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Title: Introduction to Human Factors/Ergonomics (HFE)


1
Introduction to Human Factors/Ergonomics
(HFE)Engineering Anthropometry
  • Hardianto Iridiastadi, Ph.D.

2
Introduction
  • Variability in physical dimensions
  • Studied earlier in Anthoropology (study of
    mankind)
  • Interest in physical aspects (beginning of
    anthropometry)
  • Later, data are used for biomechanics
    investigations
  • The need to design workplaces to accomodate
    differences in body dimensions

3
Human variation
4
Factors Affecting Anthropometrical Variation
  • Age
  • Gender
  • Race Ethnic
  • Socio-economics
  • Occupation
  • Life style
  • Circadian
  • Secular trend
  • Measurement

5
Ergonomic Implications
  • International markets
  • Different target countries
  • Transfer of technology
  • Job selection
  • Healthy worker effect
  • Fit the man to the job

6
Engineering Anthropometry
  • a branch of science originating from
    anthropology that attempts to describe the
    physical dimensions of the (human) body
  • anthropos man
  • metron measure

7
Types of Anthropometric Data
  • Physical (Static) anthropometry which addresses
    basic physical dimensions of the body.
  • Functional anthropometry concerned with
    physical dimensions of the body relevant to
    particular activities or tasks.
  • Newtonian data body segment mass data and data
    about forces that can be exerted in different
    tasks/postures

8
Applications
  • Tools design
  • Consumer product design
  • Workplace design
  • Interior design

9
Applied Anthropometry
10
Measurement Techniques
  • Positions
  • Standing naturally upright
  • Standing stretched to maximum height
  • Lean against a wall
  • Sitting upright
  • Lying (supine posture)
  • Anatomical position (see Kroemer et al)

11
Measurement Techniques
  • Some key measurement terms
  • Height
  • Breadth
  • Depth
  • Distance
  • Curvature
  • Circumference
  • Reach

12
Measuring Devices
13
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14
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15
Newer Measuring Devices
  • Photograph
  • Use of grids
  • Image processing techniques
  • Can record all three dimensional aspects
  • Infinite number of measurements
  • Drawbacks
  • Parallax
  • Body landmarks cannot be palpated

16
Newer Measuring Devices
  • Whole body scanner
  • Ergonomic center UI
  • 50,000 - 400,000
  • Hundreds of variables
  • Standing and
  • seated posture
  • Combined with
  • modeling software
  • (Jack, Mannequin, etc.)

17
Sample Anthropometric Data
18
Statistics
  • Coefficient of variation
  • Data diversity sd/mean
  • CV 5 (10 for strength data)
  • Large CV should be suspected
  • Standard error of the mean (se)
  • se sd/vn
  • Useful for describing confidence interval
  • E.g., 95 CI mean 1.96 se

19
Statistics
  • Means (?) and standard deviations (?) are
    typically reported for anthropometric data (often
    separated by gender)
  • Use of these value implicitly assumes a Normal
    distribution. Assumption is reasonable for most
    human data.
  • Percentiles can easily be calculated from mean
    and std.dev. using these formulas and/or standard
    statistical tables (usually z).

20
Statistics
  • Percentile
  • Commonly used 5th, 95th, 50th (median)
  • Lower-limit dimension the smaller the system,
    the more unusable by the largest user ? Use high
    percentile
  • Upper-limit dimension the bigger the system, the
    more unusable by smallest user ? Use low
    percentile

21
Statistics - Standard Normal Variate
  • Z (y-?)/?
  • Normally distributed with mean 0 and variance
    1
  • z is N(0,1)
  • From tables of normal cumulative probabilities
  • Pzz(A) A
  • Example if zA 2, A 0.9772 (two std.dev.
    above mean is the 97.7-ile)
  • Properties of z
  • zA gt 0 above mean (gt50-ile)
  • zA 0 at mean (50-ile)
  • zA lt 0 below mean (lt50-ile)

