NCDA: Pickle Sorter NCDA: Pickle Sorter Concept ReviewConcept Review

Project 98.09Project 98.09

Sponsored 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 Simplicity

Price 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

a

bcd

Denotes Very Strong Correlation

Denotes Strong Correlation

Denotes Weak Correlation

Denotes 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

Alignment

1 Lane Dividers

2 Rollers

3 Chains

4 Compartments

Identification

1 Imaging

2 Pins

3 Calipers

4 Rolling

Removal

1 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.