The primary purpose for estimating an improvement curve is to predict the cost of future

production. The prediction is based on the assumption (not always true) that the past is a good

predictor of the future. In terms of the unit improvement curve theory, this assumption means

that the unit cost (hours or dollars) of doubled quantities will continue to decrease by the same

constant percentage.

Using a graph, you can predict future costs by drawing a line-of-best-fit through the historical

data graphed on log-log paper and extending it through the unit for which you wish to make a

cost estimate. Estimate cost using the Y value (cost) at the point were the two lines intersect.

For example, suppose we had the following unit cost data:

Unit Number Hours

1 3,000

2 2,400

4 1,920

8 1,536

Plotting the data on log-log paper, you will observe a straight line with an 80 percent slope.

If you extend the line-of-best-fit to Unit #100, you can estimate the cost of Unit #100. As you

can see from the graph, the extended line reveals an estimated cost of approximately 680 hours

for Unit #100.

7.3 Analyzing Improvement Using Lot Data and Unit Theory

Accounting System Data

Use of the improvement curve is dependent on available cost data. The relevant accounting or

statistical record system must be designed to make relevant data available for analysis. Costs,

such as labor-hours per unit or dollars per unit, must be identified with the unit of product.

NOTE: It is preferable to use labor-hours rather than dollars since the dollars contain an

additional variable, the effect of inflation or deflation, which the labor-hours do not contain

.

Typically accounting systems do not record the cost of individual units. If the firm uses a joborder cost accounting, costs are accumulated on the job order in which the number of units

completed are specified and costs are cut-off at the completion of the units. Process cost

accounting also yields costs identified with end-item units. In this case, however, the costs are

usually assigned to equivalent units produced over a period of time rather than actual units.

Average Unit Cost

To use unit improvement curve theory, you must be able to estimate the cost of a particular unit.

Given lot or period costs, the only unit cost that we know is the average cost for the lot or period.

However, we have a method for using average costs in improvement curve analysis.

For example, given the following data, we must be able to estimate the cost of an additional 40

units.

Lot Number Lot Size

(Units)

Lot Total

Labor-Hours

(Cost)

Lot Average

Labor Hours

(Cost)

1 6 40,800 6,800

2 9 40,500 4,500

3 15 52,500 3,500

Calculating a Lot Plot Point for Graphic Analysis

To graph the lot average unit cost, we must select a corresponding unit number. If we assume

that costs go down during the lot, the average cost should occur at the middle of the lot – the lot

mid-point. One problem is that the True Lot Mid-Point (the unit where the average cost is

incurred) depends on the slope of the improvement curve. Unfortunately, the slope of the curve

also depends on the placement of the Lot Mid-Point. The iterative process required to calculate

the True Lot Mid-Point for each lot is too cumbersome for manual computation. As a result, we

use the following rules of thumb for graphic analysis:

â¢ For All Lots After The First Lot, calculate the lot mid-point by dividing the number

of units in the lot by two . Then add the resulting number to all the units produced prior

to the lot to determine where the unit falls in the continuing improvement curve.

For example, what would be the plot point for a lot made up of units 91 through 100. There are

10 units in the lot, so the middle of the lot would be 5 (10 2 = 5). Adding 5 to the 90 units

produced prior to the lot, we find that the plot point would be 95.

â¢ For a First Lot of Less Than 10, follow the same procedure that you follow for all lots

after the first lot. Of course, the lot plot point will equal the lot mid-point because no

units will have been produced prior to the first lot.

â¢ For a First Lot of 10 or More, calculate the lot mid-point by dividing the number of

units in the lot by three . This adjustment is necessary to compensate for the rapid

decline in cost that takes place in the first lot of production.

Given the data above, use a table similar to the following, to calculate the necessary lot plot

points and lot average hours:

Lot No. Lot Size Cumulative

Units

Lot MidPoint

Lot Plot Point

1 6 6 3.0 3.0

2 9 15 4.5 10.5

3 15 30 7.5 22.5

You can then use this information to estimate the cost of lots that have

not yet been produced. For example, suppose you wanted to estimate the

cost of a Lot #4 of 40 units to be produced after the 40 units described

above. The final row of the table would be:

4 40 70 20 50

For this example, the lot plot point for Lot #4 would be at Unit #50. You

would estimate the average unit cost for the lot using the cost of Unit

# 50.

Combining Lot Plot Point and Average Unit Cost Calculation

You can combine the calculation for the lot average unit cost and the lot plot point into a single

table, as shown below:

Lot

No.

