bear basin in the gallatin mountain range. montana: measurement uncertainty lab accreditation...
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MONTANA: MEASUREMENT UNCERTAINTY
Lab Accreditation Meeting San Diego, March 12th
MT Department of Agriculture Lab• Analytical Chemistry Lab
• 8.625 FTE
• Montana State University
• Bozeman, MT
• ~2,500 samples per year
MT Department of Agriculture Lab
• ~1/2 Feed /Fertilizer samples
• ~1/2 Pesticide samples
• ISO 17025 Accreditation November 2014
• 2 Feed, 1 Fertilizer Method
• 0.5 FTE QAO position
Outline
• What is Measurement Uncertainty (MU) ?
• ISO Requirements for MU
• MT Approach to MU-how we did it!
What is Measurement Uncertainty (MU)?
• Uncertainty associated with measurements
• Doubt about the result of any measurement
• Defines possible range/spread of results
• Tells something about the quality
What is Measurement Uncertainty ?
• Variation in results when they are repeated
• May be due to natural variations
• Take a number of readings
• Average to get to “true” value
What is Measurement Uncertainty ?
• How widely spread are the values
• Standard deviation-quantify spread
• Judge quality of measurement from the spread
• %RSD: Relative Standard Deviation
• %RSD=Divide STDDEV by AVER and X 100
ISO MU Requirements
• Reporting does not give wrong impression
• Result incomplete without a statement of uncertainty
• Needs to be understandable and relevant to the user
• REQUIRED: Procedure to estimate uncertainty
ISO MU Requirements
• Need to look at MU mathematically
• Need to put a number to the uncertainty
• You do not have to hire a statistician
• Reasonable estimation based on method
MT Approach
• Sent Staff to MU training
• Become familiar with basic steps
• Become familiar with uncertainty language
• Goal: Reasonable Estimation
• Use a practical user friendly approach
MT Approach• Established rules for calculating uncertainty
• Follow conventional methods
• Express uncertainty as consistently as possible
• Express uncertainty values properly
• Others need to understand what we have done
MT Approach• 1: Identify Approach
• 2: Identify sources of uncertainty
• 3: Estimate size of uncertainty from each source=%RSD
• 4: Combine individual uncertainties =overall figure
• 5: Expand Uncertainty
• 6: Create Uncertainty Budget
Identify Approach• Two approaches to estimating uncertainty
• Type A: use statistics from repeated findings
• Type B: Non states, other means
• Use Type A—why?
• A2LA classifies test methods for determining MU
• Method based on published consensus methods
Type A
• Use Laboratory Control sample (LCS)
• Appropriate matrix and concentration
• LCS has been through all method steps
• Apply Statistics to estimate MU
MT Approach• Lasolacid Method MU
SAMPNO RESULT MATRIX COLDATEAB10717 26.93 Feed 21-Mar-11AB10403 28.11 Feed 22-Feb-11AB10165 27.50 Feed 20-Jan-11AB10047 27.75 Feed 06-Jan-11AB04245 30.43 Feed 10-Dec-10AB04026 27.16 Feed 18-Nov-10AB01036 31.54 Feed 08-Apr-10AB00554 29.30 Feed 24-Feb-10AB00159 29.59 Feed 21-Jan-10AB00090 28.54 Feed 13-Jan-10AB00036 26.44 Feed 06-Jan-10AA93899 31.65 Feed 03-Dec-09AA93890 30.90 Feed 02-Dec-09AA93652 30.42 Feed 09-Nov-09AA90612 27.81 Feed 06-Mar-09AA90468 28.43 Feed 19-Feb-09AA90437 27.91 Feed 13-Feb-09AA84116 28.01 Feed 17-Dec-08AA83899 28.97 Feed 26-Nov-08AA83773 29.68 Feed 18-Nov-08AA83741 30.33 Feed 14-Nov-08
