Allan Fraser and Associates - training of laboratory personnel,Spectroscopic Methods,Separation Methods,Laboratory Practice,Combustion Analysis,Labora

By: Allan Fraser And Associates  11-11-2011
Keywords: Laboratory, Laboratory Practice, Laboratory Analysts

Services Offered Auditing Service:A laboratory audit is an 'A-Z' audit in which the laboratory is viewed in terms of its current status. Recommendations are given as to areas that need to be improved as far as instrumentation, personnel, reporting, health and safety, methods, training and more. An audit will highlight the status of the laboratory in terms of its readiness for ISO17025 or its level of 'Best Practice'. We conduct various audits including; ISO 17025 preparedness audit
Best Practice audit
General Laboratory Audit
Skills Audit
Health and Safety Audit Method Development:We can develop or implement analytical methods and ensure that you achieve the best accuracy and precision possible from the method. We can optimise all spectroscopic instruments and analytical methods in terms of precision and accuracy. Methods can be developed at your lab site or at our laboratory facility. Method Validation:We offer an expert service for validation of analytical methods.  We come to your laboratory and validate your methods.  Detailed method validation report issued.   Courses OfferedAll courses are offered on-site at your laboratory. Courses are mostly divided up into 50% theory and 50% practical work. We offer courses to groups of analysts but unfortunately we are unable to offer courses to individuals All courses are group offerings.  An evaluation is performed on course delegates before and after the course, facilitating a accurate assessment of development as a result of the learning. Should you be interested in a course not offered here, please contact us as we are able to develop customised courses. Spectroscopic Methods:We offer basic and advanced courses on the following spectroscopic methods: Inductively Coupled Plasma Spectrometry (ICP-AES)
Inductively Coupled Plasma - Mass Spectrometry (ICP-MS)
X-ray Fluorescence (XRF)
Atomic Absorbtion Spectrometry (AAS)
Graphite Furnace Atomic Absorbtion Spectrometry (GFAAS)
Spark Atomic Emission Spectrometry (Spark - AES) Separation Methods:We offer basic and advanced courses on the following separation methods: Gas Chromatography (GC)
High Pressure Liquid Chromatography (HPLC)
Ion Chromatography (IC)
Gas Chromatography Mass Spectrometry (GC-MS) Laboratory Practice:We offer a variety of custom deisgned laboratory practice courses including:Good Laboratory Practice
The Basics of Laboratory glassware
Wet Chemistry methods
Titration and Titration Skills
Sampling and Sample Preparation
Understanding ISO 17025
The Basics of Fire Assay
Basic Statistical Methods for Laboratory Analysts - NEW
Statistical Method Validation - a practical approach -  NEWCombustion Analysis:We offer basic and advanced courses on the following combustion methods: Combustion Analysis - LECO and Eltra instruments including C, S, N, O, H analysis
Nitrogen/Protein Combustion Analysers by the method of Dumas (LECO and other)
Calorific Value by Bomb Calorimetry
Thermogravimetric Analysis (LECO TGA series) Laboratory Supervision and Leadership:Leadership and Supervisory Skills for Lab Supervisors
Executive Leadership Coaching (individuals only)    Why we should be Training our Laboratory Analysts  
by Allan Fraser More than ever before, people are making decisions based on chemical measurements that affect us medically, environmentally, legally, and commercially. The reliability of these measurements is becoming a critical matter. Today, many analysts in South Africa do not have the proper training and often they have do not have access to a more experienced colleague that could offer assistance. My experience is that many analysts working in laboratories in the South Africa can be characterised as having little to no idea of what they are doing or why. Pre-course evaluations and bench audits that we conduct are testament to this. Simply, the "basics" are often missing. Other areas of concern are in simple dilution calculations such as "you have diluted 10 mL. of a 1000 mg/L. sodium stock solution to 100 mL. what is the concentration sodium in the diluted standard?"  The understanding of calibration is also an issue; many analysts don't understand why comparative methods require calibration or they simply cannot identify the slope, y-intercept or determine the sensitivity of a calibration curve. There is also a general lack of knowledge about volumetric glassware, how it is used, when it is used and why it is used. The availability of "push-button" laboratory instrumentation is ever increasing. Laboratory managers should not assume that an analyst is trained to perform analysis if the instrument's instruction manual was the only source of training. Education should be provided for the analyst. Furthermore, job experience and training records should be kept and reviewed on an annual basis. In the laboratory, job knowledge goals should cover these areas: 1. General laboratory technique
2. Health and Safety
3. Chemistry of specific analysis procedures
4. Quality control
5. Basic statistics When analysts are moved from one method or instrument to another they should re-qualify on the new method before doing any analysis. How they re-qualify should be defined as part of the laboratory's quality management system. When many laboratories consider training they usually have a new employee in mind, which they would have to make productive as soon as possible. Management also cannot sit the employee down in a class for one or two weeks, drill them with everything they need to even know, and then move them to the lab and expect them to remember or understand everything that was covered. Learning to be an analyst takes a long time and the most rewarding process occurs when the skills learned in the lab are supplemented with material discussed in the classroom. Successful training can never be passive. The simple presentation of a block of information in a class is rarely sufficient by itself. It must be followed up with supervised practical application on the job and then the person receiving the training must be evaluated. Further, evaluation must be continued over the lifetime of the employee. This is especially true in the case of practical laboratory work, where over time an analyst will introduce short-cuts in their work. Sometimes these short-cuts will introduce valuable savings in time and materials to the procedure; however the result of this is that the quality of the work suffers. Periodic re-evaluation of the analyst's knowledge and the method itself, serves to identify when the quality of analysis is deteriorating. Many analysts we have either met or trained are willing to learn and have a desire to become experts at what they do. No one is born an expert analyst. Training is absolutely necessary to produce a knowledgeable, competent laboratory worker. Aside from the desire to raise the overall level of professionalism among laboratory analysts, there is also often a legal necessity to have highly trained analysts. It takes a lot of time and effort to learn all the skills necessary to be an expert laboratory analyst.

