Visions of The Virtual Slaughterhouse

Søren G. Erbou

Ph.D. studentInformatics and Mathematical Modelling Technical University of DenmarkDanish Meat Research Institutesge@imm.dtu.dk

22 May 2007 Søren G. Erbou – Industrial Visionday 2

Outline

• What is the The Virtual Slaughterhouse?• Where are we now?• Visions for the future• Means• Applications• Summary

22 May 2007 Søren G. Erbou – Industrial Visionday 3

The Virtual Slaughterhouse

• Part of the Danish Meat Research Institute (Roskilde, 1954)• Owned by the Danish pig producers via the Danish Meat

Association

• Mission of DMRI• Leading knowledge centre within meat and slaughter technology

• The Virtual Slaughterhouse (2006-08)• 3D-models of pig carcasses and tools for analysing the models• Collaboration with IMM, University of Århus and Visiana• Own CT-scanner • 4 phd-students

• Why?

22 May 2007 Søren G. Erbou – Industrial Visionday 4

Where are we now?

• Pig slaughter automation programme (1998->)• >30 development projects, >40 mill. €• Improved working environment, hygiene and safety

• Examples

Cleaning of throat- and heart regions

Removal of inner bones from front part

22 May 2007 Søren G. Erbou – Industrial Visionday 5

Where are we now?

• Highly automated production• Need for better quality control• Reverse problem in the production

• Normal: Many small parts assembled into one final product• Reverse: Same input ”disassembled” into many products

• Large variability of input• Products restrict each other• Minimise variability on output and maximise profit

• New methods for production planning• Operations research

• Define new input features

22 May 2007 Søren G. Erbou – Industrial Visionday 6

Visions for the future

• Where do we want to be in 10 years?• More adaptable production• Better suited for niche production• Less variability in quality of the final products• Handle large variability of input• Keep the leading technological position worldwide

22 May 2007 Søren G. Erbou – Industrial Visionday 7

Means

• Modelling the biological variability• Modelling specific cuttings• New predictors of quality based on models• Optimise the cutting of each carcass separately

• Introducing the CT-technology to the slaughterhouse industry

• Image analysis is the key for extracting only the necessary information

22 May 2007 Søren G. Erbou – Industrial Visionday 8

Online CT

• Adapt cutting to each specific carcass• Unlimited amount of information available at an early

stage along the slaughterline• Extract useful information• Define predictors for quality• Speed and cost is crucial• Minimise data acquisition while maximising useful

information

22 May 2007 Søren G. Erbou – Industrial Visionday 9

Applications

• Trimming of the fat layer on the loin or neck muscle• The same fat thickness all over the loin gives the best

price• Small thickness is better• Important not to expose the muscle

• CT can give additional information• Model the fat layer• Fit the model to new carcasses

(University of Nebraska, Lincoln)

22 May 2007 Søren G. Erbou – Industrial Visionday 10

Applications

• Use models for developing robotic tools

• 40 carcasses CT-scanned• 3D statistical shape model

of bone structures in the ham.

• 7 model parameters describe 69% of the variation

• Parameters are localised to ease interpretation

22 May 2007 Søren G. Erbou – Industrial Visionday 11

Even more applications…

• Segmentation of muscles• Cutting and quality estimation of pig backs

• Pig atlas• Volume registration• Apply cuts in atlas and propagate to population

• Virtual dissection• Voxelwise classification• Better quality measure

• Many more to come…

22 May 2007 Søren G. Erbou – Industrial Visionday 12

Summary

• Obtaining and analysing 3D-models of pig carcasses• Introducing CT in the slaughterhouses• Image analysis and statistics are key elements• Predictors for quality• From models to robotic tools• Better suited for niche products• Production more adaptable• Quality control is crucial

22 May 2007 Søren G. Erbou – Industrial Visionday 13

Aknowledgements

DMRI:Eli V. Olsen Lars B. ChristensenClaus Borggård

IMM-DTU:Martin Vester-ChristensenMads F. HansenPeter S. JørgensenAllan LyckegaardRasmus LarsenBjarne K. Ersbøll,

Thank you for your attention…