Modification History
Release 2 - Prerequisite unit code corrected - MSS404052A
Release 1 - New unit, superseding MSACMT652A Design an experiment* - Equivalent
* New prerequisite MSS404052A Apply statistics to operational processes superseding MSACMT452A Apply statistics to processes in manufacturing
Unit Descriptor
This unit of competency covers the skills and knowledge required to design experiments. The design of experiments is generally undertaken as part of black-belt six sigma but may also be undertaken independently.
Application of the Unit
This unit applies to a technical expert who is required to design and implement experiments aimed at making breakthrough improvements in the process. They will work with other members of the process team in doing this.
This unit primarily requires the application of skills associated with problem solving, initiative and enterprise, and planning and organising skills in order to identify, implement and evaluate an experiment. Communication skills associated with gathering, interpreting and documenting information are required.
Where this unit forms part of a suite of six sigma then the following units will also be relevant:
- MSS403010A Facilitate change in an organisation implementing competitive systems and practices
- MSS403051A Mistake proof an operational process
- MSS404081A Undertake proactive maintenance analyses
- MSS405002A Analyse and map a value stream
- MSS405011A Manage people relationships
- MSS405050A Determine and improve process capability
- MSS405053A Manage application of six sigma for process control and improvement
- MSAPMSUP390A Use structured problem solving tools.
Licensing/Regulatory Information
Not applicable.
Pre-Requisites
MSS404052A Apply statistics to operational processes
Employability Skills Information
This unit contains employability skills.
Elements and Performance Criteria Pre-Content
Elements describe the essential outcomes of a unit of competency. |
Performance criteria describe the performance needed to demonstrate achievement of the element. Where bold italicised text is used, further information is detailed in the required skills and knowledge section and the range statement. Assessment of performance is to be consistent with the evidence guide. |
Elements and Performance Criteria
1 |
Choose an improvement project |
1.1 |
Review a process/value stream map |
1.2 |
Identify areas in need of improvement |
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1.3 |
Select a process/value stream area for analysis and improvement |
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1.4 |
Determine the objective of the experiment in consultation with relevant stakeholders |
2 |
Design the experiment |
2.1 |
Select appropriate factorial design |
2.2 |
Estimate signal to noise ratio |
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2.3 |
Determine required number of runs and factorial fraction |
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2.4 |
Determine resolution |
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2.5 |
Design a sequential series of experiments |
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2.6 |
Calculate resource requirement for this design |
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2.7 |
Determine whether resource requirements are practical in consultation with relevant stakeholders |
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2.8 |
Modify experiment, if required, to match available resources |
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2.9 |
Determine/develop required metrics |
3 |
Conduct the experiment |
3.1 |
Conduct first run of experiment |
3.2 |
Replicate in random order for required number of runs |
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3.3 |
Block out known sources of variation |
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3.4 |
Conduct other experiments in series |
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3.5 |
Record data/have data recorded |
4 |
Analyse and confirm the experimental results |
4.1 |
Identify aliases/confounding of variables/results |
4.2 |
Analyse data using statistics pack or similar |
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4.3 |
Interpret analysed data in line with objectives |
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4.4 |
Identify confidence level of analysed data |
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4.5 |
Design experiment to confirm correlations identified |
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4.6 |
Conduct confirming experiment |
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4.7 |
Analyse data from confirming experiment |
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4.8 |
Confirm results (or conduct further experiments) |
Required Skills and Knowledge
This section describes the skills and knowledge required for this unit. |
Required skills |
Required skills include:
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Required knowledge |
Required knowledge includes:
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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. |
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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 their ability to:
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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:
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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:
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. |
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Competitive systems and practices |
Competitive systems and practices may include, but are not limited to:
Competitive systems and practices should be interpreted so as to take into account:
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Improvement |
Improvement includes:
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Objective of the experiment |
Objective of the experiment may include:
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Factorial design |
Factorial design may include:
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Signal-to-noise ratio |
Signal-to-noise ratio may be estimated from:
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Resolution |
Resolution is typically:
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Sequential series of experiments |
A typical series of experiments consists of:
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Required metrics |
Required metrics may include:
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Statistics pack |
Typical statistics packs include:
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Unit Sector(s)
Unit sector |
Competitive systems and practices |
Custom Content Section
Not applicable.