- A Desirable Philosophy for the Analytical Chemist – By Allan Fraser 
     A good analyst continually tempers his or her confidence with doubt. Such doubt leads stimulates a search for new and different methods of confirmation for reassurance. Frequent self-appraisals should embrace every step – from collecting samples to the reporting of results.  The analyst’s first critical scrutiny should be directed at the entire sample collection process in order to guarantee a representative sample for the purpose of the analysis and to avoid any possible losses or contamination during the act of collection. Attention should also be given to the type of container and to the manner of transport and storage.       A periodic assessment should be made of the available analytical methods, with an eye to applicability for the purpose and the situation. In addition, each method selected must be evaluated by the analyst for sensitivity, precision and accuracy, because only inn this way can he determine whether he has interpreted the directions properly. Self-evaluation on these points can give the analyst confidence in the value and significance of his reported results. 

 What is the Responsibility of Laboratory Management?

By Allan Fraser         The function of an analytical laboratory facility is to provide accurate and precise analytical data to its customers. To ensure accuracy, no errors are to be committed and to ensure precision, uncertainty needs to be minimised. There is however, uncertainty in all measurement. It is therefore the duty of the laboratory management to continuously ensure that uncertainty of measurement is kept to a minimum. Keeping uncertainty to a minimum requires homogenous samples, well characterised reference materials, maximum replicates of analysis of sample and reference materials and calibration sensitive and reliable instrumentation. Moreover, the use of independent forms of analysis of samples and statistical comparison of results is good analytical practice and gives confidence in the analytical data produced by the laboratory. The use of competent analysts with the necessary skills, passion for excellence and responsibility is also a key requirement for the reliability of analytical data. With the plethora of analytical techniques and instrument suppliers available to the laboratory it is important that the procurement of instrumentation adequately cover the specifications, service availability, and availability of spare parts. The use of competent materials such as correct grade, certified purity and the effective storage of such materials are tantamount to the laboratory achieving reliable analytical data. The use of competent methods that have been proven to be fit for purpose through method validation are a cornerstone of good analytical practice. Methods should be validated for accuracy, precision, working range, reproducibility, repeatability, robustness, traceability, sensitivity and selectivity. Laboratories use ISO 17025:2005 to implement a quality system aimed at improving their ability to consistently produce valid results. It is also the basis for accreditation from an Accreditation Body. The ISO 17025:2005 standard is about competence, accreditation is simply formal recognition of a demonstration of that competence. To Deduct or Not to Deduct – that is the Question Should the reading of a blank (response) be deducted from the response 
         obtained from samples and standards?
By Allan Fraser

