may be between these two

extremes; but it is always there.

Wheeler and Chambers combine and summarise these two

important aspects as follows:

"While every process displays variation, some processes

display controlled variation, while others display

uncontrolled variation."

Why is "in control" and "out of control" important?

Shewhart gave us a technical tool to help identify the two types

of variation: the control chart .

What is important is the understanding of why correct

identification of the two types of variation is so vital. There are

at least three prime reasons.

First, when there are irregular large deviations in output

because of unexplained special causes, it is impossible to

evaluate the effects of changes in design, training, purchasing

policy etc. which might be made to the system by

management. The capability of a process is unknown, whilst

the process is out of statistical control.

Second, when special causes have been eliminated, so that

only common causes remain, improvement then has to depend

upon management action. For such variation is due to the way

that the processes and systems have been designed and built –

and only management has authority and responsibility to work

on systems and processes. As Myron Tribus, Director of the

American Quality and Productivity Institute, has often said:

“The people work in a system.

The job of the manager is

o To work on the system

o To improve it, continuously,

With their help.”

Finally, something of great importance, but which has to be

unknown to managers who do not have this understanding of

variation, is that by (in effect) misinterpreting either type of

cause as the other, and acting accordingly, they not only fail to

improve matters – they literally make things worse. These

implications, and consequently the whole concept of the

statistical control of processes, had a profound and lasting

impact on Dr Deming. Many aspects of his management

philosophy emanate from considerations based on just these

notions.

So why SPC?

The plain fact is that when a process is within statistical

control, its output is indiscernible from random variation: the

kind of variation which one gets from tossing coins, throwing

dice, or shuffling cards. Whether or not the process is in

control, the numbers will go up, the numbers will go down;

indeed, occasionally we shall get a number that is the highest

or the lowest for some time. Of course we shall: how could it

be otherwise? The question is - do these individual occurrences

mean anything important? When the process is out of control,

the answer will sometimes be yes. When the process is in

control, the answer is no.

So the main response to the question Why SPC? is therefore

this: It guides us to the type of action that is appropriate for

trying to improve the functioning of a process. Should we react

to individual results from the process (which is only sensible, if

such a result is signalled by a control chart as being due to a

special cause) or should we instead be going for change to the

process itself, guided by cumulated evidence from its output

(which is only sensible if the process is in control)?

Process improvement needs to be carried out in three

chronological phases:

Phase 1: Stabilisation of the process by the identification

and elimination of special causes:

Phase 2: Active improvement efforts on the process itself,

i.e. tackling common causes;

Phase 3: Monitoring the process to ensure the

improvements are maintained, and incorporating

additional improvements as the opportunity arises.

Control charts have an important part to play in each of these

three Phases. Points beyond control limits (plus other agreed

signals) indicate when special causes should be searched for.

The control chart is therefore the prime diagnostic tool in Phase

1. All sorts of statistical tools can aid Phase 2, including Pareto

Analysis, Ishikawa Diagrams, flow-charts of various kinds,

etc., and recalculated control limits will indicate what kind of

success (particularly in terms of reduced variation) has been

achieved. The control chart will also, as always, show when any

further special causes should be attended to. Advocates of the

British/European approach will consider themselves familiar

with the use of the control chart in Phase 3. However, it is

strongly recommended that they consider the use of a

Japanese Control Chart (q.v.) in order to see how much more

can be done even in this Phase than is normal practice in this

part of the world.

STATICAL SAMPLING FOR DATA COLLECTION

When it is possible to collect all the data for a population, the

results (for example the parameters like average (mean) or

dispersion of the data values) will accurately represent the

situation. However, because the sampling frame from which

the sample is taken usually will be large, it is impossible to

measure all the data, so a sample must be obtained.

Unfortunately, because we cannot measure all of the data the

sample parameters when calculated probably will not

accurately represent the whole data field. This gives rise to

what are known as statistical, or sampling, errors.

Two important points about sampling are that the sample must

be (a) representative of the situation and

(b) usually random,

in order to avoiding the effects of bias. Random sampling is

the most usual methods of obtaining representative sampling.

Methods of sampling

1. Random sampling

As already mentioned above, when taking a sample something

within the sampling frame must be random in order to avoid

the effects of bias. Either the situation must be random or the

sampling must be on a random basis.

