Can Process Analytical Technology Lead to Real-time Quality Management for Dairy Food Products?

Can Process Analytical Technology Lead to Real-time Quality Management

for Dairy Food Products?

Brent Young*, Nick Depree, Taj Munir and David Wilson

*[email protected]

FarmingProcessing & Supply

ChainIngredients & Dairy

SolutionsConsumer Products

Innovation to Transform the Dairy Value Chain

Dairy Primary Growth Partnership Programme

The Nature of Dairy/Food Materials

• Biological sources of variation• Highly perishable• Properties are time dependent• Properties are often not well characterised

Presents considerable challenges – to process design, control and optimisation systems – to sustainably produce safe, consistent and

economically viable products






Traditional Real-time Process Control Solutions

State of the art:

Stainless steel & PLCs – Temperature,

pressure and flow instrumentation

– Uni-variate monitoring– Manual control

common– Minimal optimisation






Challenge: We have real-time process control for some variables. But what about real-time quality (RTQ) control!?

What is RTQ? Is it PAT?

PAT Definition:

Process Analytical Technology* involves the systems approach in the planning, design, control and optimization of processing plants.

This is a model based framework that encompasses new enabling technologies for most areas of the processing industry.

* US Department of Health and Human Services, Process Analytical Technology, FDA, 2004

Challenge: Is PAT simply an evolution of what we have done all along?






What is RTQ? Is it PAT?1. Process analysers

– Fusion of models and latest sensors for better monitoring

2. Design, data acquisition and analysis tools– Multivariate models for deeper process analysis

3. Process control tools– Targeted models for optimisation– Mini models for exception detection

4. Continuous improvement and knowledge management tools– Holistic approach that integrates methodologies– Driven by the customer & regulatory authorities






What is RTQ? Is it PSE?

Fonterra Te Rapa Process PlantTA Instruments ARG2 Rheometer University Dairy Viscosity Testing Rig






Tools: Simulators Pinch Tech Soft Sensing Smart SensorsSteam MPC*

Multivariate SCM** PAT Tools

Model DAEs Objects Large Scale Data DrivenTypes: Codes Exception Based






* Model Predictive Control** Supply Chain Management

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What is RTQ? Is it PSE?

RTQ: A refocus for our aims






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I’m happy with my equipment,

but how do I save energy & operating costs?

Primarily interested in equipment design &

operation

What are my mass & energy balances?

Final QA found something amiss

What happened, where & how much product is

affected?

Challenge: Capturing a customer-centric view in a traditional engineering environment

Two Views

Challenge: Do we have two masters?






What are we doing?

• Multivariate Exception Based Modelling– Data Mining and Rectification– Sensitivity and Factor Analysis (e.g. MPCA)– Fault Detection and Diagnosis

• Models for control (e.g. MPC)– What are appropriate models?– What level of fidelity?

• Always maintain a Customer/Client focus






Challenge: Building something useful without full-scale dynamic modelling

How are we doing it?

Platform Technologies

Rapid PrototypingBuilding mini-models

R/MATLAB/Python(Tools within) Pavilion

Steady State & Dynamic Modelling

VMGSimMATLAB

Graphical User/Operator Interface Pavilion

Challenge: Building a flexible proto-typing environment,not getting bogged down producing commercial software.






Challenge: Reflective Visualisation – getting timely information to make informed decisions now & tomorrow.

Operator Displays

Visualisation






Is this the best we can do?

Basic Ideas

• Not a standard operator’s display– We already have those

• Data is graphical– Dense, big screens– A3 paper

• Focus on the future– What might happen & when – Future gets uncertain

• Consistent Colour design– Low impact






Careful design of charts – resolution, colour, aspect ratio:

Typical graphics layouts

Ref: Tufte’s The Visual Display of Quantitative Information






Advanced Visualisation






Sparklines – small, intense, word sized graphics. Placed inline with text, show flow and change of data

Fonterra Baseline Capability:






Colour Maps & HMI Design






Chart improvement – Clarity, Resolution, Data Density






Focus on the future






Design, Data Acquisition & Analysis Tools

• Data driven techniques– Data Mining & Rectification– Sensitivity & Factor

Analysis– PCA

– Fault Detection & Diagnosis – PCA & Discriminant Analysis

– Traceability – Bayesian Belief Networks,

Transfer Entropy

• Model based techniques– Process Simulation






Next steps…

• Focus on the future: Does it work?– Mini tools to tell you what will happen– Countdown

• Two screens: two types of information– Dashboards: (useful or naff?)– Super big screens, or multiple screens? – Always visible? Build your own?

• Getting away from trends & PFDs:– Moving “blobs”






This mini tool warns against blockage of the SFB – increasing T between 2 probes indicates poor flow or sticky powder

This right hand plot shows a zoom into small detailed region using the mini-tool






A mini tool looking at stability of feed solids to drier

Example stable for most of cypher but sudden change at endReal version is interactive version






Vitamin D Dosing Mini Tool

With over dosing (right)

Without (below)






Coffee Sediments SQC

Coffee sediments scores plot (right)

N.B. colours are start/middle/end of run

How to display in real time for operators?

-> ‘Snakes on a Plane’ planned! (e.g. below)






Acknowledgments

I2C2•Drs Irina Boiarkine & Ville Rimpilainen (UOA)•Arrian Prince-Pike (AUT)

Fonterra•Advanced Process Control Group, Drs Tristan Hunter & Nigel Russell (Fonterra)

Primary Growth Partnership Program (PGP)






Can Process Analytical Technology Lead to Real-time Quality Management

for Dairy Food Products?

Brent Young*, Nick Depree, Taj Munir and David Wilson

*[email protected]






We never said we were statisticians.






Can Process Analytical Technology Lead to Real-time Quality Management for Dairy Food Products?

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