The Evidence Guide describes the underpinning knowledge and skills that must be demonstrated to prove competence. It is essential for assessment and must be read conjunction with the performance criteria, the range statement and the assessment guidelines of the relevant Training Package

Overview of assessment requirements

The competent person will be able to apply statistical theory to a process to interpret and reduce its variation.

What critical aspects of evidence is required to demonstrate competency in this unit?

Evidence of the application of statistical theory to a process should be available

In what context should assessment occur?

Assessment will need to occur in an organisation implementing statistical process control or by project.

Are there any other units which could or should be assessed with this unit or which relate directly to this unit?

This unit could be assessed concurrently with other units dealing with process capability and/or change management.

What method of assessment should apply?

Assessors must be satisfied that the person can consistently perform the unit as a whole, as defined by the elements, performance criteria, skills and knowledge. A holistic approach should be taken to the assessment.

Assessors should gather sufficient, fair, valid, reliable, authentic and current evidence from a range of sources. Sources of evidence may include direct observation, reports from supervisors, peers and colleagues, project work, samples, organisation records and questioning. Assessment should not require language, literacy or numeracy skills beyond those required for the unit.

The assessee will have access to all techniques, procedures, information, resources and aids which would normally be available in the workplace.

The method of assessment should be discussed and agreed with the assessee prior to the commencement of

What evidence is required for demonstration of consistent performance?

Generally the application of statistics over a period of time would be required to generate sufficient evidence

What are the specific resource requirements for this unit?

Access to an organisation using statistical control.

Required skills:

analysis

problem solving

communication

documenting

calculations

use of statistics

Required knowledge:

sampling techniques

purpose of sampling and measurement

random, systematic, stratified sampling

relevance, reliability and representativeness of samples/data collected

purpose of replication of data for statistical control

samples, populations, finite and infinite populations and the differences

methods of calculating means, standard deviations and the like and their purpose in statistical control

the causes of variation in a process

the meaning of broad/ narrow frequency distributions/ range/standard deviations and skewed distributions in process terms

types of control charts and their applications to different types of process/product and for different purposes

process causes of variation and typical cause types of non-random variation

non-process (eg measurement) causes of variation

recognition of stable and unstable processes

causes of stability/instability in the process

calculation of control limits/process capability and the applications of different control limits

the standard distribution curve and confidence limits.

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.

Sampling scheme

Sampling scheme may include:

sampling for attributes or sampling for variables

batch, continuous or custom made products

number of items/samples

size of sample

timing of sampling

location of sampling points

type of sample

number/type of measurements to be done on each sample

sampling equipment

measurement/testing equipment/methods

Procedures

Procedures includes all work instructions, standard operating procedures, formulas/ recipes, batch sheets, temporary instructions and similar instructions provided for the smooth running of the plant. They may be written, verbal, computer based or in some other form.

For the purposes of this Training Package, ' procedures' also includes good operating practice as may be defined by industry codes of practice (eg Good Manufacturing Practice (GMP), Responsible Care) and government regulations.

Handle data

Handle data may include:

calculating means, ranges, mean of means, standard deviation (using appropriate calculation aids)

entering data into a software package

recording data either in writing or electronically

other required manipulations of the data.

Control chart

Control charts may include:

run

tally

mean/range

attributes

other relevant charts

Random

Random variation is the term used in statistical control to refer to those variations for which no cause can be found.

Non-random

Non-random, also called identifiable cause, or assignable cause or special cause are those variations for which a cause can be found and so the cause of the variation eliminated. Non-random variation may also be used to predict possible breaches of the control limits.

Control limits

Control limits, also referred to as process capability are those limits within which the process will operate if it is 'under control'.

Cost of non-conformance

Cost of non-conformance includes:

reprocessing/rework

expediting

unplanned service

excess inventory

complaint handline

downtime

returns

scrap

labour costs

material costs

infrastructure costs/overhead

utility costs

Appropriate limits

Appropriate limits may include:

1 sigma warning limits

2 sigma warning limits

3 sigma control limits

6 sigma limits