One of the most common, but not the simplest, is random

sampling as used in lotteries. Random samples may be taken

by several methods including thoroughly mixing up the items in

the sampling field and then picking the number of items in the

sample size at random e.g. without selecting). Another method

is to number each item in the population of values and then

use randomly generated numbers to obtain the random

sample. Many are already numbered such as serial numbers on

equipment, passports or National Insurance numbers. Random

numbers may be found in textbooks, statistical tables or as

computer programs.

The following example is not necessarily how it is done in

practice but is one method of sampling to illustrate the method

in general terms.

Suppose an electricity supply organisation needs to assess the

degree of corrosion of its main power lines in various areas of

the country in order to find those areas which are prone to the

worst corrosion and hence might need more attention than

other areas. It is an impossibly time-consuming task to inspect

every power line between every tower in every area and,

indeed, not necessary. Sampling can provide a sufficiently

"accurate" or reliable answer with a known degree of error.

Meanwhile, using a map of the grid system the researcher

could divide the territory into areas and the areas into smaller

locations. Each power line could be divided into smaller lengths

(possibly "between each tower") and each smaller length

would be identified in some way (e.g. numbering or coding).

In order to decide which of the thousands of lengths of cable

are to be examined, first of all the sample size (i.e. how many

lengths to be inspected) must be determined. It is the sample

size that eventually determines the degree of error in the

result, when this is applied to the whole network including

those thousands of lengths which were not checked. Basically,

the larger the sample size the smaller is the statistical error.

These statistical errors are not to be confused with human

error nor with measuring equipment error.

When the sample size has been calculated (as dealt with in a

later Topic) The next stage is to identify which of the lengths

are to be inspected.

For this purpose it is necessary to generate random numbers

either from tables available in many books on statistical

method or from computer spreadsheets (e.g. Lotus 1-2-3, or

EXCEL). When the required number of random numbers has

been obtained these are used to identify the corresponding

numbers on the grid map as the ones to be inspected.

Figure 1 illustrates a very simplified, abridged example of

this method in diagrammatic form showing only 30 lengths of

cable. These are numbered 1 to 30.

A sample size of eight is used in this instance. Random

numbers, taken from a random number table, are

18,28,5,13,16,9,26 and 21. These are indicated in red on the

"map" below. These numbered cables would be used as the

sample:

Cable

numbers

1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3

1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0

Methods of sampling

2.Systematic sampling

Systematic sampling (or constant skip method) is not random.

Nevertheless, it can be used where the situation is random.

For example, suppose the objective of a large organization is to

obtain a random selection from the 800 employees to sit as

representatives on a management productivity group. Each has

an employee staff identification number issued randomly by

Personnel Department. To collect a sample of 20 names,

management could take, for example every 40th name from the

staff register (i.e. 800 divided by 20 equals 40, hence every

40th name).

Methods of sampling 3. - stratified sampling

This method is useful where the sampling frame has natural

strata or divisions. For example, to ensure that all

occupations in a company are equally represented the

occupations could be the strata and within each stratum,

random or systematic samples could be taken. So, using the

example quoted for systematic sampling, if the employees

consisted of 64 managers, 200 supervisors and 536 engineers

(=800 employees) to obtain a representative proportion from

each employee grade (or stratum), the proportions would be:

for managers, 64 out of 800 total employees = 8%, 200 out of

800 = 25% and 536 out of 800 = 67%.

Therefore, 8% of the random numbers would be from

management names, 25% from supervisors' names and the

rest, 67%, from the engineers' names. This ensures a

representative proportion from each group.

Mystery shoppers

The "mystery shoppers" method of sampling is used in market

research to determine the quality of goods and services. With

this method employees or specially engaged agencies acting as

"customers" make notes on the service they receive in the

environment being inspected.

This method can be used for testing the "ambience" of areas

(e.g. "how pleasant" is the area). For example, some rail

services use the method for inspecting their rolling stock and

stations for litter, vandalism, malicious damage, graffiti and the

general appearance of the environment and "feel" of their

assets.

ANALYTICAL SAMPLING

What is it ?

Analytical estimating is a structured work measurement

technique. The formal BSI definition (22022) states that it is a

development of estimating, in which the time required to

perform each constituent part of a task at a defined rate of

working is estimated from knowledge and practical experience

of the work and/or from synthetic data

An important feature of this technique, which helps to improve

accuracy, is that a whole job should be broken down into

smaller individual tasks. This is because any errors in the time

estimates may be seen as random and will therefore

compensate for each other.

