CLUB of BOLOGNA€¦ · • Thesis work was carried out at Tampere University of Technology –...

Performance Monitoring and Operator Assistance Systems in Mobile Machines

CLUB of BOLOGNAGiuseppe Pellizzi PhD Prize 2012

23rd Annual Meeting of the Club of BolognaNovember 9, 2012

Lauri Palmroth – [email protected]


Presentation outline

1. Introduction2. Scope of Thesis3. Outcome of Thesis work


Introduction

• Thesis work was carried out at Tampere University of Technology

– Department of Automation Science and Engineering

• Research partner: John Deere Forestry– Tampere, Finland– Factory: Joensuu, Finland


John Deere ForestryCut-to-length forest harvesting1. CTL forest harvesting method is the most common in Europe

– Trees are processed to logs at felling site2. Two separate machines are used in the CTL method, harvester

and forwarder. – harvester is used for felling, delimbing and bucking (i.e. cutting the

trees into logs) of timber.– Once the harvester has processed the tree stems to logs, a forwarder

picks up the logs and carries them to the roadside for further transportation.

3. Role of the forest machine operator– Despite high level of automation, the task field of the operator is

broad and quite demanding. – The work of the operator requires both motor-sensory and cognitive

skills and knowledge and involves a lot of planning and decision making tasks


Cut-to-length forest harvestingHarvester and forwarder

Harvester

forwarder


Scope of thesis

”Increase the productivity and fuel efficiency in mechanized forestry”

1. Machine performance evaluation– Evaluate technical condition of the machine

2. Modeling of man-machine process– Interpret operators actions

3. Human performance evaluation– Evaluate operators actions

4. Operator assistance by decision support and coaching– Help the operator


Scope of thesis1. Machine performance evaluation

• The performance of the man-machine system is affected by

– Technical machine performance

– Operator’s skills, work techniques

– Varying operating conditions• Machine performance

evaluation– Performance indices based on

measurements from CAN busof the machine

– Follow-up of trends of technicalperformance in varyingoperating conditions


Scope of thesis2. Modeling of man-machine process

• Modeling the operators work– task network model

• Recognition of work tasks– Some work tasks can be directly recognized from the

measurements– How to recognize the work tasks that are not directly

observable?


Scope of thesis2. Modeling of man-machine process• Recognition of work tasks

that are not directlyobservable using HiddenMarkov Models

– Recognition of work tasks and work cycles based on the combination of multivariate control signals generated by the operator

– Although single control signals look like arbitrary, the separate work tasks can be revealed based on underlying sequences of combined control commands


Scope of thesis2. Modeling of man-machine process

• Example use of work taskrecognition:

– Distribution of work time in different worktasks


Scope of thesis3. Human performance evaluation

• Performance evaluationof the operator is basedon work task recognitionand task levelmeasurements

– Evaluation of operator ’s skill

– Evaluation of operator’swork tehcniques and methods



• Example of performanceevaluation:

– Distribution of operator’s workingtime using differentwork techniques



• How good the measuredperformance is?

• Statistical evaluation of measurements

– Benchmark performance– Reveal the potential of

improvement• Allows comparison of

different measurements– Significance


Scope of thesis4. Operator assistance by decision support and coachingHelp the operator by1. Measurements of the operator’s

work2. Associate measurements to work

task level– Requires work task recognition

3. Evaluate operator’s measurements– Requires statistical reference

material, benchmark performance4. Make observations and give

suggestions– Linuistic feedback


Scope of thesis4. Operator assistance by decision support and coaching• Expert system based

on fuzzy similaritymeasures

• Shows observationsand gives suggestionsto the operator

– According to the rulewhich has the highestsimilarity withoperator’smeasurements

– Sorts the suggestionsin order of significance


Outcome of Thesis workForestry in general

1. Use of automatic measurements in forestry education

– Training with simulators & real machines– Specific excercises with measurement feedback

2. Engineering purposes– Measurements of how JDF machines are used

worldwide – Machine development


John Deere ForestryOperator performance report/analysis


Machine tuning & operator training

• Machine tuning and operator training pilot projectsby John Deere instructors

– Aim for productivity and fuel economy improvement in the customer machines by 1) Machine tuning 2) Improving operators’ working methods

– Operator well-being at work is important• Machine data analysis

– Tuning of machine settings• Operator data analysis

– Review of operator performance analysis/report, together with instructor

– Follow-up of the results


Machine tuning & operator training example of results

Before:

After:- 3,9s (8%)

improvement


Machine tuning & operator training example of resultsBefore: After:


Machine tuning & operator trainingexample of resultsBefore: After:


John Deere worldwideForestry / Construction / Agriculture

• On-board analysis of machine data– Optimization of

machine control parameters

– Machine efficiency– Show optimization

potential for customer• Utilize machine data for

engineering purposes


Thank you!

CLUB of BOLOGNA€¦ · • Thesis work was carried out at Tampere University of Technology –...

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