row crop harvest logistics for single harvester/grain cart

Row Crop Harvest Logistics for Single Harvester/Grain Cart Operations

John Evans, MSPh.D. Candidate

Joe Luck, Associate Professor Santosh Pitla, Assistant Professor

Department of Biological Systems Engineering University of Nebraska Lincoln

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• Project Motivation • Objectives • Harvester Modeling • Grain Cart Modeling• Decision Support Tool

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Outline

Shrinking Profit Margins§ Cost of equipment ↑§ Cost of inputs ↑§ Commodity prices ↓

Higher in-field efficiency is needed to reduce cost and increase productivity § Equipment selection § Time and compaction reduction

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Project Motivation

Create a practical and feasible harvest logistics model with decision support tools for single harvester, single grain cart operations. • User Inputs

§ Yield Monitor Data § Machine Capacities

- Harvester- Grain Cart

• Outputs§ Optimized Paths

- Productivity- Bottlenecks- Economics

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Project Objective/ Scope

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Harvester Logistics Modeling

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ObjectiveDevelop a mathematical model of single harvester operation in headland field patterns capable of the following:1.Minimizing the non-working in-field travel of the harvester in

irregular shaped fields.2.Producing solution that allows for unloading on the go. 3.Calculate the possible reduction in non-working travel compared to

actual harvest data.

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Project Objective/ Scope

OptimizationAlgorithm

PassesThatTheHarvesterMustComplete OptimalRouteMinimizingTime

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General Models • Bochtis, D. D., & Vougioukas, S. G. (2008). Minimizing the non-working distance travelled by

machines operating in a headland field pattern. Biosystems Engineering, 101(1), 1–12. https://doi.org/10.1016/j.biosystemseng.2008.06.008

• Oksanen, T., & Visala, A. (2009). Coverage path planning algorithms for agricultural field machines. Journal of Field Robotics, 26(8), 651–668. https://doi.org/10.1002/rob.20300

Harvest Modeling• Hansen, A. C., Zhang, Q., & Wilcox, T. A. (2007). Modeling and analysis of row crop

harvesting patterns by combines. Transactions of the ASABE, 50(1), 5–12.

• Ali, O., Verlinden, B., & Van Oudheusden, D. (2009). Infield logistics planning for crop-harvesting operations. Engineering Optimization, 41(2), 183–197. https://doi.org/10.1080/03052150802406540

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Past Work

Need spatial data to validate and compare against harvest optimization model.• Desired Data:

§ Spatial Machine Data - Engine Speed - Fuel Usage - Unload Auger Status

§ Spatial Agronomic Data- Yield

~ 3600 acres of data collected from two producers

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Harvester Data Collection

• Loop

For w < 2r, theta is given by: 𝜃 = cos'( )*+

𝐿𝑜𝑜𝑝𝑇𝑢𝑟𝑛𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = 𝜋 ∗ 𝑟 ∗ (𝜃 + 90)

90 + ∆𝑦

• U-Turn

𝑈_𝑇𝑢𝑟𝑛𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = F𝑑GH

�

G∈H

+ ∆𝑟𝑖 + ∆𝑟𝑗

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Turning Distance Calculation

• Plotted actual vs. predicted of every turn in real field path

• Predicted was almost always less than actual because predicted is perfect turn at tightest turning radius.

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Turning Distance Verification

Min ∑Harvester_Non-Working_Distance

With respect to:

1) Unload Auger Position2) Unloading Rate 3) Bin Capacity

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Optimization Equation

Genetic Algorithm§ Generate Random Population (Set of Paths)

- Paths were created from permutation of passes- Direction of passes was based on order from first

pass§ Calculate Route Length

- Check constraints - add penalty if necessary - Distance between passes was calculated and

summed§ Selection of Best Routes

- Top 10% of shortest paths are selected as “parents” and are crossed and mutated to generate a new population of “children”

§ Settings - Elitist Selection - Population (group of paths) size = 600- Max iterations = 100

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Optimization Method

Passes

Path

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ResultsActual vs. Optimized • Irregular shaped fields*• Harvest unload

consideration • 29.1% average

reduction of non-working travel

Field Crop Area (m2)[ac]

Actual Path Order w/ Modeled Turns

Optimized Route Distance (m)

% Non-Working Travel Reduced

EFE Soybeans 22070 [54.53] 2705 1880 30.50

R Soybeans 35360 [87.38] 3019 2067 31.53

H Corn 3349 [8.27] 1317 984 25.28

* Continuous AB passes required

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Grain Cart Modeling

Calculate cycle time of the grain cart § Account for cart unloading § Avoid obstacles (unharvested crop, fence lines, etc..)