How can it be used ?

Analytical estimating would normally be used for assessing

work over a reasonably lengthy period of time, where it may be

difficult and more expensive to collect the information required

using other measurement techniques. Also, in some work

environments the presence of an individual carrying out work

measurement in the work place could be unacceptable. In

these cases, analytical estimating may be an appropriate

method to use, assuming someone with experience of the work

is available to apply their experienced judgement. ( This may

be work measurement personnel who have previous experience

of this particular work )

However, the work content of some jobs cannot be estimated

in advance because one is unclear about what is required until

an assembly operation has been tested or stripped down. For

example, during the progress of repair unforeseen and non

standard difficulties can arise. Removing a wooden door from

its frame by unscrewing 8 or 12 screws could take five minutes

if the screws were recently inserted, or a great deal longer if

the screws are rusted and clogged with paint.

In summary, the technique is used most commonly in any work

environment where a lengthy time (and associated high cost) is

needed to collect data.

Advantages & Disadvantages

Perhaps the most significant advantage of using anaytical

estimating is its speed of application and low cost. Using

trained and experienced personnel process and measurement

data can be quickly assembled and applied.

However, the use of experienced judgement when determining

the time necessary to perform a task is the technique's most

obvious source of weakness when compared with a more

precise technique such as time study. This is why the

technique would not normally be used when a more precise

and accurate alternative is a feasible and economic alternative,

particularly to highly repetitive, standardised operations.

Many jobs, such as craft work in the maintenance field, consist

of a group of tasks which are periodically repeated but the

precise nature of each task varies each time in minor respects (

see research on Natural & Normal Variation for further

explanation). In this example, since it is impractical, in terms

of time and cost, to allocate one time study observer

permanently to each craftsman, the alternative is to use a

time-study basis plus the experienced judgement of an ex-craft

work-study observer to allow for detailed task variations.

BUSINESS PLANNING

Business (Corporate) Planning is the process of deciding what

tactical action and direction to take, in all areas of business

activity, in order to secure a financial and market position

commensurate with the strategic objectives of the organisation.

To put it another way, it is the comprehensive planning for the

whole of the business and involves defining the overall

objectives for the organisation, and all the actions that must be

adopted in order that those objectives are achieved.

Illustration:

If only we spent as much time doing our jobs, as we waste in

these budget meetings, we would be a lot better off. This

planning stuff is all very well, but has anyone ever worked out

how much it costs? Anyway, all we can ever do is write down

what we think will happen, then wait until it hasn’t happened,

and finally argue about why it didn’t. Sometimes I wonder if it

is all worthwhile.

Statements like these occur because:

No one has taken the trouble to explain the purpose and

benefits of planning;

The planning methods are wrong;

Plans are imposed from above, rather than worked out

and agreed with the people who are going to have to

carry them out;

So-called planning is often no more than totalling up the

various departments’ forecasts, and calling them the

company plan.

In general it can be assumed that FIVE important features of

Corporate Planning prevail, they are:

1. Objectives and objective setting;

2. Flexibility - the ability to be adaptable within the plan;

3. Growth - anticipating opportunities for new markets;

4. Synergy - the sum of joint efforts being greater than

either one;

5. Time span - the critical length of the plan - long termism

is increasingly risk managed in today’s business

environment.

CORPORATE PLANNING

A planning technique that aims to integrate all the planning

activities of an organisation and relate them to the best overall

objectives for the organisation.

Explanation:

A large number of planning techniques has been extensively

used in business and commerce for a considerable time.

Budgetary control (q.v.) which involves a large amount of

budgetary planning has been one of the most wide ranging and

successful, via its materials, labour, sales, overheads, R&D,

capital and cash budgets. A further development of this is the

technique of profit planning (q.v.), which considers a number

of alternative strategies on capital investment, expansion,

diversification for example, before setting a single preferred

plan. Corporate planning represents a further widening and, at

the same time, a closer integration of earlier techniques. As

examples of the widening process, corporate planning would

normally include management development and training,

environmental and community plans in addition to operating

plans. As an example of closer integration, the technique would

involve all managers and departments in setting objectives and

determining the means to achieve them, in relation to the

overall company plan.

