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

Elements and Performance Criteria

  1. Choose an improvement project
  2. Design the experiment.
  3. Conduct the experiment.
  4. Analyse and confirm the experimental results.

Required Skills

Required skills

analysis

problem solving

communication

documenting

calculations

use of statistics packs

Required knowledge

Charting such as Pareto Charts Main Effects Plots Scatter Plots Interaction Plots Contour Plots Response Surface Plots

Statistical principles and analysis such as ANOM Prediction Equations ANOVA Oneway ANOVA Desirability Function Hit a Target Advanced Graphical Data Analysis MultiVari Planning Variation Trees and Funneling Hypothesis Testing Central Limit Theorem Statistical Analysis Roadmap Analysis for Means and ttest Correlation and Regression

Factorial analysis principles and methods such as MultiVariate Analysis Taguchi SN Ratios level Factorial Taguchi L Half Fraction PlackettBurman run Full factorial

Acceptance criteriaconfidence levels

Evidence Required

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 in conjunction with the performance criteria the range statement and the assessment guidelines of the relevant training package

Overview of assessment requirements

Assessment should confirm that the person can undertake DoE projects in a work situation

What are the specific resource requirements for this unit

Access to an organisation using design of experiment or access to an organisation where DoE could be conducted

In what context should assessment occur

Assessment will need to occur in an organisation implementing DoE or through project based assessment

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 six sigma type work andor change management These are

MSACMTA Determine and improve process capability

MSACMT650A Determine and improve process capability

MSACMTA Apply six sigma to process control and improvement

MSACMT653A Apply six sigma to process control and improvement

MSACMCA Lead change in a manufacturing environmentandor

MSACMC410A Lead change in a manufacturing environmentand/or

MSACMCA Manage people relationships

MSACMC611A Manage people relationships

MSAPMSUPA Use structured problem solving tools

MSAPMSUP390A Use structured problem solving tools

MSACMSA Analyse and map a value chain

MSACMS601A Analyse and map a value chain

MSACMTA Mistake proof a production process

MSACMT451A Mistake proof a production process

MSACMTA Undertake proactive maintenance analyses

MSACMT481A Undertake proactive maintenance analyses

The prerequisite unit MCMTA Apply statistics to processes in manufacturingshould where possible be assessed concurrently with this unit

The prerequisite unit MCMT452A Apply statistics to processes in manufacturingshould where possible be assessed concurrently with this unit

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 the assessment

What evidence is required for demonstration of consistent performance

Generally one significant DoE project should generate sufficient evidence


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.

Objective of the experiment

Purpose may include:

screen factors to find the critical few

optimise a few critical factors

solve process problem(s)

reduce waste

increase reliability.

Factorial design

Factorial design may include:

2/3 level Factorial,

Taguchi L8,

2/4-1 Half Fraction,

Plackett-Burman 8-run

Full factorial.

Signal to noise ratio

Signal to noise ratio may be estimated from:

previous DoE experience

previous process capability studies

statistical process control data

estimated from other sources

Resolution

Resolution is typically:

Resolution III DOE: A design where main factor effects are confounded with two factor and higher order interactions.

Resolution IV DOE: A design where main effects are confounded with three factor and higher order interactions and all two factor interactions are confounded with two factor interactions and higher order interactions.

Resolution V DOE: A design where main effects are confounded with four factor and higher order interactions and two factor interactions are confounded with three factor interactions and higher order interactions.

Sequential series of experiments

A typical series of experiments consists of:

a screening design (fractional factorial) to identify the significant factors,

a full factorial or response surface design to fully characterize or model the effects,

confirmation runs to verify results

Required metrics

Required metrics may include:

quantitative measures normally associated with the process

other quantitative measures relevant to the experiment

ranking systems for normally qualitative measures such as defectives

Statistics pack

Typical statistics packs include:

minitab

JMP

spreadsheets such as Excel particularly with specific add ons such as Sigma XL, Analyse It or other add ons

Many statistical packages are suitable. It is desirable that they include residual analysis capability.