Inputs: § Harvester path§ Harvester unloading points§ Cart unloading location§ Speed

- Loaded - Unload

Outputs:§ # of harvester waiting events§ Total harvester waiting time § Total grain cart travel distance

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Grain Cart Model Objective

Need grain cart data to determine if it is a limiting factor• Desired Data: Spatial Machine Data and Bin Level (Grain

Mass)• Gap in current data collection methods:

§ Scale data is separate from machine data. § Scale data is usually only recorded when off loading to truck. § Machine data not usually recorded at all. § GPS is not available because units are often shared between tractor and

combine.

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Grain Cart Data Collection

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Grain Cart Data Collection• Initial Solution

§ Publish Scale Data on CAN Bus- Instrumentation Amplifier - CAN Node

§ CAN Data Logger w/ GPSSCALE DISPLAY

INSTRUMENTATIONAMPLIFIER

CAN NODE

J1939 CAN LOGGER

POWERCONTROL

TRACTOR DATASIMULATOR

(TESTING ONLY)

TEST LOAD CELL

Bench Test Spatial Variation of Grain Cart Weight

LegendGrain_CartWieght__lb

< 15550

15499 - 32800

32799 - 48500

48501 - 61800

> 61800

Unloading Location

Weight lbs.

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Boundary Generation

Coverage map using polygons Binary representation

Binary Mask Legend▪ RestrictedTravel▪ UnrestrictedTravel−CartPath

Legend▪ HarvesterCoverage○ HarvesterUnload− Boundary

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Grain Cart

Binary Mask Legend▪ RestrictedTravel▪ UnrestrictedTravel−CartPath

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Grain Cart Simulation

Binary Image

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Grain Cart Simulation

80536 Meters (~50 Miles) of Cart Travel

Actual Grain Cart Travel Data

Legend− HarvesterUnloadPath−ActualCartPath

Simulated Grain Cart Travel Data

54305 Meters (~34 Miles) of Cart Travel

Legend− HarvesterUnloadPath−ActualCartPath

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Grain Cart Model Example Output

§ # of harvester waiting events = 2§ Total harvester waiting time = 4.56 min § Total grain cart travel distance = 51.0km

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Decision Support Tool

Tool capable of identifying/calculating: • Bottlenecks • In-field travel • Cost per bushelVarying:

§ Header width § Bin capacities

- Harvester - Grain cart

§ Unloading rate - Harvester - Grain cart

§ Economic factors

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Objective

Purpose:Define the passes the harvester needs to complete based on:

- Header width- AB pass orientation

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Pass Generation

• Split passes§ Distance § Heading§ Swath width

• Find straight passes§ STD of heading

• Find AB pass§ Fuzzy subtractive clustering

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Pass Generation

- AB PASS

- HEADLAND

• Find baseline pass using boundary, AB pass heading, and new header width

• Offset new lines • Interpolate yield to new

points on 1hz interval

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Pass Generation (Header Width Change)

AB Baseline

Start Simulation

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Decision Support Tool GUI

Data Import

Economic Values

Grain Cart Parameters

Harvester Parameters

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Decision Support Tool Results

Harvester 1 2HeaderWidth(ft) 40 40

Area(ac) 43.06 43.06Distance(mi) 9.06 9.06

Productivity(ac/h) 23.78 20.45Efficiency 0.9 0.9Fuel($/ac) 2.7 3.4

TotalCost($/ac) 13.26 19.52TotalCost($/bu) 0.31 0.45

GrainCart 1 2Binsize 1282 880

#ofwaitevents 1 5

CumulativeWaitTime(min) 2.43 13.65

• Harvest Logistics Model§ Real field data § Irregular shape fields* § Optimized path

• Grain Cart Model § Calculate

- Cycle time- Total distance

§ Identify - Limitations- Current Efficiency

• Decision Support Tool§ Economics of equipment sizing

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Project Outcomes

CLAAS OmahaMaury Salz

University of Nebraska LincolnDr. Santosh Pitla

Dr. Joe Luck

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Special Thanks

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Thank You

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Grain Harvest Logistics Modeling

• Loop

For w < 2r, theta is given by: 𝜃 = cos'( )*+

𝐿𝑜𝑜𝑝𝑇𝑢𝑟𝑛𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = 𝜋 ∗ 𝑟 ∗ (𝜃 + 90)

90 + ∆𝑦

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Turns

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Pass Generation from Planter Path Files

• U-Turn

𝑈_𝑇𝑢𝑟𝑛𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = F𝑑GH

�

G∈H

+ ∆𝑟𝑖 + ∆𝑟𝑗

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Turns

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Simulation

Min ∑Harvester_Operation_Time

With respect to:

1) Unload Auger Position2) Bin Capacity 3) Boundaries4) Grain Cart Cycle Time

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Optimization Equation

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Project Objective/ Scope

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Scenario Analysis§Change Machine Parameters§Re-run Harvest Simulation §Compare

- Time to Complete- Field Efficiency - Limiting Factors