Illustration:

The technique has found most favour with larger companies of

mature standing, i.e. those whose days of headlong growth are

over, who are subject to strong international competition and

who wish to think out extremely carefully their future

investment projects and at the same time to harmonise and

integrate the policies, procedures and plans created in each

country, division and operating unit of the company.

Predetermined motion time system (PMTS)

Definition:

PMT Systems are methods of setting basic times for doing basic

human activities necessary for carrying out a job or task.

'Tables of time data at defined rates of working for classified

human movements and mental activities. Times for an

operation or task are derived using precise conventions.

Predetermined motion time data have also been developed for

common combinations of basic human movements and mental

activities'.

Background

The principle of analyzing work into into basic actions was first

published by F. Gilbreth in 1920, as his Therbligs. The first

commercial and internationally recognized system was devised

in the 1930's to circumvent the banning by the government of

the United States time study and the stop-watch as the means

of measuring work performed on US government contracts. It

was devised by Quick, Malcolm and Duncan under the title

Work-Factor and appeared in 1938. Other methods followed,

the main one, some ten years later, being Methods-Time

Measurement (MTM). Both systems share basic similarities but

are based on different standards of time.

Outline description of PMTS

The concept of PMTS is to analyse a job into its fundamental

human activities, apply basic times for these from tables and

synthesize them into a basic time for the complete job. The

basic elements include the following:

reach for an object or a location,

grasp an object , touching it or closing the fingers around

it,

move an object a specified distance to a specified place,

regrasp an object in order to locate it in a particular way,

usually prior to:

release an object to relinquish control on it,

other elements for assembling to, or inserting an object into,

its intended location.

For each of these actions basic times are tabled. For example,

in Work-Factor the time unit is one thousandth of a minute

(the Work-Factor Time Unit) whereas in MTM the unit is one

hundred-thousandth of an hour (time measurement unit, tmu).

The times for basic actions are adjusted for other factors which

take into account such variables as:

distances moved, in inches or centimetres

difficulty in performing the actions, such as avoiding

obstacles during moves, closeness of fit during

assembling, weight of the object, all of which increase the

times to carry out the basic actions.

The above basic motions cover most of the actions performed

by humans when carrying out work. Other basic activities

include:

walking to a specified place

bending down and stooping

kneeling on one knee and kneeling on both knees

foot and leg motions

sitting down and standing.

Mental activities include times for: See, Inspect, Identify,

Nerve Conduct, React, Eye focus, Eye travel times, Memorize,

Recall, Compute (calculate) and others, mostly from Work-

Factor.

Levels of detail in systems

In order to speed up measurement time the major systems all

include different levels of detail, such as:

1. most detailed systems: MTM and Detailed Work-Factor

2. Second level systems: MTM-2 and Ready Work-Factor

(abridged versions) achieved usually by the four methods

of combining, statistically averaging, substituting and/or

eliminating certain basic motions.

3. Third level systems: MTM-3 and Abbreviated Work-Factor

(even more abridged)

4. "higher level" systems, usually times for complete

activities.

One example of simplifying in the second level system MTM-2

is the combining of MTM elements reach, grasp and release to

produce a new MTM-2 element of "Get".

PMTS is often used to generate synthetic data or (standard

data banks) which are overall basic times for more complex

tasks such as maintenance or overhauling of equipment. This is

achieved by synthesizing the hundreds of small jobs measured

using PMTS into a time for the complete project.

Basic times produced by PMTS need to have relaxation

allowances and other necessary allowances added to produce

standard times.

An example of part of a typical analysis in MTM-2 is

An extract from an MTM analysis showing the first seven

elements.

MTM Analysis

Job description:

Analyst: E J H

Assemble r.f.

transformer to base-

plate Date: 3 May

El. Description LH tmu's RH Description

1 Move hand to washer R14C 15.6 R14B Move hand to

transformer

2 Grasp first washer G4B 9.1 G1A Grasp

transformer

3 Move hand clear of

container M2B --- --- Hold in box

4 Palm washer G2 5.6 --- Ditto

5 To second washer R2C 5.9 --- Ditto

6 Grasp washer G4B 9.1 --- Ditto

7 Move washers to area M10B 16.9 M14C Transformer to

plate

Notes on descriptions of some of the codes as examples.

