13. Vision Inspection 2012
Transcript of 13. Vision Inspection 2012
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Vision and Visual Search
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Why is understanding visual search
performance it important?• Designing:
• Inspection for quality assurance
• Inspection for maintenance
• Inspection for safety
• Inspection, inspection, inspection…and –• Human-environment interaction
• Human-product interaction
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Poor Lighting
• Can result in eye fatigue– Low light levels
– Glare
• Impairs tasks thatrequire vision– Inspection
– Quality
– Service
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Visual Search and Detection
• The goal of the HFE engineer is usually to
maximize accuracy, minimize search times,
and minimize effort
• Sometimes these occur together and
sometimes do not
• Different factors affect each differently
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Visual Search & Detection
• Search– Eye Movements through the visual field (various
strategies)
• Detection
– Targets and non-targets (noise)
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Find the Letter “V”
Raise your hand when you do!
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Search Strategies
Serial Search Model
• Targets & Non-targets
• Items inspected serially (one at a time) todetermine target/non-target
• Search patterns affected by organization of space(e.g., left right/top down if organized; more
random and less exhaustive if no pattern)• For targets that are not readily visible, the increase
in p(detect) diminishes with time
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Visual Search & Detection
• Influences– expectancy – where a target might be
• use to structure display so know where to start thevisual search
– conspicuity leads to its detection (“pops out”)of field – search is effectively parallel, or all at
once rather than serial• good if pop out is desirable, but will distract if not a
target
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Detection
• Once possible target has been detected
through search, must decide if it is in fact a
target
• Can use models of signal detection
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Signal Detection Theory
• Model of how humans separate
“noise” = all stimuli, whether relevant or not from
“signal” = the relevant, important information
To make decisions aout, e!g!,
" #art defect vs! not
" $hich icon to click on
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%pplications of Signal Detection
Theory to &nspection• 'ollect oservation (through sensory systems),
then determine if there is enough evidence toconstitute a signal " 'rack is large enough
" *egion on +ray is cloudy enough
" -ever is high enough (here, not necessarily throughsenses, ut could e)
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Signal Detection Theory
Hit False Alarm
Miss CorrectRejection
Signal
Say
Noise
Noise
SaySignal
Type 1Error
Type 2
Error
State of the World
O p e r a t o r B e h a v i o
r
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Signal Detection Theory
• Sensitivity (d’)- how good an operator is at
telling signal from noise
– “Bottom Up Influencers”: an be influenced bysignal to noise ratio, redundancy of signal, etc.
– “Top Down Influencers” – personal
characteristics
– These can be influenced by a number of things
E.g., payoffs, incentives, experience,
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'ase Study
• Manufacturing #lant for a #harmaceutical 'ompany• .isual &nspection Task to identify defective pills (color an
important cue)
• /utput (efore intervention)0 123 ppm
" 'ommon #rolems0• -atigue
• 4igh Turnover
• $astage 4igh (false alarms)
• Management willing to look at a new manufacturing process
" 5oals0 More output, less personnel cost, reduce wastage
• 4ow can information aout visual search ailities and Signal
Detection Theory help6
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Task0 To inspect pill color
Manufacturing #rocess0
7atches (12 parts8atch) on a
'onveyor
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.isual Search and &nspection• -astpaced
• 9ncertainty of pill in terms of color
• .ariaility in response (accept or re:ect)
• *ules help, ut do ;/T rela< :udgment and have costsassociated with time
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;ot &deal &deal ;ot &deal
.isual *ules (posted in front of the inspector)
Suggested inspection time: 3 sec/batch = .214 sec per
pill
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%dditional Suggestions0 filtering
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%dditional Suggestions0 separate into rows
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Redced !n"ormation
F l o # n o t i n t e
r r p t e d $
e
x p e c t a
n c y
4-8> &ntervention01! /ptimal presentation of material
?! -ast rate of parts (@ A3B)
C! Saved 1! million8Euarter reduced material wastage
increased output
reduced fatigue F MSD