Operator performance report generation

• US 9,892,376 B2
• Filed: 01/14/2014
• Issued: 02/13/2018
• Est. Priority Date: 01/14/2014
• Status: Active Grant

• Current Assignee: Deere & Company
• Original Assignee: Deere & Company
• Inventors: Pfeiffer, Dohn W., Blank, Sebastian
• Primary Examiner(s): Choy, Pan G
• Application Number:
  US14/155,023
• Publication Number:
  US 20150199637A1
• Time in Patent Office: 1,491 Days
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 50/02 Agriculture; Fishing; Forestry; Mining

Abstract

A set of data indicative of sensed parameters on an agricultural machine is evaluated against a reference data set to obtain an evaluation value indicative of how the set of data compares to the reference data. A performance score is generated based on the evaluation value and indicates a performance of a given operator in operating the agricultural machine. An operator performance report is generated based on the performance score.

Claims

1. A computer-implemented method, comprising:

sensing a grain productivity of an agricultural machine, using a grain productivity sensor, and generating a grain productivity signal indicative of the sensed grain productivity while a given operator is operating the agricultural machine;

sensing a fuel consumption of the agricultural machine, using a fuel consumption sensor, and generating a fuel consumption signal indicative of the sensed fuel consumption;

sensing a machine state of the agricultural machine, using a machine state sensor, and generating a machine state signal indicative of the sensed machine state;

sensing a vehicle speed of the agricultural machine, using a vehicle speed sensor, and generating a vehicle speed signal indicative of the sensed vehicle speed;

communicating with each sensor, by a processor, to receive the grain productivity signal, the fuel consumption signal, the machine state signal and the vehicle speed signal;

calculating, by the processor, a fuel efficiency ratio and a non-productive fuel efficiency ratio, and wherein the fuel efficiency ratio and the non-productive fuel efficiency ratio are configured to be broken into discrete timeframes upon being calculated;

controlling, by the processor, an average distance component to generate an output based on the fuel efficiency ratio, the non-productive fuel efficiency ratio, in the discrete time frames, and received inputs from reference functions;

controlling, by the processor, a fuzzy logic controller to evaluate a comparison of the output from the average distance component to reference data, and, based on the evaluation, generate a value indicative of a fuel efficiency performance of the given operator;

controlling by the processor, a fuel efficiency metric generator to generate a fuel economy pillar score based on the value of the fuel efficiency performance for the given operator;

generating by the processor, an interactive operator performance output based on the fuel economy pillar score;

controlling, by the processor, a viewer component to display the interactive operator performance output for user interaction;

generating, by the processor in real-time, closed loop control data to be fed back to the agricultural machine based on the fuel economy pillar score; and

performing automated control of the agricultural machine by automatically adjusting the controls of the agricultural machine in order improve the overall performance based on the generated control data.

2. The computer-implemented method of claim 1 wherein controlling the fuzzy logic controller to evaluate the comparison comprises:

evaluating the comparison of the output from the average distance component to historical reference data for the given operator.

3. The computer-implemented method of claim 1 wherein the given operator works for an organization and wherein controlling the fuzzy logic controller to evaluate the comparison comprises:

evaluating the comparison of the output from the average distance component to historical reference data for other operators in the organization.

4. The computer-implemented method of claim 1 wherein controlling the fuzzy logic controller to evaluate the comparison comprises:

evaluating the comparison of the output from the average distance component to historical reference data for other operators that have a threshold performance score.

5. The computer-implemented method of claim 1 wherein controlling the fuzzy logic controller to generate the value comprises:

classifying the value into one of a plurality of performance classes based on how the output from the average distance component compares to the reference data.

6. The computer-implemented method of claim 1 and further comprising:

generating operator recommendations based on the generated value indicative of the performance of the given operator in regards to fuel efficiency.

7. The computer-implemented method of claim 1 wherein generating the operator performance report comprises:

generating the report with an operator identifier section identifying the given operator, a performance score overview section displaying a plurality of different performance scores, and a plurality of performance score detail sections each displaying detailed information for a corresponding performance score displayed in the performance score overview section.

11. The computer-implemented method of claim 1 wherein the processor comprises a set of a plurality of different processors and wherein receiving, at a processor, comprises, receiving at a processor in the set of processors, and wherein the step of controlling an average distance component comprises controlling the average distance component with one of the sets of processors.

12. The computer-implemented method of claim 11 wherein controlling the fuzzy logic component comprises controlling the fuzzy logic component with one of the set of processors.

13. The computer-implemented method of claim 11 wherein controlling a fuel efficiency metric generator comprises controlling the fuel efficiency metric generator with one of the set of processors.

8. A computer system, comprising:

a grain productivity sensor configured to sense a grain productivity of an agricultural machine;

a fuel consumption sensor configured to sense a fuel consumption of the agricultural machine;

a machine state sensor configured to sense a machine state of the agricultural machine;

a vehicle speed sensor configured to sense a vehicle speed of the agricultural machine;

a processor configured to communicate with each sensor by receiving signals of the grain productivity, the fuel consumption, the machine state and a vehicle speed;

the processor configured to calculate a fuel efficiency ratio and a non-productive fuel efficiency ratio based on the grain productivity, fuel consumption, machine state and vehicle speed of the agricultural machine, wherein the fuel efficiency ratio and the non-productive fuel efficiency ratio are configured to be broken into discrete timeframes upon being calculated;

the processor configured to cause an average distance component configured to generate an output based on the fuel efficiency ratio, the non-productive fuel efficiency ratio and received inputs from reference functions;

the processor configured to cause a fuzzy logic controller configured to evaluate a comparison of the output of the average distance component to reference data, and, based on the evaluation, generate a value indicative of a performance of the given operator in regards to fuel efficiency;

the processor configured to cause a fuel efficiency metric generator configured to receive the value from the fuzzy logic controller and generate a fuel economy pillar score based on the value;

the processor configured to generate an interactive operator performance output based on the fuel economy pillar score;

the processor configured to control a viewer component to display the interactive operator performance output for user interaction;

the processor configured to generate closed loop control data to be fed back to the agricultural machine based on the fuel economy pillar score, to adjust controls of the agricultural machine in order improve the overall performance based on the generated control data.

9. The computer system of claim 8, further comprising:

a pillar score aggregation layer configured to receive the fuel economy pillar score along with other performance scores and generate a composite score for the given operator.

10. The computer system of claim 9, wherein the pillar score aggregation layer is further configured to generate closed loop, real time control data configured to be provided back to the agricultural machine.