Transcript WORKPLACE EXPOSURE ASSESSMENT AND FIELD …

UNIVERSITY OF HOUSTON - CLEAR
LAKE
2015
Quality product (or service) as one that is
free of defects and performs those
functions for which it was designed and
constructed
and
produces
Client
satisfaction. (Juran)
Quality Control: System of activities
whose purpose is to control the quality of
a product or service so that it meets the
needs of users. (Taylor)
An additional QC system implemented to
assess the efficacy of the QC system
monitoring the product.
This control
system is referred to as a QA program.
Thus, quality assurance could be defined
as quality control on quality control.
Defines mission, goals, and values of
organization.
Also provides: financial
systems, HR, and administrative functions.
The quality management system provides
policies, procedures, and organization that
defines the quality assurance programs
and how they interact with and are
supported by the overall management
system.
Elements:
- Organization
- Management System
- Document Control
- Review of Requests/Tenders/Contracts
- Subcontracting
- Service to Customer
- Purchasing
Elements:
- Control of Nonconformance
- Complaints
- Improvement
- Corrective Action
- Preventive Action
- Control of Records
- Internal Audits
- Management Reviews and Reports
Topics:
- Selection and Training of Personnel
- Selection of Methods
- Estimation of Uncertainty
- Control of Data
- Equipment and Instrumentation
- Traceability
Topics:
- Sampling
- Handling of Test Items
- Quality Assurance of Results
- Reporting of Results
Issues scaled and adjusted to organization
size and scope of processes involved.
Purpose of quality is to provide a level of
assurance that the result of a process will
meet specifications.
The terms: accuracy, bias, and precision
are terms often used to describe how close
a result is to the true or expected value.
“Accuracy is qualitative term referring to
whether there is agreement between a
measurement made on an object and its
true (target or reference) value”. [NIST]
“Quantitative
term
describing
the
difference between the average of
measurements made on the same object
and its true value”.
Bias is the difference between the average
of observed results and the true value, and
is determined over a period of time.
Quantitative measurement of normal distribution
of results due to random error in the system.
“Standard error” used to describe precision
measurements. The smaller the standard error,
the more precise are the measurements.
Precision is a measurement of the variability or
standard error observed between the average
value and the individual readings.
Measures of variability include statistics like the
range, variance, standard deviation, coefficient of
variation, and the standard error.
Measures of variability that are often used to
evaluate precision are:
range – maximum minus minimum;
sample variance – differences between
average of a series of measurement
and the individual measurements;
sample standard deviation – square
root of variance;
coefficient of variation – standard
deviation divided by the mean; and,
standard error – estimate of expected
error in sample estimate of population
mean or the sample SD divided by the
square root of size.
In order to draw conclusions about
airborne contaminant concentration, the
extent of current or future worker
exposure, efficacy of control measures,
samples must be properly collected and
analyzed.
Sample collection and analysis are interrelated, and both are critical components
of accurate data production. There must be
goals and objectives for each operation.
Caused by several factors:
- Training, attitude, and attention
- Representative !!! samples
- Environmental factors – T/%RH/BP;
sampling handling and transport;
contaminant concentrations assessed
- Sample collection factors – flow rate,
time, and collection efficiency
Rigid adherence to written sampling
methods can reduce inherent variability.
Materials must be consistent in quality and
use. Equipment and instruments used
must be appropriate for the procedures
employed.
Metrics for monitoring the sampling plan
is through use of samples that produce
results
that
provide
comparisons:
duplicate, split, spiked, and blank samples.
Control samples:
- Duplicate samples – evaluate method
- Split samples – e.g. bulk samples to
labs
- Spiked samples – most common; apply
known mass of contaminant on media
- Blank samples – field blanks; transport
blanks; and, media blanks.
Use of reference method – NIOSH/OSHA
Documentation of modifications, etc.
Validated methods.
Identify
variables
that
cannot
be
controlled.
Written sampling method/protocol –
equipment; sampling time intervals;
personal/area; handling and transport;
“blanks”; recordkeeping; decontamination
process; data check sequences; and
personnel training.