Lot

Size

Cumulative

Units

Lot MidPoint

Lot

Plot

Point

Lot

Average

Hours

Lot

Total

Hours

1 6 6 3.0 3.0 6,800 40,800

2 9 15 4.5 10.5 4,500 40,500

3 15 30 7.5 22.5 3,500 52,500

4 40 70 20.0 50.0

Plotting Data on a Log-Log Graph

Plot the average lot cost data (Y) at the corresponding lot plot point (X) on log-log paper and for

an improvement curve. Extend the improvement curve through Unit #50, the lot plot point for

Lot #4.

On the Y axis, the lot average cost at Unit #50 is approximately 2,700 labor hours. With this

information, you can estimate the cost of Lot #4 at 108,000 labor hours (i.e., 2,700 labor hours x

40 units).

7.4 Fitting a Unit Curve

General Points to Consider

Throughout this chapter, we have assumed that all data fit a perfectly straight line.

Unfortunately, most data do not fall exactly on a straight line. You need to be able to identify a

trend and fit data to that trend. You can visually fit a line using graphic analysis, but most linesof-best-fit are developed using regression analysis.

Whatever method of analysis you use to fit an improvement curve, if a data point is a significant

distance away from the trend set by other data points, look into the cause of the deviation. If your

analysis indicates that the data point is not comparable with the rest of the data for some reason,

consider adjusting or eliminating the data point from your analysis. However, never eliminate a

data point from your analysis simply because it does not fit the apparent trend set by the

remaining data.

Graphic Analysis

When visually fitting a straight line, graph the data then draw the line to minimize the distance

between the straight line and the data points. Normally, you should give more weight to the

larger lots as you fit the straight line.

When fitting a straight line on ordinary graph paper, you know that the line-of-best-fit must go

through the average of the X values ( ) and the average of the Y values ( ). When fitting a line-ofbest-fit through improvement curve data on log-log paper, you have no similar fixed reference

point. Without this fixed reference point, even skilled analysts can arrive at very different

lines.

Regression Analysis

Normally, you can obtain more accurate results using regression analysis and a log-log

transformation. Using the logarithmic values of X and Y instead of the actual values, the

equation of the unit improvement curve (Y = AXB) becomes:

Log Y = Log A + B(Log X)

The new equation describes a straight line (Y = A + BX) relationship. After this transformation,

you can use regression analysis to fit a straight line to the data.

Improvement curve regression analysis programs differ in several ways including:

â¢ Use of True Lot Mid-Point.

In addition to the accuracy gained from using regression analysis, most improvement curve

programs use the true lot mid-point rather than the rule-of-thumb calculations described earlier in

this section for graphic analysis. The greatest effect of using the true lot mid-point is in the first

lot. Examples of the differences between the rule-of-thumb and true lot mid-points are depicted

in the following table:

Selected First Lot Mid-Points

True-Lot Mid-Points

Units in

First Lot

Rule-ofThumb

70%

Curve

80%

Curve

90%

Curve

2 1.00 1.37 1.39 1.4

10 3.33 3.95 4.17 4.36

100 33.33 28.65 32.36 35.43

1,000 333.33 258.15 304.43 340.67

10,000 3333.33 2,495.48 3,002.85 3,384.18

Differences in calculating the lot mid-point will affect the results of the improvement curve

analysis by the placement of the data points for analysis.

â¢ Method of Regression.

Not all improvement curve analysis programs use the same mathematical model for regression

analysis. For example, some analysis programs assign a weight to each lot based on the lot size,

while others do not. Software using unweighted regression considers all lots (large and small)

equally. When weights are assigned to each lot based on lot size, larger lots receive more

analysis consideration than smaller lots.

â¢ Measures of Fit.

o Regardless of the regression model used to develop the line-of-best-fit, virtually

all regression analysis software will provide measures of the line’s goodness of fit.

o The primary goodness of fit measure is the coefficient of determination (r 2 ) for

the equation. As described in the chapter on “Using Regression Analysis,” the

coefficient of determination indicates the portion of variation in Y is explained by

the regression line (e.g., an r 2 of .94 indicates that 94 percent of the variation in Y

is explained by the relationship between X and Y).

o Many improvement curve analysis programs also provide the T-test for

significance of the regression equation.

â¢ Graphic Analysis Capability.

Many regression analysis programs provide a capability to graph the data and the regression line.

For most analysts, this display is one of the strongest tools for identifying anomalies in the data

that affect the value of the regression analysis as an estimating tool.