22
Normal Distribution Table
23
Percentile Example
  • For female stature (from Table)
  • ? 160.5 cm
  • ? 6.6 cm
  • What female stature represents the 37.5th -ile?
  • From normal distribution
  • z(37.5) -0.32
  • Thus, X(37.5) ? z?
  • 160.5 - (0.32)(6.6)
  • 158.4 cm

24
Anthropometric Data Variances
  • To combine anthropometric dimension, need to
    calculate a new distribution for the combined
    measures, accounting also for the covariance
    (Cov) between measures (M mean S std. dev.)

MXY MX MY SXY SX2 SY2
2Cov(X,Y)1/2 SXY SX2 SY2
2(rXY)(SX)(SY)1/2 MX-Y MX - MY SX-Y SX2
SY2 - 2Cov(X,Y)1/2 SX-Y SX2 SY2 -
2(rXY)(SX)(SY)1/2
  • Means add, variances do not!

25
Class Activity
26
Anthropometrical Design Procedures
  1. Determine dimensions of product which are
    critical for design (considering effectiveness,
    safety and comfort)
  2. Determine the related body dimensions
  3. Select user population (who will use the product
    or workplace)
  4. Conduct reference study to find secondary data,
    if available (considering population
    characteristics) or conduct measurement
  5. Select percentile

27
The Average Human
  • Anthropometric data for individuals is often
    estimated using stature or body weight in linear
    regression equations.
  • Ex average link lengths as a proportion of body
    stature
  • Advantages
  • Simplicity
  • Disadvantages
  • relationships are not necessarily linear, nor the
    same for all individuals
  • Values represent averages for a portion of a
    specific population

28
Anthropometry in Design
  • Anthropometric data is most often used to specify
    reach and clearance dimensions.
  • The criterion values most often used
  • Reach 5 Female
  • Clearances 95 Male
  • Try to accommodate as large as possible user
    population within constraints

29
Design Approaches
  • Design for extremes
  • emphasize one 'tail' of distribution
  • Design for average
  • emphasize the center of a population distribution
  • Design for adjustability
  • emphasize that all potential users/consumers are
    'equal
  • Varying ranges of accommodation
  • 5th-95th ile typical
  • 25th-75 ile less critical functions or
    infrequent use
  • 1st - 99th ile more critical functions /- low
  • 0.01 - 99.99 ile risk of severe outcomes

30
Design for Extremes
  • Example Door Height
  • Assuming a normal distribution
  • z (X - ?)/?
  • Obtain z gt -ile from stats table
  • What height to accommodate? (95th-ile male)
  • ? 69 ? 2.8 (from anthropometric table)
  • z0.95 1.645 (X - 69)/2.8 gt X 73.6
  • Additional allowances?
  • Hair
  • Hats and shoes
  • Gait
  • Etc.

31
Examples
Which design strategy should be employed?
  • leg clearance at a work table
  • finger clearance for a recessed button
  • height of an overhead conveyor system
  • grip size for a power tool
  • weight of a power tool
  • height of a conveyor
  • strength required to turn off an emergency valve

32
General Strategies and Recommendations
  • Design for Average
  • Usually the worst approach both larger and
    smaller users wont be accommodated
  • Design for Extremes
  • Clearance use 95th percentile male
  • Reach use 5th percentile female
  • Safety accommodate gt99 of population
  • Design for Adjustability
  • Preferred method, but range and degrees of
    adjustment are difficult to specify

33
Homework
  • Working in groups
  • Select a workplace near campus. Identify any
    ergonomic mismatch. Suggest how the workplace
    can be better designed from the perspective of
    engineering anthropometry. You should outline the
    design approach.
  • Pick a journal paper that discusses the use of
    anthropometric data in design. Submit a one-page
    summary (in Indonesian) of the paper. Also submit
    softcopy of the paper.
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