Theory of Sampling (TOS) –the missing link in chemical analysis,

process monitoring & quality control (PAT)

Kim H. EsbensenACABS: Applied Chemometrics, Analytical Chemistry,

Applied Biotechnology, Bioenergy & Sampling research group, University of Aalborg Esbjerg (AAUE)

Denmark

- ”samples” for analysis …

- usually treated identically

- ABSOLUTELY not identical !!!

- matrix is different –

- internal compositional

heterogeneity: CHS

”population thinking …”

A traditional view of analyticalchemistry: samples in the lab.

And neither was the lot … … …

from where all were sampled …

- all ”units” are identical

Heterogeneity at different scales !

- very high CHL

- high CHL

Primary stage ”representative sampling” … ?- External (spatial) heterogeneity -

Apparently a homogenous lot … …

Sneak preview of coming horrors …

- very low CHL

Grab sampling … there is nothing worse !

- state-of-the-art NIR monitoring !

- state-of-the-art pipe-line sampling ?

- severely TOS-incorrect !

By-pass: - ”practical solution”

- examples from NIR-monitored processes

- grab-sampling for at-line NIR

- structurally incorrect primary sampling (TOS)

Process Analytical Technologies (PAT)

PAT - a system for design, analysis and control of manufacturing …

- a system for designing, analyzing, and controlling manufacturing through timely measurements (i.e., during processing) of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality

- it is important to note that the term analytical in PAT is viewed broadly toinclude chemical, physical, microbiological, mathematical, and risk analysis conducted in an integrated manner … (? role of representative sampling ?)

The current context for analytical chemistry...

Process Analytical Technology (PAT): (tools)

There are many current and new tools available that enable scientific, risk-managed (pharmaceutical) development, manufacture, quality assurance. These tools….. when used within a system can provide effective and efficient means for acquiring information to facilitate process understanding, develop risk-mitigation strategies, achieve continuous improvement, and share information and knowledge.

In this framework, PAT tools can be categorized as:

* Multivariate data acquisition and analysis tools * Modern process analyzers or process analytical chemistry tools* Process and endpoint monitoring and control tools * Continuous improvement and knowledge management tools

An appropriate combination of some, or all, of these tools may be applicable to a single-unit operation, or to an entire manufacturing process and its quality assurance.

Process Analytical Technology: PAT – Process Understanding

A process is well understood when:

* ALL CRITICAL sources of variability are identified and understood* VARIABILITY is managed by the process * Product quality attributes can be accurately and reliably PREDICTED

Although TOS has been known for > 50 years- very little appreciated and/or implemented in:

- PAC: Process Analytical Chemistry- PAT: Process Analytical Technologies

- QC: Quality Control- or in the analytical laboratory (sic)

This despite the fact that sampling errors form the dominant part of what is erroneously termed "measurement errors” –

sampling errors reach 50-100+ * the analytical error s.s.

Critical issues:Samples are but a portion of original material, a source ... ... a lot

Samples usually originate from heterogeneous material ... ...

Samples are mandated to be representative of the lot ...

Critical issue - How to draw a representative sample for all lot types ?

General principles: Theory of Sampling (TOS)

PRINCIPLES of REPRESENTATIVE SAMPLING + analysis

- - Sampling is NOT ”a simple materials handling” operation

- - Sampling is a 50+ year old theory (TOS)

Focus is ”naturally” on sample size: MS

Taking the primary sample ….

- is not when to decide on: MS !!

- Different materials are of different

intrinsic heterogeneities .… .…

TOS’ first surprise: - a paradox:

- Focus is ”naturally” on sample size: MS

- very difficult to avoid conventional

statistical population thinking … …

TOS is different !!!

”True” lot concentration … aLOT ?

”Heterogeneity” does not follow ANY statistical distributions !!

- A few necessary definitions:

- let’s begin here … …

- TOS

50 ppm - showcase

”True” lot concentration – aLOT ??

50 ppm100 ppm - showcase

”True” lot concentration – aLOT ??

50 ppm100 ppm 500 ppm - showcase

”True” lot concentration – aLOT ??