7.5 Estimating Using Unit Improvement Curve Tables

Estimating Choices

Once the cost of Unit #1, in hours or dollars, and the slope of the improvement curve have been

established, we can develop estimates of future costs in several ways. You could graph the data

on log-log paper and read your estimates from the graph. You could substitute the values into the

improvement curve equation. Many analysts use a third choice, improvement curve tables.

Improvement Curve Tables

Improvement curve tables are an expansion of the X B portion of the basic unit improvement

curve equation, Y = A X B . The result is recorded as a decimal fraction, which is typically

calculated to six or eight decimal places. There is a different table value for each unit and slope.

Below is an illustration of a partial improvement curve table.

Partial Improvement Curve Table

79 Percent 80 Percent 81 Percent

Unit Cum Total Unit Cum Total Unit Cum Total Unit

1 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000

2 1.790000 0.790000 1.800000 0.800000 1.810000 0.810000

3 2.478245 0.688245 2.502104 0.702104 2.526065 0.716065

4 3.102345 0.624100 3.142104 0.640000 3.182165 0.656100

5 3.680837 0.578492 3.737741 0.595637 3.795233 0.613068

6 4.224550 0.543713 4.299424 0.561683 4.375245 0.580012

7 4.740494 0.515944 4.833914 0.534490 4.928703 0.553458

8 5.233533 0.493039 5.345914 0.512000 5.460144 0.531441

9 5.707214 0.473681 5.838864 0.492950 5.972892 0.512748

10 6.164223 0.457009 6.315374 0.476510 6.469477 0.496585

11 6.606656 0.442433 6.777485 0.462111 6.951880 0.482403

12 7.036189 0.429533 7.226831 0.449346 7.421690 0.469810

13 7.454188 0.417999 7.664747 0.437916 7.880206 0.458516

14 7.861784 0.407596 8.092339 0.427592 8.328507 0.448301

15 8.259928 0.398144 8.510538 0.418199 8.767503 0.438996

16 8.649429 0.389501 8.920138 0.409600 9.197970 0.430467

17 9.030982 0.381553 9.321821 0.401683 9.620576 0.422606

18 9.405190 0.374208 9.716181 0.394360 10.035902 0.415326

19 9.772580 0.367390 10.103736 0.387555 10.444457 0.408555

20 10.133617 0.361037 10.484944 0.381208 10.846691 0.402234

21 10.488713 0.355096 10.860211 0.375267 11.243003 0.396312

22 10.838235 0.349522 11.229900 0.369689 11.633750 0.390747

23 11.182513 0.344278 11.594336 0.364436 12.019252 0.385502

24 11.521844 0.339331 11.953813 0.359477 12.399798 0.380546

25 11.856497 0.334653 12.308597 0.354784 12.775651 0.375853

26 12.186716 0.330219 12.658929 0.350332 13.147049 0.371398

27 12.512724 0.326008 13.005031 0.346102 13.514210 0.367161

28 12.834725 0.322001 13.347104 0.342073 13.877334 0.363124

29 13.152906 0.318181 13.685335 0.338231 14.236605 0.359271

30 13.467440 0.314534 14.019894 0.334559 14.592192 0.355587

Unit Estimate.

To estimate the price or cost for a specific unit, you can simply multiply the cost of Unit #1 by

the appropriate unit factor for the desired unit and slope.

Where:

Y U = T 1 x F U

Y U = Unit cost estimate

T 1 = Theoretical cost of Unit #1

F U = Unit cost factor for the unit.

For example, if Unit #1 is 2,000 labor hours, what would be your estimate for Unit #20 if

production is expected to follow an 80 percent improvement curve? The table value for Unit #20

and an 80 percent slope is .381208. The estimate would be 762.4 labor hours, calculated as

follows:

Y U = T 1 x F U

= 2,000 labor hours x .381208

= 762.4 hours

We need to do the same thing for Lot Data:

Y L = (T 1 x F C2 ) – (T 1 x F C1 )

Where:

Y L = Lot cost estimate

T 1 = Theoretical cost of Unit #1

F C2 = Cumulative cost factor for all production through the proposed lot

F C1 = Cumulative cost factor for all production prior to the proposed lot

For ease of calculation, this equation may be rewritten as:

Y L = T 1 (F C2 – F C1 )

For example, if Unit #1 is 4,000 labor hours and the improvement curve slope is 80 percent, what

would be your estimate for Units #15 to #25? Your estimate should be 15,192.24 labor hours,

calculated as follows:

YL = T1(FC2 – FC1)

= 4,000 (12.308597 – 8.092339)

= 4,000 (4.216258)

= 16,865.032 (rounded to 16,865 labor hours)

7.6 Identifying Issues and Concerns

Questions to Consider in Analysis

As you perform price or cost analysis, consider the issues and concerns identified in this section,

whenever you use an improvement curve.

