Elements and Performance Criteria

RANGE STATEMENT
The range statement relates to the unit of competency as a whole. It allows for different work environments and situations that may affect performance. Bold italicised wording, if used in the performance criteria, is detailed below. Essential operating conditions that may be present with training and assessment (depending on the work situation, needs of the candidate, accessibility of the item, and local industry and regional contexts) may also be included.
Codes of practice
Where reference is made to industry codes of practice, and/or Australian/international standards, it is expected the latest version will be used
Standards, codes, procedures and/or enterprise requirements
Standards, codes, procedures and/or enterprise requirements may include:
Australian and international standards such as:
AS ISO 1000-1998 The international system of units (SI) and its application
ISO 5725 Accuracy (trueness and precision) of measurement methods and results
ISO/IEC Guide 98-3:2008 Uncertainty of measurement - Part 3 Guide to the expression of uncertainty in measurement (GUM)
Eurachem/CITAC Guide CG4 Quantifying uncertainty in analytical measurement
national measurement regulations and guidelines
National Association of Testing Authorities (NATA) Technical notes
material safety data sheets (MSDS)
equipment manuals and warranty, supplier catalogues and handbooks
sampling and test procedures and standard operating procedures (SOPs)
enterprise quality manual and customer quality plan
validation of the equipment and associated software where applicable
validation of spreadsheets developed in-house for assay and process calculations
Concepts of metrology
Concepts of metrology may include:
that all measurements are estimates
measurements belong to a population of measurements of the measured parameters
repeatability
precision
accuracy
significant figures
sources of error
uncertainty
traceability
Data
Data may be recorded on:
worksheets
spreadsheets
databases linked to information management systems
Data may include results of:
observations
tests and measurements
analyses
surveys
quality assurance and control assessments
Data may be presented in the form of:
graphs
tables
histograms
pie charts
bar charts
control charts
semi-quantitative observations and be expressed on a scale (for example, 1 to 4 or + to ++++)
Calculations
Calculations may be performed:
with or without a calculator
using computer software, spreadsheets, databases and statistical packages
Calculations of scientific quantities
Calculated of scientific quantities may include:
converting units involving multiples and submultiples
significant figures, round off, estimate and approximate
transposing and evaluating formulae
fractions, decimals, proportions and percentages
perimeters and angles
percentage and absolute uncertainties in measurements and test results
statistical values of data, such as mean, median, mode and standard deviation
areas (m2) and volumes (mL, L, m3) of regular shapes, such as packaging
dose (mg), average mass, mass percentage, density, specific gravity, moisture, relative and absolute humidity, viscosity and permeability
ratios, such as mass to mass, mass to volume and volume to volume percentages
concentration, such as molarity, g/100mL, mg/L, mg/(L, ppm, ppb, dilution mL/L
average count, colonies per swab surface and cell counts, such as live and dead/total
process variables, such as pressure, gauge pressure, velocity and flow rates
biological oxygen demand (BOD), chemical oxygen demand (COD) and total organic carbons (TOC)
% content of moisture, ash, fat, protein, alcohol, sulphur dioxide and trace metals, such as calcium or zinc
food properties, such as % concentration (dry), friability, bitterness, brix, free amino nitrogen, diastatic power, calorific content and yeast viability
stress, strain, moduli and force
Records
Records could include information associated with:
purchase of equipment and materials, service records
safety procedures
history of calibration and test results
Occupational health and safety (OHS) and environmental management requirements
OHS and environmental management requirements:
all operations must comply with enterprise OHS and environmental management requirements, which may be imposed through state/territory or federal legislation - these requirements must not be compromised at any time
all operations assume the potentially hazardous nature of samples and require standard precautions to be applied
where relevant, users should access and apply current industry understanding of infection control issued by the National Health and Medical Research Council (NHMRC) and State and Territory Departments of Health

EVIDENCE GUIDE
The Evidence Guide provides advice on assessment and must be read in conjunction with the performance criteria, required skills and knowledge, range statement and the Assessment Guidelines for the Training Package.