50 ppm100 ppm500 ppm500 ppm – realistic lot distribution

Reality is a harsh mistress … … …

50 ppm100 ppm 500 ppm - showcase1000 ppm – realistic lot distribution

Reality is a harsh mistress … … …

50 ppm100 ppm 500 ppm - showcase1000 ppm – real distribution5000 ppm – realistic lot distribution

Reality is a harsh mistress … … …

50 ppm100 ppm 500 ppm - showcase1000 ppm – real distribution5000 ppm – real lot distribution10.000 ppm (1%) – realistic lot distribution

- trace concentration: below 1% … …

N.B. - note sample size MS vs. lot size ML

Heterogeneity- as a function of:• concentration• spatial distribution• constitutional dist.

• sampling tool size• sampling process• sample handling &

preparation

material (lot)characteristics

sampling processcharacteristics

- only a partial, idealistic model

- Real life: significant to extreme heterogeneity !!!

Is this, then, the company’s

most highly trained personel?

- TOS: the lot … …

Sampling is closely related to thenature (form, material) of the lot

It is necessary to discriminatebetween the ”effectivedimensionality” of the lot to besampled …

- Historical document #4

n.b.

which means

- worst of all …NOT regarding PAT !!!!!!

- sampling is ALWAYS:

n.b. different sampling rate

1. Primary sampling

2. Secondary sampling

3. Tertiary sampling

4. ( … rare, but … )

5. ( sample preparation )

6. Analysis

a multi-staged process …

First step solutions .....

The possibilities for successfulsampling is closely related to thenature (form, material) of the lot

Lot transformation …

TOS – synopsis:

- error systematics

- three sources !!!

1

2

– Mixing / blending– Particle Size Reduction (comminution)

– Composite Sampling– Representative Mass Reduction

• The ultimate summary of TOS• 3 principles and 4 practical procedures

– Heterogeneity Characterization– Variography (1-D ditto)– Lot Dimensionality Reduction

Seven Sampling Unit Operations

Normally used once in planning / optimization of a sampling process

Used as active steps in the sampling process (often used several times)

- archetype grab-sampling

- very often used: grab-samplingGrab sampling is NEVER acceptable

Conventional ”process sampling” … …

NB: This is also grab sampling!

ARCHETYPE grab sampling

- - - - - - - - - of reactors ....

Grab sampling – Hall of Shame

15 industrial process lots: 1D, 3D

All assumed to be homogeneous!

Care to take a grab sample .. .. ..

Anyone ?

… even in laboratory life …

$ 64.000 question: homogeneous? - not at all – very heterogeneous!

- the world’s worst sampling method

Brief introduction to process sampling … - ”easy”: relatively

homogeneous stuff(s) …

Server

What’s the situation regarding process sampling (1D lots) ?

Instrumental signals & reference samples ..

Pipeline sampling or conveyor belt ….

Server

- issue: HETEROGENEITY (…. gravity & flow segregation ….)

Multivariate Calibration (PLS-R)

Chemometric Data Analysis - -

Solve this problem ??

Not a chance, unfortunately !

Many instrumental analytical methods (X) are based on"analysis by proxy” - for which the representativity of

reference data (Y) is critical w.r.t. underlyingmultivariate calibrations

(X,Y) must both be representative– these are different issues …

NOT a data analysis issue (sorry!)

Representative sampling: critical success factor

TOS: a missing link in much of current process analysis

Quick overview of 99 %-ile of conventional ”process sampling designs”

All these designs are incorrect – sampling process is non-representative !!!

- Physical sampling, or sensor probe localisation

There is no way out of the need for understanding theprinciples and practise involved for producing representative

reference sampling

The situation can not be remedied by neither statistics, chemometric data analysis, nor by any other type of

a posteori "corrections"

TOS requirements:

Introduction to the Theory of Sampling (TOS): A practical framework of 7 sampling unit operations (SUO),

with which to approach all types of sampling in the field, in the production plant, in industry or in the laboratory

– Mixing / blending– Particle Size Reduction– Composite Sampling– Representative Mass Reduction

• The ultimate summary of TOS• 3 principles and 4 practical procedures

– Heterogeneity Characterization– Variography (1-D ditto)– Lot Dimensionality Reduction

Seven Sampling Unit Operations

Normally used once in planning / optimization of a sampling process

Used as active steps in the sampling process (often used several times)

SEVEN SAMPLING UNIT OPERATIONS – a toolbox for practical representative sampling

Kim H. Esbensen & Lars Petersen

Aalborg University Esbjerg, Denmark, www.acabs.dk

ACABS: Theory of Sampling (TOS): course documentation (2006)

www.acabs.dk

- ONLY TOS-correct & practical pipeline sampling configuration …

- a necessary condition for:

- a representative sample …

A quasi-acceptable ”solution” … based solely on existing technology

UPWARD flow only !!!

