Monitoring Productivity of Harvesting Operations

Transcription

1 Monitoring Productivity of Harvesting Operations Chad Niehaus University of Illinois at Urbana-Champaign February 4, 2014

2 Motivation Farm equipment has reached a threshold in terms of size We have the ability to collect large amounts of data from machines How do we use this data to help in decision support

3 Objectives of Study Quantify and evaluate machine performance for a complete season of corn production by recording and mapping machine usage during normal field operations Investigate predictive strategies that can be used to control machinery to maximize fuel usage efficiency and productivity based on current field conditions Determine field efficiencies and field capacities to reflect machine and operator performance

4 Methods and Procedure Collect CAN bus data off of all vehicles from select farms. Data Variables collected Longitude/Latitude/Altitude Travel Speed Engine Speed Separator Engage Auger Position etc.

5 Data Analysis Divide Combine Harvesting into 8 states using different variable metrics 1. Idle with Grain Tank not Full 2. Idle with Grain Tank Full 3. Unloading Not Harvesting 4. Harvesting and Unloading 5. Harvesting 6. Headland Turn Separator Engaged 7. Field Transport 8. Road Transport

6 Machine States

7 Data Analysis GPS data Unproductive time Traveling to and within fields Stopped and unloading Machine adjustments, maintenance and repair time Turning and crossing waterways time Idling Productive time carrying out harvest operations

8 Monitoring Productivity Viewing a farm as a manufacturing floor and applying lean manufacturing concepts to reduce machine travel time and stoppages In lean environment want to eliminate waste, reduce time, reduce waste, while improving overall quality of product Travel time is about 14% of this farm s harvesting hours

9 Monitoring Productivity Using our metrics for each operating state we can evaluate machine efficiency In lean manufacturing concept 100% efficient is perfect but not obtainable 85% efficient is exceptional 60% efficient is average 40% efficient is low

10 Reducing Inefficiencies What can be changed to reduce unproductive time? Biggest increase to productivity will come from optimizing fleet size (number of combines, semi trucks, grain carts working together) Dependent on amount of laborers available Being able to unload on the go rather than unloading stationary at the truck Distance to grain storage site

11 Reducing Inefficiencies Limiting the amount of idle time on all machines Data analysis showed most machines idling 25 to 30% of the total hours Also need to consider logistics of traveling from field to field Have a planned order in which each field will be completed (cannot always be followed due to weather and other unforeseen variables)

12 Future Goals To be able to break down productivity by operator and create operator benchmarks Measuring productivity in terms of acres covered per hour and grain throughput per hour Also taking into consideration the quality of operation (no skips, grain lost over time, grain quality)

13 Conclusions Think about the size of your fleet of vehicles and if it sufficient to maintain productivity with minimal stops Have a plan to follow but deviate as needed due to weather/field conditions

14 Thank You Questions or Comments