Overview of assessment

Critical aspects for assessment and evidence required to demonstrate competency in this unit
Assessors should ensure that candidates can:
code, record and check the documentation of data
calculatescientific and statistical quantities relevant to the workplace and present accurate results in the required format
recognise anomalies and trends in data
maintain the confidentiality of data in accordance with workplace and regulatory requirements
keep records up-to-date and secure.

Context of and specific resources for assessment
This unit of competency is to be assessed in the workplace or simulated workplace environment.
This unit of competency may be assessed with:
MSL924002A Use laboratory application software
technical units, such as:
relevant MSL973000 series units of competency
relevant MSL974000 series units of competency.
Resources may include:
data sets and records
computer and relevant software or laboratory information system
relevant workplace procedures.

Method of assessment
The following assessment methods are suggested:
review of data worksheets, calculations, computer files (such as spreadsheets, databases, statistical analysis), graphs, tables and/or charts prepared by the candidate
review of records transcribed, maintained or stored by the candidate
feedback from supervisors and peers
questions to assess understanding of relevant procedures and trends in data
observation of the candidate as they process data, file and store records.
In all cases, practical assessment should be supported by questions to assess underpinning knowledge and those aspects of competency which are difficult to assess directly.
Where applicable, reasonable adjustment must be made to work environments and training situations to accommodate ethnicity, age, gender, demographics and disability.
Access must be provided to appropriate learning and/or assessment support when required.
The language, literacy and numeracy demands of assessment should not be greater than those required to undertake the unit of competency in a work like environment.

This competency in practice
Industry representatives have provided the case studies below to illustrate the practical application of this unit of competency and to show its relevance in a workplace setting.
Manufacturing
A laboratory assistant in a materials testing laboratory was performing routine tensile tests on samples of vinyl sheet. The assistant converted the readings from the machine to appropriate units using a simple calculation and recorded them in the logbook for that test method. After comparing these test results with previous results for the same type of vinyl material, the assistant found that the tensile strength was within the required range. However, it was at the lower rather than the upper end of the range as in previous testing. The assistant discussed the results with the laboratory supervisor. The calibration file for that machine showed that it had been calibrated four months previously and had not needed adjustment. Test results for the same period showed that the machine was giving lower than normal tensile strength readings for the few higher strength materials tested over the last two months. The assistant did some more checks and confirmed this trend. The machine was re-calibrated by the instrument company and the frequency of internal calibration checks by the laboratory assistant was increased. This problem would not have been detected or corrected as quickly without the assistant's initiative and competent recording and retrieval of test results and calibration information.
Biomedical
A technical assistant works in a team with laboratory scientists and technical officers. Analyses of electrolytes are routine and occur in large volume throughput even in this small diagnostic laboratory. The assistant is assigned tasks that contribute to the overall production of results, their reporting and the quality control evaluation of the results. One task is the daily collection of the electrolyte analyses from the internal quality control area. In this case, the technical assistant plots the results on a Levy-Jennings graph and computes the mean value. The assistant reports immediately to the supervisor if the plots show deviations which indicate out-of-control results.
Food processing
Cooking and holding temperatures greatly affect the nutrient composition of processed foods. The CSIRO provides documentation of nutrient losses with temperature variations. For cooked foods, there is the added problem of microbial growth in the so called 'danger zone'. In one laboratory, the technical assistant conducts simple testing of foods using a temperature probe and also measures the temperature of the storage areas, holding trays or bainmaries and individual tray units. Careful documentation of the temperatures of the foods and times of measurement must be kept. The technical assistant supplies the data as tables and a plot of temperature versus time. For quality control purposes, the assistant is directed to use a cross reference of mercury thermometer readings versus probe measurements for ambient temperature. The assistant plots the thermometer readings against the probe readings and reports to the supervisor if the plot shows a slope other than the defined value.