- composite sampling of (very) heterogeneous pipeline flux

- sampling 8 segments of pipeline flow (10L) + frac. shovel.

… followed by compositing (8L) + fractional shoveling

REPRESENTATIVE PRIMARY SAMPLING (problem-dependent)

primary process sampling: a master example

- not exactly realised by grab-sampling !!!

- sneak preview of coming attractions … (ACABS)

- conventionalprocess sampling

-TOS-incorrect:

- non-representative

- recurrent loop sampling- co-located with PAT modalities

- state-of-the-art NIR monitoring !

- Let’s play along – to learn a new chemometric issue

By-pass: - ”practical solution”

- typical result: significant TSE (not necessary)

- bad sampling – not an ”instrument problem”

- bad sampling – not a ”measurement problem”

- typical result: uncomfortable ”measurement errors”

TSE = PSE + SSE + TSE + TAE + IPE … …

- bad X-sampling

- VERY LARGE Y-sampling errors …

- or bad Y-sampling

- reference sampling

- but luckily, bad sampling is not always the case …..

- not always – how much are YOU willing to gamble ???

”SAMPLING – is not gambling!”

”TOS-sampling is not relevant for my:

- lot (material)

- process

- samples … … ”

???

- attributed to Pierre Gy

Still – after all this TOS talk ….

- Useless process sampling: grab sampling …

Often met with (unfortunately):

I don’t need/want/understand all this TOS [crap]:

It is a reasonable assumption that the flow is homogeneous ….

A minute analytical quantity is enough for the analyzer …..

Taking many sensor recording (e.g. 20 /sec.) will ensure representativity….

How NOT to install a probe

N.B. Generic illustration !!

Similarity with any existingtechnologies is purelyaccidental & NOT intended

Peekaboo, through a window

A memorable review ….(leading chemometrics journal …)

- by a certain irate reviewer, ”who shall still remain undisclosed” – after all...

”This aproach does not correspond to what we* mean by sampling …..”

Let’s hope he can define ”his” sampling ...

* chemometricians …..

- in as broad and comprehensive

fashion as Theory of Sampling (TOS)

- THEORY of SAMPLING (TOS)

how?• how would YOU do this?• HOW could you do this?

• sampling is necessary -• not just materials handling

• TOS: Theory of Sampling

Pierre Gy: founder of TOS

Cannes, June 8.th, 2005

First World Conference on Sampling and Blending, Aug. 2003, Esbjerg

Pierre Maurice Gy

b. Paris, July 25, 1924

Chem. Eng. Paris Sch. Phys. & Chem. (46)

Ph.D. physics. Univ. Nancy (1960)

Ph.D. Math. (stat). Univ. Nancy (1975)

Gold medal (Soc. l’industri Minerale) (63,76)

Lavoisier Medal (Fr. soc. Chemistry) (1995)

… 9 books, 175 papers, 200 lectures …

REPRESENTATIVE SAMPLING FOR RELIABLE DATA ANALYSIS: Theory of Sampling (TOS)

Lars Petersen, Pentti Minkkinen*, Kim H. Esbensen

Aalborg University Esbjerg, Denmark, www.acabs.dk*) Lappeenranta University of Technology, Finland, www.lut.fi

Chemometrics and Intelligent Laboratory Systems, vol. 77 (2005) 261-277

www.acabs.dk

REPRESENTATIVE PROCESS SAMPLING for reliable data analysis

Lars Petersen & Kim H. Esbensen

Aalborg University Esbjerg, Denmark, www.acabs.dk

Journal of Chemometrics (2006), in print

www.acabs.dk

Representative Process sampling in practice – a tutorial:variographic analysis and estimation of Total Sampling Errors (TSE)

*Kim H. Esbensen, Hans Henrik Friis-Petersen, Lars Petersen, Jens Bo Holm-Nielsen & Peter P. Mortensen

ACABS, Aalborg University Esbjerg, Denmark

www.acabs.dk