Testing of
programs
supplies
and
materials
–
Statistical sampling protocols
Labels – lot-specific Certificates of Analysis
Material QA/QC issues – sampling media
Lab/field blanks
QA
 Calibration
– “set of operations used to
determine the accuracy of the reading of a test
device to a stated uncertainty” [AIHA]
 Equipment calibration and recordkeeping
 Description of environmental conditions
 Realistic pre- and post-calibration intervals
 Written methodology for calibration
 Mechanisms used for establishing traceability of
calibration standards (i.e. NIST) or other
recognized organizations.
 Portable
instruments = laboratory function.
Purpose to provide immediate results
useful to help make decisions.
 Subject to many of same QA as laboratory.
 Users trained on equipment.
 Calibration before and after use; standard
and routine maintenance.
 QC samples for accuracy and precision on
a regular basis with appropriate data
analysis.
Formal recognition by a national or
international authority of capability of a lab
to perform testing and measurements.
Purpose to provide information that will
help make informed decisions regarding
laboratory selection. Demonstrates lab
competence and capabilities. (e.g. AIHA)
AIHA – voluntary program; ISO/IEC
Standard
17025;
inter-laboratory
proficiency programs, and other technical
requirements.
Normal distribution properties:
Symmetrical distribution in which the
mean, median, and the mode all have the
same value.
See: Figure 13.3
+/- 1 SD = 68%
+/- 2 SD = 95%
+/- 3 SD = 99.7%
For random samples of size n drawn from a
population with mean and SD, as n
increases:
mean of samples approaches
population mean;
SD of samples approaches SE of
mean;
shape of the distribution will
approach the normal.
Extend lines that segment the distribution
curves by standard deviation, then rotate
by 90 degrees to form a control chart.
See: Figure 13.4
mean +/- 3 sigma of average is UCL/LCL
mean +/- 2 sigma of average is UWL/LWL
Two general types in data-producing
systems:
- assignable (or determinate) causes is
systematic error (i.e. control chart data)
- unassignable (indeterminate) causes is
random error
Need two types of control charts – one to
deal with bias and another for precision.
Since bias is related to central tendency, a
common type of control chart for bias plots
MEANS (xbar).
Precision is a measure of variability, and is
commonly monitored by the use of
RANGES.
Combination of charts is referred to an
xbar and r chart.
Defined as a data point that “appears to be
markedly different from other members of
the sample in which it occurs”. Not
discarded or deleted, but indicated in set.
Data could be:
- an extreme value in the distribution;
- results from some gross deviation
from analytical method or math error; so,
investigate process and calculations first.
Most IH methods used address both
sampling and lab analysis. Validation.
Sampling part of methods is often
accepted as published and then evaluated
further based on field studies and
comparison with other methods.
Lab portion of methods should be
validated for the analytes, instrumentation,
and the procedures involved (i.e. spiked
samples).
Sample to which has been added a known
amount of analyte. The analysis of spike
samples can be used to determine the bias
and precision of a test method, the accuracy
of a lab measurement process, and/or to
detect changes in the analytical process.
Need to know ranges of concentrations of
interest and the relationship between
recovery and concentration(s).
AIHA definition: “the lowest concentration of
an analyte in a sample that can be reported
with a defined, reproducible level of
certainty”.
Environmental chemistry limits:
- Critical Limit – analyte detection
- Detection Limit – distinguish from zero
- Quantitation Limit – relatively close to the
true value.
Labs report results to reflect the “true” value.
Number of significant figures implies the
precision that can be attributed to the result.
General rules to apply:
- The least precise measurement determines
the number of significant figures.
- All digits are retained during the calculation
and the final result is rounded to significant
digits.
- Other rules for significant figures on page
324 of third edition.
Two types of error that contribute to uncertainty:
random errors and biases.
- Biases – contributors that can be corrected or
minimized (e.g. calibration of standards or
references by labs, material prep, environ
conditions). Overall average deviation.
- Random errors – results of contributors that
cannot be corrected (e.g. instruments, inability to
repeat a process, variability, etc.). Predominant
contributor to the precision control chart. It can
be measured but cannot be corrected.
Proficiency Testing Programs by:
American
Industrial
Hygiene
Association (AIHA)
Proficiency Analytical Testing (PAT) –
evaluate labs analyzing workplace samples
by use of reference samples (i.e. metals,
silica, organics, asbestos, lead, microbial).
Statistical
data
analysis to
assess
proficiency according to defined criteria.
Round-robin approach.
Statistics
Normal distributions
QA/QC
Control charts