â¢ Is improvement curve analysis used when the contract effort involves:

â¢ A significant amount of manual labor in the contract?

â¢ Uninterrupted production?

â¢ Production of complex items?

â¢ No major technological change?

â¢ Or should involve, continuous pressure to improve?

â¢ Does the documentation to support the use of the improvement curve include:

o A statement describing the improvement curve theory used in developing the

estimate?

o A summary of related cost data for the product being purchased and any similar

products?

o A description of how available data were used in estimating the theoretical cost of

Unit #1 and the slope of the curve?

o A statement on how the improvement curve estimate was used in price or cost

analysis?

Like CERs, improvement curves are a form of comparison estimate. Unless you are satisfied that

the historical data provide a valid base for the use of an improvement curve, estimates based on

the curve should be suspect.

â¢ Was improvement curve theory properly applied to the available data?

Verify the application of the improvement curve to the data available. Remember that different

improvement curve models will produce different results.

For instance, you may find that a unit curve will provide more reasonable results than a

cumulative average curve provided by an offeror. Examine the results of both curves when an

offeror proposes using a cumulative average curve, because cumulative average curves often

conceal significant fluctuations in per unit labor hours.

â¢ Did any improvement curve analysis isolate costs associated with contract changes

and production interruptions?

Changes and production interruptions will both have a disruptive effect on improvement. If their

effects are not identified and considered in analysis, improvement curve estimates will typically

underestimate actual requirements. Random fluctuations around an improvement curve line-ofbest-fit should be expected. However, if costs increase or decrease dramatically, you should

suspect that the actual costs have been affected by a contract change or a break in production.

When you suspect that actual costs are affected by a contract change or break in production,

contact the cognizant auditor and Government technical personnel for assistance in your

analysis.

On the other hand, an offeror might overstate the impact of an interruption in productioncontending that the interruption has been so long that it will have to start from scratch. However,

impovements in unit costs result in part from such factors as better product design, tooling, work

methods, and work layout. If these were properly documented, some of the improvement should

carry over to the new effort-regardless of the length of the interruption or turnover of personnel.

â¢ Does the improvement curve analysis project continued improvement?

Occasionally, an offeror will propose “negative learning.” In other words, as more units are

produced, the cost per unit increases. Do not accept the negative learning argument. If something

has significantly changed, consider starting a new curve with a new first unit value and slope.

â¢ Does the improvement curve estimate include the costs of rework and repair?

The effort for rework and repair may or may not be included in the costs projected with the

improvement curve. Therefore, you need to determine if these costs are included in the projected

costs before allowing any add-on factors for rework or repair.

â¢ 8.0 – Chapter Introduction

â¢ 8.1 – Identifying Situations For Use

â¢ 8.2 – Identifying Elements Of A Labor Standard

â¢ 8.3 – Measuring And Projecting Operation Efficiency

â¢ 8.4 – Identifying Issues And Concerns

8.0 – Chapter Introduction

In this chapter, you will learn about work measurement concepts and their application to cost

analysis.

Work Measurement . Work Measurement involves the use of labor standards to measure and

control the time required to perform a particular task or group of tasks. Most often labor

standards are developed and applied in manufacturing operations; however labor standards can

be used in estimating and managing the cost of a vast variety of activities including engineering

drafting, clerical administration, and janitorial services.

Work Measurement System . A Work Measurement System is a management system designed to:

â¢ Analyze the touch labor content of an operation;

â¢ Establish labor standards for that operation;

â¢ Measure and analyze variances from those standards; and

â¢ Continuously improve both the operation and the labor standards used in that operation.

Work Measurement System Plan . A Work Measurement System Plan is the firm’s program for

implementing, operating, and maintaining work measurement in its operations. As a minimum,

the plan should provide guidance on:

â¢ Establishing and maintaining standard accuracy;

â¢ Conducting engineering analyses to improve operations;

â¢ Revising standards and related system data; and

â¢ Using labor standards as an input to budgeting, estimating, production planning, and

performance evaluation.