The codes in the LH and RH columns refer to those in the MTM

time tables. For example: R14C is translated as "Reach 14 in.

to an object jumbled with other objects in a group, so that

search and select occur" (Class C reach). R14B is translated as

"Reach 14 in. to a single object in location which may vary

slightly from cycle to cycle." G2 is a grasp Case 2 which is a

Regrasp to move the washer into the palm G4B is a Grasp Case

4B which is for grasping *object jumbled with other objects so

search and select occur. Objects within the range 0.25 x 0.25 x

0.125 in. to 1 x 1 x 1 inch."

One tmu is one hundred-thousandth of an hour.

Time study

What is it?

Time study is a tried and tested method of work measurement

for setting basic times and hence standard times for carrying

out specified work. Its roots are back to the period between the

two World Wars.

The aim of time study is to establish a time for a qualified

worker to perform specified work under stated conditions and

at a defined rate of working.

This is achieved by a qualified practitioner observing the work,

recording what is done and then timing (using a time

measuring device) and simultaneously rating (assessing) the

pace of working.

The requirements for taking a time study are quite strict.

Conditions:

the practitioner (observer) must be fully qualified to carry

out Time Study,

the person performing the task must be fully trained and

experienced in the work,

the work must be clearly defined and the method of doing

the work must be effective

the working conditions must be clearly defined

There are two main essentials for establishing a basic time for

specified work i.e. rating and timing.

Some terminology explained

Timing

The observer records the actual time taken to do the element

or operation. This usually is in centiminutes (0.01 min.) and is

recorded, using a stop-watch or computerized study board.

Rating.

When someone is doing work his/her way of working will vary

throughout the working period and will be different from others

doing the same work. This is due to differing speeds of

movement, effort, dexterity and consistency. Thus, the time

taken for one person to do the work may not be the same as

that for others and may or may not be 'reasonable' anyway.

The purpose of rating is to adjust the actual time to a

standardized basic time that is appropriate and at a defined

level of performance. Rating is on a scale with 100 as its

standard rating.

Elements

A complete job usually will be too long and variable to time and

rate in one go, so it would be analysed into several smaller

parts (elements) which, separately, will each be timed and

rated.

Basic time

This is the standardised time for carrying out an element of

work at standard rating.

Example: An observer times an element as 30 centiminutes

(cm) and because it is performed more slowly than the

standard 100, he rates it as 95. Thus the basic time is 95%

of 30 or 28.5 basic cm. The formula is: (actual time x

rating)/100.

Allowances

Extra time is allowed for various conditions which obtain, the

main ones being relaxation allowance for:

a. recovery from the effort of carrying out specified work

under specified conditions (fatigue allowance)

b. attention to personal needs

c. adverse environmental conditions,

d. others concerned with machine operations

Frequency

The basic time is the time for a complete cycle to be performed

but as not all elements are repeated in every cycle their times

per average cycle must be pro rata. In the example which

follows, element 2 only occurs once every eight cycles so its

basic time is one eighth of the element time, per cycle. Similar

treatment for element 7 (one twelfth).

Standard time:

Basic time + allowances

RATING

Definition

Rating is a term used in work measurement to assess the

speed and effort put into a job of work by the worker. The

British Standard Institute definition of the verb “to rate” is:

To assess the worker‟s rate of working relative to the

observer‟s concept of the rate corresponding to standard

rating. The observer may take into account, separately

or in combination, one or more factors necessary to the

carrying out of the task, e.g. speed of movement, effort,

dexterity, consistency.

The concept

In order to determine the time necessary to carry out a task or

job it is not sufficient just to assess this by timing with a

chronometer a worker carrying out the task or even estimating

it. The worker might be working slowly or “extra quickly”.

These are vague terms but neither would be satisfactory for

the purposes of obtaining some sort of “standard time” for the

job. What is needed is a time the “average”, trained, qualified

worker would take to do the job.

This concept of the “average rate” at which the qualified worker

would work is a very subjective one - it is a matter of opinion.

In essence, we do not want a time for doing a job quickly or

slowly. We need a standard time for the job and not a time for

any individual worker.

The solution is to assess the time actually taken by a qualified

worker who knows the job and is properly trained to do it and

then adjust this actual time to what it would have been had

that worker been working at the standard rate. Thus, rating

eliminates the need to search for that mythical standard worker

and takes out of the equation the need for that worker to

adjust his/her pace to the standard rate of working, something

which is difficult to do.