x (g/T)= 28.92SD(g/T)= 1.527
MT Example• 21 data points from AAFCO
• Collected over 3 years
• (g/T) = 28.92
• SD (g/T) = 1.527
• RSD (%) = 5.280
• MU= 5.28%
Sample PREP MU EXAMPLE
• Design set of experiments
• 3 Different samples
• Each samples: mass reduction to 4 splits
• Each split: 3 instrument measurements
MT Approach• EXAMPLE
• Sample PREP MU
• Hypothetical data
• Repeat for 3 samples
• AVER SD splits 3 samples
• Calc: %RSD of AVER SD
• %RSD= MU Sample PREP
Sample 1 SD method
Split 1
25.00
22.00
23.00
AVER split 1 23.33 1.53
Split 2
19.00
19.00
16.00
AVER split 2 18.00 1.73
split 3
18.00
17.00
15.00
AVER split 3 16.67 1.53
AVER SD method 1.60
AVER splits 19.33
SD method/splits 3.53
AVER SD method 1.60
SD splits 1.93
%RSD 9.97
MU sample PREP EXAMPLE 9.97%
MT Approach
• Unfamiliar Concepts/Terms
•Combine Uncertainties
•Expand Uncertainty
•Uncertainty Budget
MT Example: Lasolacid• Add 2 uncertainties together
• MU Sample PREP: ~10 %• MU method: 5.28%
• Use root sum square method (RSS)
• UC =
• Uc = (~10.02 + 5.282)1/2 = 11.31
• Combined Uncertainties: 11.31%
Coverage factor K
• Numerical factor used as a multiplier
• To expand uncertainty
• Include more results at greater confidence
• Typically in the range 2 to 3
Degree of Freedom
• Degree of freedom: number of measurements - 1
• For >20 values, k = 2.0, degree of freedom = ∞
• Tabulated values of k shown below:
n -1 1 2 3 4 5 6 7 8 9 10
k(corr) 12.71
4.30 3.18 2.78 2.57 2.45 2.37 2.31 2.26 2.23
n -1 11 12 13 14 15 16 17 18 19 20
k(corr) 2.20 2.18 2.16 2.15 2.13 2.12 2.11 2.10 2.09 2.09
Lasalocid Measurement Uncertainty• The data from LCS AAFCO Lasalocid 2007-30 was used to
estimate MU• U1: Sample prep 21 data points • U2: Testing process 21 data points
• Uc = (~10.02 + 5.282)1/2 = 11.31
• U = (2.0 x 11.31) = 22.62
Symbol Source of UncertaintyValue (%)
Distrb Div Uncert (1σ)Degree Freedm
U1 Sample Preparation ~10.0 N 1 ~10.0 ∞
U2 Testing process 5.28 N 1 5.28 ∞Uc Combined Uncertainty 11.31 %
U Expanded Uncertainty (k=2.0) 22.62%
Summary of Determination
• Combined Uncertainty : 11.31%
• Expand Uncertainty: 11.31 X 2.0 = 22.62%
• Average: 28.92 g/T
• 22.62% of 28.92g/T= ± 6.54 g/T
• 95% confident result will be 22.38-35.46 g/T
• YAHOO!!
Conclusions
• Deriving measurement uncertainty is so doable
• Standard protocol for determining uncertainty
• This is NOT a stumbling block for accreditation
• Practical approach—usable and manageable
References
• International Standard, ISO/IEC 17025, Section 5.4 Test and calibration methods and method validation. Second edition 2005-05-15, Reference number ISO/IEC 17025:2005(E).
• Montana Department of Agriculture Quality Management System for ISO accredited methods
• A2LA Introduction to Measurement Uncertainty-Training Course 2013
• A Beginners guide to Uncertainty in Measurement , Stephanie Bell, NPL, Issue 2
MIDWEST AOAC meeting
• June 8-10th 2015
• Bozeman, MT
• SYMPOSIA:• Pesticides at work in the Agriculture LAB • State AG FEED LABS going ISO-Say what? • Veterinary Toxicology and Mycotoxins • NFTA technical presentations • Food Safety: Chemistry and Microbiology Applications • ICP workshop • LIMS issues
• SPECIAL EVENTS:• Vendor expo and presentations• Tuesday evening social: Mountain Chalet surrounded by snowcapped mountains• Casper-Helfe Memorial Golf Outing
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