ncda: pickle sorter concept review
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NCDA: Pickle Sorter NCDA: Pickle Sorter Concept ReviewConcept Review
Project 98.09Project 98.09Sponsored by Ed Kee ofSponsored by Ed Kee of
Keeman Produce, Lincoln, DEKeeman Produce, Lincoln, DE
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OverviewOverview
• Introduction to the Problem• Method
– Wants Metrics– System and Functional Benchmarking– Concept Generation – Concept Selection
• Schedule• Budget
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BackgroundBackground
• Title: Pickle Sorter • Sponsor: Ed Kee of Keeman Produce• Problem: The cucumber pickling industry
currently separates out undesirable pickles by hand. Mr. Kee would like a device to efficiently and reliably separate the usable cucumbers from the unusable ones.
Plant SchematicPlant Schematic
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StrategyStrategy
• Mission: To provide an integrated, automated system to sort out undesirable pickles on the processing line.
• Approach: Collect customer wants and develop them into metrics which can be used to evaluate benchmarks and concepts, leading to a final design solution.
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Customer WantsCustomer Wants
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Customer Wants (Customer Wants (cont’d)cont’d)
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Wants Wants Metrics Metrics
Quality Metrics Cost Effectiveness Working Area Speed Reliability Portability Adaptability SimplicityPrice a d d d d d d dPickles/ minute d c d a d d a c% bad removed d a d d d d b c% good removed d a d d d d b cmean time to failure d d d d a d c cWidth d d a d d b b dLength d d a d d b b dWeight d d d d d a b c
abcd
Denotes Very Strong CorrelationDenotes Strong CorrelationDenotes Weak CorrelationDenotes No Correlation
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BenchmarkingBenchmarking
• Patents, Internet and Trade Journals• System:
– Integrated production line identification and sorting• Function:
– Material handling equipment and identification– System consists of three main functions: alignment,
identification and removal.
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System BenchmarksSystem Benchmarks
•Machine Vision common to all System Benchmarks•Typical Sorting Parameters
- Color, Size(length), Surface Features
•Best Practices
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Functional BenchmarksFunctional Benchmarks
Alignment • Common Material Handling Task• Best Practices: lane dividers, overhead rollers
Removal• Wide Range of Possible Methods• Best Practices: air jet, piston, robotic arm, trapdoor
Identification *Critical System Function• Best Practice: Machine Vision was the only geometric identification system found in use
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Alignment
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Sorting
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Target ValuesTarget Values
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Concept GenerationConcept Generation
Benchmarking• Functions Which Satisfy Target Values• Best Practices• Produce Handling Applications
Brainstorming • Mechanical Solutions for Identification• Use of Physical Properties for Self-Separation
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Concepts
Alignment1 Lane Dividers
2 Rollers
3 Chains
4 Compartments
Identification1 Imaging
2 Pins
3 Calipers
4 Rolling
Removal1 Air Jet
2 Piston
3 Trapdoor
4 Tilting Tray
5 Robot Arm
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Concepts (cont’d)
Piezoelectric Pins– Displacement of pins in field creates 3-D surface image
Calipers– Difference in caliper displacement provides degree of curvature
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Imaging Process
• Hardware: – Digital Video Camera– Frame-Grabber– Data Acquisition
Board– Low Cost PC
• Software: – Image processing
utilities– Specialized Grading
software– GUI for operator
control over selection parameters
• Input/Output controlled by microcomputer
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Imaging Algorithms
• Image as camera would receive it:
• Processing includes:– Histogram analysis– Threshold selection– Application of an edge
or range detection algorithm
– Deterministic process
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Image Flattening
• Thresholded Image:• Proper threshold level
is determined by Histogram analysis
• A good threshold level may change slightly from batch to batch, but not often within a batch of pickles.
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Edge Detection Algorithms
• Ex: Canny Algorithm • Ex: Zero Crossings
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Edge Detection Algorithms
• Ex: Gradient Magnitude • Ex: Edge Tracking
Complete Model
Progress To DateProgress To Date
Critical Tasks in SpringCritical Tasks in Spring
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Estimated Hours
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Estimated CostsEstimated Costs
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Closing Points
• Problem Statement• Concept Selection Justification:
– Alignment: Overhead Rollers– Identification: Computer Controlled Imaging– Removal: Air Propulsion
• Physical Demonstration of Model.
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