This unit applies to a person working in an organisation applying statistical process control on processes or operations. The statistical process control will usually be used to monitor the processes or operations and determine when action needs to be taken. The appropriate action will then be taken in accordance with standard procedures.
The unit includes applying knowledge of frequency distribution and variation to the data/chart to distinguish between random and non-random variation and assumes understanding of the process and/or equipment to help interpret those results.
This unit primarily requires the application of skills associated with gathering and analysing data and communicating statistical information to others. This unit also has a strong emphasis on problem solving, initiative and enterprise, planning and organising, and self-management to solve problems and manage processes.
Not applicable.
1 | Collect process data | 1.1 | Interpret sampling scheme |
1.2 | Obtain measurements in accordance with standard procedures | ||
1.3 | Handle data, as required |
2 | Interpret data | 2.1 | Plot data on appropriate control chart |
2.2 | Distinguish between random and non-random patterns of results | ||
2.3 | Identify results outside the control limits | ||
2.4 | Recognise situations requiring action | ||
2.5 | Take appropriate action in accordance with standard procedures | ||
2.6 | Determine cost of non-conformance |
3 | Calculate control limits | 3.1 | Consult relevant stakeholders to determine appropriate limits |
3.2 | Use relevant methods to calculate/revise control limits | ||
3.3 | Plot limits on control chart | ||
3.4 | Explain impact of limit to relevant stakeholders |
Required skills |
Required skills include: applying a range of sampling procedures analysing samples and data for variation, relevance, reliability and representativeness problem solving the causes of variation in a process communicating with other employees to obtain samples/data and to explain results and limits plotting or documenting results undertaking calculations, including: basic arithmetic functions mean, range, mean of means, standard deviation (using appropriate calculation aids) using statistics to support process and operations control |
Required knowledge |
Required knowledge includes: sampling techniques purpose of sampling and measurement random, systematic and stratified sampling 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 meaning of broad/narrow frequency distributions/range/standard deviations and skewed distributions in process terms concept of limits, including: 1 sigma warning limits 2 sigma warning limits 3 sigma control limits 6 sigma limits 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 (e.g. 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 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: follow sampling procedures apply basic statistical processes analyse data to identify variations and non-conformances plot or document results. |
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 control/management reports from supervisors/managers 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 studies/scenarios (particularly for assessment of contingencies, improvement scenarios, and so on) targeted questioning reports from supervisors, peers and colleagues (third-party 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. |
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 |
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 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 |
Handle data | Handle data may include: calculating means, ranges, mean of means and standard deviations (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, 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 |
Unit sector | Competitive systems and practices |
This unit contains employability skills.
Not applicable.