Guidelines for Laboratory Quality Managers

<p>CHAPTER 1</p><p>Laboratory management and ISO 17025:2017</p><p>Clause 4: General requirements</p><p>4.1 Impartiality</p><p>4.2 Confidentiality</p><p>Clause 5.0: Structural requirements</p><p>Clause 6.0: Resource requirements</p><p>6.1: General</p><p>6.2 Personnel</p>6.3 Facilities and environmental conditions</p><p>6.4 Equipment</p><p>6.5 Metrological traceability</p><p>6.6 Externally provided products and services</p><p>Clause 7.0 Process requirements</p><p>7.1 Review of requests, tenders and contracts</p><p>7.2 Selection, verification and validation of the methods</p><p>7.3 Sampling</p><p>7.4 Handling of test or calibration itemsEnsuring the validity of the results</p>7.5 Technical records</p><p>7.6 Evaluation of measurement uncertainty</p><p>7.7 Ensuring the validity of the results</p><p>7.8 Reporting results</p><p>7.9 Complaints</p><p>7.10 Non-conforming work</p><p>7.11 Control of data-information management</p><p>Clause 8.0 Management system requirements</p><p>8.1 Management system documentation (Option A)</p>8.2 Control of Management system documents (Option A)</p><p>8.3 Control of records (Option A)</p><p>8.4 Action to address risks and opportunities (Option A)</p><p>8.5 Improvement (Option A)</p><p>8.6 Corrective actions (Option A)</p><p>8.7 Internal audits (Option A)</p><p>8.8 Management Reviews (Option A)</p><p></p><p>CHAPTER 2</p><p>Essential for Quality management in testing laboratories</p><p>Managing the Quality of Laboratory Testing Processes</p><p>Developing a Quality Management System (QMS)</p><p>Plan Do Check Act cycle</p><p>Six sigma quality management system</p><p>Quality systems</p><p>Quality system: quality assurance, quality assessment and Control</p><p>Principles of Quality Control</p><p>System planning</p><p>Investigation phase</p><p>Quality manager responsibility</p><p>Steering Team responsibility</p><p>Task team responsibility</p><p>Time line</p><p>Implementation phase</p><p>Consolidating the program</p><p>Monitoring and evaluating the program</p><p>Management review</p><p>Communication and motivation</p><p>TIPS1: Human resources</p><p>TIPS2: Scheduling and conducting a gap analysis</p><p>TIP3: Quality Manual</p><p>TIP 4: Example Scheme of task assignment</p><p>TIP5: Example of Project Gantt chart</p><p></p><p>CHAPTER3</p><p></p><p>Preparing for analysis: the analytical method</p><p>Sources of methods</p>Evaluation of published methods</p><p>The codex Alimentarius commission</p><p>The European Union</p><p>The European Committee for standardization</p><p>International Standard Organization</p><p></p><p>CHAPTER4</p><p></p><p>Statistics for the Quality Control Laboratory</p><p>Data presentation</p>Measure of the central tendency (mean, median, mode)</p><p>Measures of spread (range, variance, standard deviation)</p><p>Normal distribution</p><p>Using samples to estimate population values</p><p>Standard error of the mean</p><p>Shapiro-Wilks for testing normality</p><p>Confidence Intervals</p><p>Steps in the process of hypothesis testing</p><p>Example of statistical tests routinely applied in the analytical laboratory</p><p>F-test</p><p>Outliers: Dixon test</p><p>Outliers: Grubbs test</p><p>Cochran Test for extreme value of variance (outlier variance)</p><p>Combining (Pooling) Estimates of Standard Deviations</p><p>Precision calculations</p><p>Averages</p><p>Comparing two averages by using the t-test</p><p>The repeatability limit (r)</p><p>The calibration process: Regression line</p><p>Weighted regression line</p><p>Method of Standard Addition (MOSA)</p><p>Errors, linear regression analysis and method of standard addition</p><p>The Youden approach to constant and proportional errors</p><p>ANOVA- Analysis of Variance</p><p>Two-way ANOVA</p><p>Meaning of p-value</p><p></p><p>CHAPTER 5</p><p>Uncertainty measurement</p><p>Approaches to estimate measurement uncertainty</p><p>The bottom up approach</p><p>How to calculate the standard uncertainty for a type A evaluation</p><p>How to calculate the standard uncertainty for a type B evaluation</p><p>Top down approach</p><p>Case study – determination of cholesterol in animal and vegetable fats and oils</p><p>Other approaches to estimate measurement uncertainty: The Horwitz equation</p><p>The Horrat value</p><p>CHAPTER 6</p><p>Control Charts and Process capability</p><p>Control Charts</p><p>Construction of a Control Chart</p><p>How to set the control limits for an X chart</p><p>Type of control charts: Average, Range and Standard deviation control charts</p>Quality Control samples</p><p>Guidelines on Interpretation of Control Charts</p><p>Practical points in using a control chart</p><p>TIP: Way to calculate Standard deviation calculation</p><p>Process capability</p><p>Capability Indices Cp and Cpk</p><p>How to conduct a functional study</p><p>Process capability Analysis: An example</p><p>Six sigma and process capability</p>Process capability index Cpk and Six-Sigma metric</p><p>Conclusions</p><p></p><p>CHAPTER7</p><p>Risk Management</p><p>Risk management in the new laboratory standard ISO 17025:2017</p><p>Addressing Opportunities</p><p>Integrating and Implementing Actions</p><p>Risk Management</p><p>Risk identification</p>Failure Modes and Effects Analysis (FMEA) for laboratory</p><p>Probability of Occurrence</p><p>Probability of Occurrence with Standard Linear Scaling</p><p>Severity</p><p>Risk mitigation</p><p>Detection level</p><p>RPN calculation</p><p>Examples</p><p>Sampling frequency</p><p>Frequency of Sampling/Analysis</p><p>Useful readings</p><p>Example of risk assessment for an analytical method from sampling collection to test results</p>