Labor Standard Types . A labor standard is a measure of the time it should take for a qualified

worker to perform a particular operation. Labor standards are commonly grouped into two types:

â¢ Engineered standards are developed using recognized principles of industrial

engineering and work measurement. The standards developed define the time necessary

for a qualified worker, working at a pace ordinarily used, under capable supervision, and

experiencing normal fatigue and delays, to do a defined amount of work of specified

quality when following the prescribed method. As a result, you can use engineered

standards to examine contractor estimated labor hours and to identify any projected

contractor variances from that estimate.

â¢ Non-engineered standards are developed using the best information available without

performing the detailed analysis required to develop engineered standards. Historical

costs are commonly used standards that typically measure the hours that have been

required to complete a task rather than the hours that should be required.

Estimate of Efficient Operation Cost . Standards provide information on what it should cost to

complete an operation or series of operations in product production. Instead of applying pressure

to improve in all areas, managers can use this information to identify areas requiring particular

management emphasis. The Acquisition Team can use that same information to identify

inefficient operations for close scrutiny during contract negotiations.

â¢ The log-log graph below presents a line-of-best-fit developed using actual labor-hour

history. Note that this line follows the form of the improvement curve. Without labor

standards, the firm and the Government would likely project the improvement curve to

estimate the labor hours required to produce future units.

â¢ Labor standards provide additional information that can be used in estimate development

and analysis. The vertical distance between the labor-hour history and the labor standard

represents the variance from the standard. Some of that variance may be related to

inefficiencies that cannot be resolved. However, all elements should be targeted for

identification and analysis. Key elements include:

o Technical factors (e.g., manufacturing coordination, engineering design changes,

fit problems, design errors, operation sheet errors, tooling errors, work sequence

errors, and engineering liaison problems).

o Logistics (e.g., incorrect hardware and parts shortages).

o Miscellaneous factors (e.g., unusual working conditions, excessive overtime, and

excessive fatigue).

o Worker learning (e.g., familiarity with processes and methods).

â¢ Variance analysis should identify, categorize, and develop plans to control all variances

from standard. Plans will typically concentrate on the operations with the largest

variances from standard, because these operations present the greatest opportunity for

cost reduction.

Updating Standards . Standards cannot be set and forgotten. Process improvement is one of the

central elements of an effective Work Measurement System. As methods improve, the associated

labor standards must be updated.

Standards changes will affect the estimating value of all the data based on those standards. For

example, some variance analyses may remain valid while other analyses will be rendered

meaningless as a result of the change. The system must assure that valid analyses are retained for

continued utilization. At the same time, the system must also assure that meaningless data are not

misused.

8.1 – Identifying Situations For Use

General Situations . Contractors should consider the use of labor standards whenever contractor

employees will be performing the same tasks repetitively over an extended period of time. Labor

standard development requires extensive detailed effort. The time and cost required for standards

development are prohibitive unless the task will be performed repetitively. On the other hand,

when an operation will be performed repetitively, the cost visibility provided by labor standards

permits detailed cost evaluation and control that can result in significant savings to the

Government. To be of real value, labor standards must be considered in making key management

decisions (e.g., budgeting, estimating, production planning, and performance evaluation).

8.2 Identifying Elements Of A Labor Standard

Key Elements . As a contracting officer, it is likely that you will never be required to develop a

labor standard. However, you may be called upon to negotiate a contract price based, in part, on

labor standards. Therefore, you should know the elements of a standard and how they are

developed.

The figure below depicts some of the factors that should be considered in each element.

Leveled Time . Leveled time is the time that a worker of average skill, making an average effort,

under average conditions, would take to complete the required task. There are a variety of

techniques used in leveled time development, but the four used most commonly are:

â¢ Time Study. In performing a time study, industrial engineers (or other labor analysts)

time the effort required to perform a defined task. While it may sound simple, this is a

complex process that requires special training and experience. To perform a time study,

the analyst must:

o Clearly define and document the work design, including the best design of the

work place, tools, tasks, and subtasks.

o Select a person to be timed. The person selected should be receptive to being

timed, experienced in the work methods being used, and familiar with the tasks

and subtasks of the work design.

o Observe and record the time that the selected worker requires to perform each of

the subtasks in the work design. Several observations are required to average out

random variations and assure that all elements of the work have been considered.

The number of observations required will increase as the confidence level desired

by the analyst increases and as the variability between observed times increases.

o Assign a pace rating based on an evaluation of how the ability and effort of the

worker being timed compares with those of an average worker. Using the pace

ratings, the analyst converts observed times into a leveled time for the subtask.

o Total subtask times to develop a leveled time for the entire task.