    There are differing opinions on whether the blank response should be deducted from the standards or not. Some instrument software has a built in function that automatically deducts the blank value before plotting the calibration regression whether you like it or not! I personally believe that blank should not be deducted (since there is random error in every measurement) and that it’s effect will be taken care of in the least squares regression where all of the indeterminate errors are taken into account when calculating the slope and intercept. Where the blank is deducted is when we wish to see if there is systematic (determinate) error which is evident by the presence of the intercept on the y-axis after deducting it.  It is important to include the value for a 'blank' in the calibration curve. A blank is a “low” concentration standard. The blank should be subjected to exactly the same sequence of analytical procedures. The instrument signal given by the blank will often not be zero. This signal is subject to errors like all the other points on the calibration plot. It is wrong in principle to subtract the blank value from the other standard values before plotting the calibration graph. This is because when two quantities are subtracted, the error in the final result cannot also be obtained by simple subtraction. Subtracting the blank value from each of the other instrument signals before plotting the graph thus gives incorrect information on the errors in the calibration process. Always run a duplicate blank and ensure that it undergoes the same procedures as in the sample preparation.Hypothesis Testing – Asking a Question of Nature By Allan Fraser

       As a scientist and a rational human being, learn to question everything and strive to find answers on your own through research. 'Doubt' is the most sacred thing for a scientist and an adherent of the scientific method. This doubt keeps you on focused when you feel like surrendering or believing in something at face value without adequate scientific research. As scientists, we constantly strive to create a rational and lucid picture of the world by piecing together one fact at a time, through theorising and experimentation (Pilgrim, 2011). A Hypothesis means to “Ask a Question of Nature”. In Science we often need to test our hypothesis. A hypothesis is an educated guess, based on observation. Usually, a hypothesis can be supported or refuted through experimentation or more observation. A hypothesis can be disproven, but cannot be proven to be true (Helmenstine, 2010). To test the hypothesis we create an experiment that will yield one of two answers: Yes or No or True or False. The classical way to make statistical comparisons is to prepare a statement about a fact for which it is possible to calculate its probability of occurrence. This statement is the null hypothesis and its counterpart is the alternative hypothesis (Fraser, 2011). The null hypothesis is traditionally written as H0 and the alternative hypothesis as H1 orHa. A statistical test measures the experimental strength of evidence against the null hypothesis. A Null Hypothesis is a statement that the difference between two values can be explained by random error. It is retained if the test for significance does not fail (H0). A null hypothesis assumes that the numerical quantities being compared are the same. The probability of the observed differences appearing as a result of random error is then calculated from statistical theory. The alternative hypothesis is therefore a statement that the difference between two values is too great to be explained by random error. The alternate hypothesis is accepted if a test for significance shows that the null hypothesis should be rejected (Ha or H1). Typical tests for significance are the F ratio test and the t-test. If we reject the null hypothesis at say, a 95% confidence level, there is a 5% probability that the null hypothesis was incorrectly rejected. An example of hypothesis testing is:

Let μ1 and μ2 be the means of two samples; If one wants to investigate the likelihood that their means are the same, then the null hypothesisis:   H0: μ12      and the alternative hypothesis is:  H1: μ1 ≠μ2    but it could also be: H1: μ12   The first example of H1 is said to be two-sided or two-tailed because includes both μ12and   μ12;The second is said to be one-sided or one-tailed. The number of sides has implications on how to formulate the test (Fraser, 2011). References:
Fraser A.W., (2011), “Statistical Method Validation for Analytical Methods – a practical approach”
Helmestine A.M., (2010) “Scientific Hypothesis, Theory, Law Definitions” (accessed 25 May 2011)
Pilgrim G. (2011)  

Keywords: Laboratory, Laboratory Analysts, Laboratory Practice,