13. Vision Inspection 2012

8/20/2019 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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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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• 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

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13. Vision Inspection 2012