â¢ Predetermined Leveled Times. Instead of using time study to develop a leveled time,

the analyst can use predetermined leveled times (also called predetermined standards or

basic motion standard data). Predetermined leveled times are established for basic body

motions, such as reach, move, turn, grasp, position, release, disengage, and apply

pressure. The analyst may obtain them from published standards in tabular or electronic

forms, or the firm may develop its own. To use predetermined leveled times, the analyst

must:

o Clearly define and document the work design, including the best design of the

work place, tools, tasks, and subtasks.

o Select and document the source of the predetermined leveled times.

o Identify and document the basic body motions involved in performing each

subtask. Motions for each hand must be specifically identified. The need for

precise measurement of complex body motions for each job element may make

this method of leveled time development inappropriate for complex tasks with

long performance cycle times.

o Assign times to the body motions required to complete each subtask and total

assigned times to develop a leveled time for the subtask. Documentation should

demonstrate that the accuracy of the original data base has not been compromised

in application or standard development.

o Total subtask times to develop a leveled time for the entire task.

â¢ Standard Time Data. Standard time data (or elemental standard data) are developed for

groups of motions that are commonly performed together, such as drilling a hole or

painting a square foot of surface area. Standard time data can be developed using time

studies or predetermined leveled times. After development, the analyst can use the

standard time data instead of developing an estimate for the group of motions each time

they occur.

o Typically, the use of standard time data improves accuracy because the standard

deviations for groups of motions tend to be smaller than those for individual basic

motions. In addition, their use speeds standard development by reducing the

number of calculations required.

o Estimate development using standard time data is much like using predetermined

leveled times except that groups of motions are estimated as a single element

instead of individual body motions.

â¢ Work Sampling. Work sampling is commonly used to develop non-engineered

standards. It cannot be used alone to develop engineered standards. However, it can be

used to supplement or check standard development by more the definitive techniques

described above. For example, it can be used to determine job content and assess

productive vs. nonproductive time.

o In work sampling, analysis is based on a large number of random, rather than

continuous observations. Estimates are based the proportion of time spent by one

or more persons on a given activity. This is useful for jobs with irregular

components that vary in the amount of time per unit of output.

o To use work sampling in standard development, the analyst must:

ï§ Identify and define activities involved in the work (through discussions

with the workers and preliminary observations).

ï§ Develop the method(s) for observing and recording activities.

ï§ Determine the sampling strategy (e.g., stratified) and number of

observations (by time and place).

ï§ Record observed activities during each period.

ï§ Consolidate and analyze the data.

ï§ Use the data collected to develop nonengineered standards or to

supplement development of engineered standards.

PF&D Allowance . After the leveled time is developed, estimators must consider a personal,

fatigue, and delay (PF&D) allowance. Be careful when contractors use predetermined time

systems. Some predetermined time systems include a partial or complete allowance for PF&D. If

the contractor uses such standards, additional PF&D consideration may not be appropriate.

Contractor work measurement policies and procedures should provide the detailed rationale used

for applying PF&D allowances. Each allowance should be identified and quantified. Total PF&D

allowances typically total 15 percent. However, allowances may be higher or lower depending

on the nature of the work and related working conditions. For example, strenuous work in an

extremely hot environment would typically merit a higher PF&D allowance than light labor

performed in an air conditioned room.

Personal Allowance. A personal allowance considers time for a worker to take care of personal

needs, such as trips to the rest room and drinking fountain. The table below

Personal Allowance Considerations

Personal allowance

documentation should

document:

Considerations Typical

Percentage

Allowance

A Basic Allowance which

considers the breaks available

for work during an 8-hour day.

Most firms allow, at least, two 10-minute

breaks during each 8-hour shift, the basic

personal allowance is 4.2 percent (20

minutes/480 minutes).

4.2

Normal office conditions 0.0

Normal shop, central heat, slightly dirty or

greasy.

1.0

Slightly disagreeable conditions. Exposed to

inclement weather part of the time, poor

heating, or poor cooling.

3.0

Extremely disagreeable conditions.

Proximity to hot objects, continuous

6.0

exposure to disagreeable odors and fumes, or

to excessive temperature ranges.

Total time allowed:

5 minutes 1.0

10 minutes 2.1

15 minutes

20 minutes

3.1

4.2

Any allowance for work

performed in a super-clean

room.

An additional allowance may be added to

consider the time require to assure that

super- clean room requirements are met.

4.0

Fatigue Allowance. A fatigue allowance considers the time required to recuperate from fatigue.

Fatigue Allowance Considerations

Personal allowance

documentation

should document:

Considerations Typical

Percentage

Allowance

Any allowance for

handling heavy

weights.

