introduction to human factors/ergonomics (hfe) “engineering anthropometry”
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Introduction to Human Factors/Ergonomics (HFE) “Engineering Anthropometry”. Hardianto Iridiastadi, Ph.D. Introduction. Variability in physical dimensions Studied earlier in Anthoropology (study of mankind) Interest in physical aspects (beginning of anthropometry) - PowerPoint PPT PresentationTRANSCRIPT
Introduction to Human Factors/Ergonomics (HFE)
“Engineering Anthropometry”
Hardianto Iridiastadi, Ph.D.
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
Human variation
Factors Affecting Anthropometrical Variation
Age Gender
Race & Ethnic Socio-economics
Occupation Life styleCircadian
Secular trend Measurement
Ergonomic Implications
• International markets– Different target countries
• Transfer of technology
• Job selection– Healthy worker effect– Fit the man to the job
Engineering Anthropometry
• “a branch of science originating from anthropology that attempts to describe the physical dimensions of the (human) body”
“anthropos” = man
“metron’ = measure
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
• Tools design
• Consumer product design
• Workplace design
• Interior design
Applications
Applied Anthropometry
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)
Measurement Techniques
• Some key measurement terms– Height– Breadth– Depth– Distance– Curvature– Circumference– Reach
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
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.)
Newer Measuring Devices
Sample Anthropometric Data
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/√n– Useful for describing confidence interval– E.g., 95% CI = mean ± 1.96 se
• 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).
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
Statistics
• Z = (y-)/– Normally distributed with mean = 0 and variance = 1– z is N(0,1)
• From tables of normal cumulative probabilities– P{z≤z(A)} = A
– Example: if zA = 2, A = 0.9772 (two std.dev. above mean is the 97.7%-ile)
– Properties of z:• zA > 0; above mean (>50%-ile)
• zA = 0; at mean (50%-ile)
• zA < 0; below mean (<50%-ile)
Statistics - Standard Normal Variate
Normal Distribution Table
• 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
Percentile Example
• 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.):
Anthropometric Data: Variances
Means add, variances do not!
MX+Y = MX + MY
SX+Y = [SX2 + SY
2 + 2Cov(X,Y)]1/2
SX+Y = [SX2 + SY
2 + 2(rXY)(SX)(SY)]1/2
MX-Y = MX - MY
SX-Y = [SX2 + SY
2 - 2Cov(X,Y)]1/2
SX-Y = [SX2 + SY
2 - 2(rXY)(SX)(SY)]1/2
Class Activity
1. Determine dimensions of product which are critical for design (considering effectiveness, safety and comfort)
2. Determine the related body dimensions3. 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
Anthropometrical Design Procedures
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 statureAdvantages:
◦ Simplicity
Disadvantages:◦ relationships are not necessarily linear, nor the same for all
individuals◦ Values represent averages for a portion of a specific population
The “Average Human”
• 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
Anthropometry in Design
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
Design Approaches
Example: Door HeightAssuming a normal distribution
◦ z = (X - )/ ◦ Obtain z => %-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 => X = 73.6”◦ Additional allowances?
Hair Hats and shoes Gait Etc.
Design for Extremes
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
ExamplesWhich design strategy should be employed?
Design for Average:◦ Usually the worst approach: both larger and smaller users
won’t be accommodated
Design for Extremes:◦ Clearance: use 95th percentile male◦ Reach: use 5th percentile female◦ Safety: accommodate >99% of population
Design for Adjustability◦ Preferred method, but range and degrees of adjustment are
difficult to specify
General Strategies and Recommendations
• 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.
Homework