Google Links

Follow the links below to find material targeted to the unit's elements, performance criteria, required skills and knowledge

Required Skills

Required skills

Required skills include

performing relevant mathematical operations

identifying and using relevant statistical methods

communicating and explaining data related changes and procedures to individuals and groups

negotiating with other employees and managers on proposed improvement actions

analysing procedures and data to establish variation

solving problems to root cause where assignable cause of variation is not obvious

working in a team

using computer software relevant to required analyses and process

Required knowledge

Required knowledge includes

data collection methods

data processing techniques required

variability and normal distribution

three sigma or six sigma processes as relevant

random and nonrandom results recognition of assignable causes

causes of different types of nonrandom results

causes of random variation

process understanding sufficient to translate the data into variations in the process and determine methods of controlling them

Evidence Required

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

Critical aspects for assessment and evidence required to demonstrate competency in this unit

A person who demonstrates competency in this unit must be able to provide evidence of the ability to

analyse process information

calculate process capabilitytrial limits

improve process capability or organise for it to be improved

analyse revised process information and recalculate process capability

Context of and specific resources for assessment

Assessment of performance must be undertaken in a workplace using or implementing one or more competitive systems and practices

Access may be required to

workplace procedures and plans relevant to work area

specifications and documentation relating to planned currently being implemented or implemented changes to work processes and procedures relevant to the assessee

documentation and information in relation to production waste overheads and hazard controlmanagement

reports from supervisorsmanagers

case studies and scenarios to assess responses to contingencies

Method of assessment

A holistic approach should be taken to the assessment

Competence in this unit may be assessed by using a combination of the following to generate evidence

demonstration in the workplace

workplace projects

suitable simulation

case studiesscenarios particularly for assessment of contingencies improvement scenarios and so on

targeted questioning

reports from supervisors peers and colleagues thirdparty reports

portfolio of evidence

In all cases it is expected that practical assessment will be combined with targeted questioning to assess underpinning knowledge

Where applicable reasonable adjustment must be made to work environments and training situations to accommodate ethnicity age gender demographics and disability

Guidance information for assessment

Assessment processes and techniques must be culturally appropriate and appropriate to the oracy language and literacy capacity of the candidate and the work being performed


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.

Competitive systems and practices

Competitive systems and practices may include, but are not limited to:

lean operations

agile operations

preventative and predictive maintenance approaches

monitoring and data gathering systems, such as Systems Control and Data Acquisition (SCADA) software, Enterprise Resource Planning (ERP) systems, Materials Resource Planning (MRP) and proprietary systems

statistical process control systems, including six sigma and three sigma

Just in Time (JIT), kanban and other pull-related operations control systems

supply, value, and demand chain monitoring and analysis

5S

continuous improvement (kaizen)

breakthrough improvement (kaizen blitz)

cause/effect diagrams

overall equipment effectiveness (OEE)

takt time

process mapping

problem solving

run charts

standard procedures

current reality tree

Competitive systems and practices should be interpreted so as to take into account:

the stage of implementation of competitive systems and practices

the size of the enterprise

the work organisation, culture, regulatory environment and the industry sector

Process capability

Process capability is:

the measurable ability of a process to reliably produce within calculated limits (the limits depend on the variation of the process)

Variation

All processes have variation. The approach in this unit is to separate random variation (no assignable cause) from non-random variation (which has an assignable cause). By finding and eliminating assignable causes, total variation is reduced and process capability will be improved

Six sigma

Six sigma refers to:

a statistical tool for recording defects and determining capability. Six sigma limits equate to 3.4 defects per million opportunities for each product or service transaction. Six sigma is also used as a general term covering a competitive systems and practices approach. Six sigma training typically covers several units of competency in this Training Package

Three sigma

Three sigma refers to:

a traditional statistical process control. Three sigma limits equate to 3 defects per thousand opportunities for each product or service transaction

Required data

The calculation of three sigma or six sigma limits requires process data. The data required depends on the nature of the limits being calculated

Assignable cause

Any non-random variation is said to have an ‘assignable cause’. The methods of data analysis common to statistical capability analysis as well as other methods of root cause analysis should be used to determine the cause of this non-random variation

Improved process capability

Improvements to process capability result from eliminating the causes of non-random variation. The improvements made may be:

as a result of continuous improvement with the process capability being recalculated periodically

as a result of an improvement project with the process capability recalculated as part of that project

Procedures

Procedures may include:

work instructions

standard operating procedures

formulas/recipes

batch sheets

temporary instructions and similar instructions provided for the smooth running of the plant

good operating practice as may be defined by industry codes of practice (e.g. good manufacturing practice (GMP) and responsible care)

government regulations

Procedures may be:

written, verbal, computer-based or in some other format