Effective Net

Pounds Percent of Time Under Load

Handled 1-12 13-25 26-50 51-75 76-100

1-10 0 1 2 3 4

11-20 1 3 5 7 10

21-30 2 4 9 13 17

31-40 3 6 13 19 25

41-50 5 9 17 25 34

51-60 6 11 22 x x

61-70 7 14 28 x x

71-80 8 17 34 x x

x – Study for possibilities for worker rotation and

other means to relieve fatigue.

Select

percentage

from table.

Multiply the table values above by the following

factors to consider lifting requirements:

For picking up from the floor, multiply the table

value by 1.10.

For placing the load above chest height, multiply

table value by 1.20.

For getting the load from chest height, multiply the

basic allowance by 0.50.

Depends on

work.

For sliding and rolling objects, multiply the weight

by the coefficient of friction to determine the

Depends on

work.

effective weight moved.

Coefficients of Friction (Average Values)

Surfaces Friction Coefficient

Wood on Wood 0.4

Wood on Metal 0.4

Metal on Metal 0.3

Sitting or standing. (Work will normally be less

tiresome if the position is varied frequently.)

0.0

Sitting. 1.0

Walking. 1.0

Standing. 2.0

Climbing or descending ramps, stairs, or ladder. 4.0

Working in close cramped quarters. 7.0

Any allowance for the

mental requirements

of the job.

Work largely committed to habit (e.g., simple

calculations on paper, reading easily understood

material, counting and recording, simple inspection

requiring attention but little discretion, or arranging

papers by letter or number).

0.0

Work requires full attention (e.g., copying numbers

or instructions, remembering part number while

checking a parts list, or filing papers by subject of

familiar nature.

2.0

Work requires concentrated attention (e.g., reading

of nonroutine instructions or cross-checking items).

4.0

Work requires deep concentration (e.g., making

swift mental calculations or memorizing items).

8.0

Any allowance for the

lighting on the job

site.

Continual glare on work area.

Work requiring constant change of light.

Less than 75 foot candle power on work surface for

normal work.

Less than 125 foot candle power on work surface

for close work.

2.0

Any allowance for

noise on the job site.

Constant, rather loud noises over 60 decibels (e.g.,

machine shops or motor test shops).

1.0

Average constant noises, level but with loud, sharp,

intermittent, or staccato noise (e.g., nearby riveters

or punch presses).

2.0

0.00 to 0.20 minute cycles 4.0

0.21 to 0.40 minute cycles 3.0

0.41 to 0.80 minute cycles 2.0

0.81 to 2.50 minute cycles 1.0

2.51 minutes or more 0.0

Any allowance for the

use of safety devices

or clothing.

No allowance should be made here unless it is

necessary to remove the equipment occasionally

for relief or if wearing the item causes fatigue.

Face shield 2.0

Rubber boots 2.0

Goggles or welding mask 3.0

Tight, heavy protective clothing 4.0

Filter mask 5.0

Safety glasses 0.0

Delay Allowance. A delay allowance covers unavoidable, predictable and unpredictable delays

for such activities as replenishing materials, rejecting nonstandard parts, making minor

equipment repairs, and receiving instructions.

Delay Allowance Considerations

Personal allowance

documentation

should document:

Considerations Typical

Percentage

Allowance

Basic Allowance Isolated job. Little coordination with adjacent jobs. 1.0

Fairly close coordination with adjacent jobs. 2.0

Worker moves once each 5 minutes. 5.0

Worker moves once each 30 minutes. 3.0

Worker moves once each 60 minutes. 2.0

Worker moves once each 2 hours. 0.0

Special Allowances . Any proposed special allowance must be supported by detailed

engineering analysis. An appropriate study should be conducted in each shop or functional area

to ascertain any requirement for a separate delay allowance. The analyst should assure that there

is no duplication between cycle time elements and allowance elements and that the Special

Allowance does not become a dumping ground for operation activity that is not an integral part

of shop work load.

â¢ Work elements such as cleaning chips from equipment, tool care, or tool replacement,

though occurring irregularly, should be measured and the time required prorated directly

to the machine operating portion of the work cycle rather than as an allowance.

â¢ Certain other irregularly occurring elements having a direct relationship to the job such as

obtaining parts and materials and periodic inspection should be added to the cycle time

on a prorated basis or as a separate work element rather than added as an allowance.