So, to quote the BSI standard 3138 “Glossary of Terms used in

Management Services” Term number 22074, standard rating is

defined as

The average rate at which qualified workers will work, provided

they adhere to the specified method, and are motivated, suited

and accustomed to the task.

How is it done?

So, clearly, rating is highly subjective. To aid raters to conform

with the universally accepted concept of rating there are sets of

films/videos/CDs which demonstrate various jobs with their

rates and have tests for training purposes.

Capable observers must be trained in the art of rating, first

recognizing the standard rating and then, through practising,

assessing against this standard other levels of rates of working.

Rating scales have been developed. One of the original ones is

Charles Bedaux’s, known as the “60/80 scale”. Bedaux

considered that workers paid on a fixed daywork system

without any financial incentive would normally do 60 minutes

worth of work in an hour whereas one on a financial bonus

scheme would get the work done on average one third faster,

doing 80 minutes work in an hour (incentive rate). The rest of

this “60/80 scale” was pro-rata. So, for example, a worker

working twice as fast as this perceived “normal” 60 rating

would be assessed as working at 120 rating.

This Bedaux scale was later converted to decimal form

accepted by British Standard Institute which allocated a rating

of 75 BS in place of Bedaux 60 and 100 BS rating replacing

Bedaux’s 80 rating. The complete BS scale supercedes the

corresponding Bedaux scale pro rata.

Incentives:- financial reward system

Introduction

The concept of schemes for incentive payments is a very

controversial one. The first thing to make clear is that financial

incentives and motivation are diametrically opposed to each

other. Frederick Herzberg in particular would, in his time, be

aghast at the mention of the two concepts in the same breath.

But this is the subject of another Topic (see below).

In the Topic “Scientific Management” you will read about the

pioneers of this approach the management. The way to get

more work out of people was to give them some incentive

which could range from the negative “stick” method to the

positive “carrot” incentive. The “stick” drives people to work

more quickly because the must, while the “carrot” attracts

them to speed up to earn rewards. In a nutshell, better output

is achieved because people are made to work better while

psychological motivation produces better output because

people want to achieve. Both methods are largely effective and

successful but for different reasons.

In order for financial incentive schemes to be effective they

must be based on targets. Targets, usually, are in terms of

output in numerical form reling on the jobs being work

measured.

A typical scheme

A typical scheme is the piecework method in which workers are

paid “per unit produced”. The format of the system is chosen

(described later). A standard time per unit is set on the job

using a suitable choice of work measurement. The output is

linked to the (usually) variable wages. The proposal is put to

the workforce and unions if relevant for their discussion and

agreement.

There is a minimum safeguard for the worker, or basic pay

rate, usually set at a 50 BS performance. Workers are never

paid less than this amount. Above the 50 BS a bonus

proportional to the actual performance is paid. 100 BS level is

known as the “incentive” performance and 75 BS,is “normal”

performance

A basic scheme is as described above with basic wage is paid

up to an actual performance of 50 BS. Above this a bonus is

paid in direct proportion to the actual performance on a one-

for-one basic. In all cases the pay performance scale is geared

to actual currency of the country, pro rata.

There are many different forms of financial incentives. One of

the most basic schemes is the “50 + a half” which is similar to

the above but pay performance bonus is at a rate of only half

of the actual performance. The Figure below illustrates the 50

+ 1/2 scheme. For example, if the worker produces 90 actual

performance, he/she is paid the wage equivalent to a 70

performance i.e. half of the bonus part going to the worker

and half to the company.

Other variants include the Taylor differential piece-rate

scheme, which is similar to the above but has a step or “jump”

in the payment as an extra inducement to increase output.

Another group uses curved schemes, such as the Rowan

“hyperbolic” payment scheme and the Barth Variable Sharing

scheme.

An example of a „fixed‟ bonus scheme

In the 1960’s the Philips organization, tired of the

administration involved in payment-by-results, devised a

method of individual fixed bonuses in its Premium Payment

Plan (PPP). Basically, workers contracted with the company to

work at a certain rate on average for an equivalent fixed

bonus. Workers who defaulted on the contract were warned

that in order to maintain their individual bonuses they must

improve. Employees could work their way up to higher levels of

bonus through contracting to work at correspondingly higher

output levels as they became more experienced.