When a special allowance is appropriate, the time required is first calculated in minutes and then

converted to a percentage. The base for calculating and applying the allowance percentage is

normally the sum of the leveled time and the PF&D allowance. Appropriate special allowances

typically fall into two categories:

â¢ Those that consider elements that occur on an unforeseeable basis:

o Power failures of nonreportable duration.

o Minor repairs to defective parts.

o Waiting for a job assignment.

o Obtaining job information from a supervisor, inspector, or production control

specialist.

o Unsuccessful hunt for parts or materials.

o Machine breakdown of nonreportable duration.

â¢ Those that consider elements that occur periodically (daily, weekly, hourly) such as:

o Cleaning and lubricating equipment.

o Work area clean-up.

Applying an Allowance to Leveled Time . Allowances are normally expressed as a percentage of

standard time spent unproductively (e.g., a 15 percent PF&D Allowance indicates that 15 percent

of the worker’s standard time is spent unproductively). To apply an allowance, the analyst must

determine how much the leveled time must be increased to allow for the unproductive time. This

is accomplished by dividing the leveled time by the percentage of time spent productively.

Where:

T S = Standard time

T L = Leveled time

A PF&D = PF&D allowance in decimal form

For example: The leveled time for a particular task is 170 minutes, the PF&D Allowance is 15

percent, and there is no special allowance. The standard time would be calculated as:

Note: The leveled time is 85 percent of the standard time (85% of 200 is 170). The remaining 15

percent of the standard time (15% of 200 minutes is 30 minutes) is the allowance for personal,

fatigue, and delay factors.

8.3 – Measuring And Projecting Operation Efficiency

Comparing Labor Standard with the Actual Time . Standards represent goals for efficient

operation. Tasks are rarely completed in the allowed standard time. Work Measurement Systems

commonly use realization or efficiency factors to evaluate how the actual time required to

complete a task compares with the standard time for that task. Analysts can then use these

measures to identify tasks that require special analysis to identify and correct inefficient

operations.

Since estimators strive to estimate realistic contract costs, they use realization or efficiency

factors with labor standards to estimate future labor hours required to complete the task.

Calculating a Realization Factor . A realization factor is generally a measure of overall

performance (e.g., shop, product line, or plant). It will normally be calculated from historical

data as:

Where:

F R = Realization factor

T A = Acutal time to perform the work

T S = Standard hours for the task

R = Repetitions of the task included in the work

Don’t be confused by the fact that some firms refer to this calculation as an efficiency factor.

For example: A task has a standard time of 1.5 hours. Actual time to perform the task 100 times

is 300 hours. Using the model at ***, the realization factor would be 2.00

In the above example, actual experience shows that the work takes twice as many hours as the

standard time indicates.

Developing an Estimate Using a Realization Factor . The estimator can use the standard time

and realization factor to develop a realistic labor-hour estimate using the model at ***.

For example. An estimate of the actual time to complete the task above for 50 units would be

calculated as:

Y = T S x R x F R

= 1.5 x 50 x 2.00

= 150 labor hours

Where:

Y = Estimated hours

All other symbols are as defined above

Calculating an Efficiency Factor . An efficiency factor is calculated to demonstrate efficiency

against the standard (e.g., a task with an efficiency factor of .60 is being performed at 60 percent

efficiency). The factor is normally calculated:

Where:

F E = Efficiency factor

All other symbols are as defined above

For example. A task has a standard of 1.8 hours. Actual time to perform the task 100 times is

400 hours. The efficiency factor would be calculated as follows:

Developing an Estimate Using an Efficiency Factor . The estimator can use the standard time

and efficiency factor to develop a realistic labor-hour estimate.

For example. An estimate of the time to complete the task above for 50 units would be

calculated as:

Analyzing Realization and Efficiency Factors . Analysis of labor estimates developed using labor

standards requires extensive knowledge and experience. Even skilled industrial engineers

typically require special training in work measurement analysis. As a result, you should normally

request technical support whenever an offeror estimates labor hours using labor standards.

For each standard, offerors should be required to provide information on internal analyses of the

variance between the actual time required to complete the work and the standard time to

determine the causes for the variance and identify ways of managing performance improvement.

You should expect offeror’s to demonstrate continued improvement in realization and efficiency

factors. The figure below depicts some of the reasons for that improvement.

â¢ At Unit #1, total labor-hours include substantial inefficiencies related to technical,

logistics, learning, and other factors.

â¢ As production increases, there should be reductions in all areas of inefficiency. In most

cases, there should also be an improvement in the labor standard itself, as better

production methods are identified and implemented.

â¢ By Unit #1000, the contractor should be operating efficiently, with only minor

inefficiencies related to such factors as unavoidable parts shortages.

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