Quality Management System Template Free.docx 5a5c6f

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I. Contents of quality management system template free ================== This template of 23 policies and procedures has been compiled to assist training companies in deg their training quality management system in a Seta-compliant and -friendly way. The contents of the policies & procedures have ed accreditation site visits and audits at 18 of the various Setas. More information In order to be granted a Seta accreditation training providers need to have a documented set of policies and procedures that encapsulate how they manage the quality of their training. This is often quite a tedious process as providers tend to have tacit or “unspoken” quality management built into the way in which they conduct their business – this is rarely explicitly documented. This template is intended to help you to capture this by asking all the right questions to assist you in getting maximum value from this process, whilst also catering for Seta compliance. Who should use this QMS? Training providers and assessment centres seeking Seta/ETQA accreditation. What does this agreement say? The QMS template consists of the following documents: 1.

Quality Assurance Policy and Procedure

2.

Strategic Management Policy and Procedure

3.

Marketing Policy

4.

Resource Management Policy and Procedure

5.

Financial Management Policy and Procedure

6.

Risk Management Policy and Procedure

7.

Staff Selection, Appraisal, Development and Promotion Policy and Procedure

8.

istration and Communication Policy and Procedure

9.

Document and Record Management Policy and Procedure

10.

Reporting Policy and Procedure

11.

Health and Safety Management Policy

12.

Registration & Accreditation Policy

13.

Learning Programme Development and Evaluation Policy and Procedure

14.

Learner Entry, Guidance and Policy and Procedure

15.

Course Delivery (Facilitation) Policy and Procedure

16.

Offsite Delivery Policy and procedure

17.

Work Site Management Policy

18.

Assessment Management and RPL Policy and Procedure

19.

Moderation Policy and Procedure

20.

Appeals and Disputes Policy and Procedure

21.

Certification Policy and Procedure

22.

Evaluation and Review Policy and Procedure

23.

Management System Review Policy/Internal Audit Policy and Procedure What does this QMS document look like? The QMS template can be printed onto 85 A4 pages What do you need to do to use the QMS template?

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Read the policies & procedures to ensure understanding Amend and adapt it to reflect your quality management processes – bear in mind your specific Seta’s requirements

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Change “TP” to the name of your company, as well as version numbers etc as described in the document

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Distribute the policies & procedures to anyone involved with quality management in your company. Disclaimer The Online Agreements Shop cc and its , staff, legal advisers, partners and consultants, agents and any person associated therewith cannot be held liable for any loss or damage that is incurred or may be incurred by any person as a direct or indirect result of the use of this website or any document or information contained on or obtained from this website, nor as a result of anything that is contained in or left out of any document. ==================

III. Quality management tools

1. Check sheet The check sheet is a form (document) used to collect data in real time at the location where the data is generated. The data it captures can be quantitative or qualitative. When the information is quantitative, the check sheet is sometimes called a tally sheet. The defining characteristic of a check sheet is that data are recorded by making marks ("checks") on it. A typical check sheet is divided into regions, and marks made in different regions have different significance. Data are read by observing the location and number of marks on the sheet. Check sheets typically employ a heading that answers the Five Ws:    

Who filled out the check sheet What was collected (what each check represents, an identifying batch or lot number) Where the collection took place (facility, room, apparatus) When the collection took place (hour, shift, day of



the week) Why the data were collected

2. Control chart Control charts, also known as Shewhart charts (after Walter A. Shewhart) or process-behavior charts, in statistical process control are tools used to determine if a manufacturing or business process is in a state of statistical control. If analysis of the control chart indicates that the process is currently under control (i.e., is stable, with variation only coming from sources common to the process), then no corrections or changes to process control parameters are needed or desired. In addition, data from the process can be used to predict the future performance of the process. If the chart indicates that the monitored process is not in control, analysis of the chart can help determine the sources of variation, as this will result in degraded process performance.[1] A process that is stable but operating outside of desired (specification) limits (e.g., scrap rates may be in statistical control but above desired limits) needs to be improved through a deliberate effort to understand the causes of current performance and fundamentally improve the process. The control chart is one of the seven basic tools of quality control.[3] Typically control charts are used for time-series data, though they can be used for data that have logical comparability (i.e. you want to compare samples that were taken all at the same time, or the performance of different individuals), however the type of chart used to do this requires consideration.

3. Pareto chart A Pareto chart, named after Vilfredo Pareto, is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the cumulative total is represented by the line. The left vertical axis is the frequency of occurrence, but it can alternatively represent cost or another important unit of measure. The right vertical axis is the cumulative percentage of the total number of occurrences, total cost, or total of the particular unit of measure. Because the reasons are in decreasing order, the cumulative function is a concave function. To take the example above, in order to lower the amount of late arrivals by 78%, it is sufficient to solve the first three issues. The purpose of the Pareto chart is to highlight the most important among a (typically large) set of factors. In quality control, it often represents the most common sources of defects, the highest occurring type of defect, or the most frequent reasons for customer complaints, and so on. Wilkinson (2006) devised an algorithm for producing statistically based acceptance limits (similar to confidence intervals) for each bar in the Pareto chart.

4. Scatter plot Method

A scatter plot, scatterplot, or scattergraph is a type of mathematical diagram using Cartesian coordinates to display values for two variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis.[2] This kind of plot is also called a scatter chart, scattergram, scatter diagram,[3] or scatter graph. A scatter plot is used when a variable exists that is under the control of the experimenter. If a parameter exists that is systematically incremented and/or decremented by the other, it is called the control parameter or independent variable and is customarily plotted along the horizontal axis. The measured or dependent variable is customarily plotted along the vertical axis. If no dependent variable exists, either type of variable can be plotted on either axis and a scatter plot will illustrate only the degree of correlation (not causation) between two variables. A scatter plot can suggest various kinds of correlations between variables with a certain confidence interval. For example, weight and height, weight would be on x axis and height would be on the y axis. Correlations may be positive (rising), negative (falling), or null (uncorrelated). If the pattern of dots slopes from lower left to upper right, it suggests a positive correlation between the variables being studied. If the pattern of dots slopes from upper left to lower right, it suggests a negative correlation. A line of best fit (alternatively called 'trendline') can be drawn in order to study the correlation between the variables. An equation for the correlation between the variables can be determined by established best-fit procedures. For a linear correlation, the best-fit procedure is known as linear regression and is guaranteed to generate a correct solution in a finite time. No universal best-fit procedure is guaranteed to generate a correct solution for arbitrary relationships. A scatter plot is also very useful when we wish to see how two comparable data sets agree with each

other. In this case, an identity line, i.e., a y=x line, or an 1:1 line, is often drawn as a reference. The more the two data sets agree, the more the scatters tend to concentrate in the vicinity of the identity line; if the two data sets are numerically identical, the scatters fall on the identity line exactly.

5.Ishikawa diagram Ishikawa diagrams (also called fishbone diagrams, herringbone diagrams, cause-and-effect diagrams, or Fishikawa) are causal diagrams created by Kaoru Ishikawa (1968) that show the causes of a specific event. [1][2] Common uses of the Ishikawa diagram are product design and quality defect prevention, to identify potential factors causing an overall effect. Each cause or reason for imperfection is a source of variation. Causes are usually grouped into major categories to identify these sources of variation. The categories typically include  People: Anyone involved with the process  Methods: How the process is performed and the specific requirements for doing it, such as policies, procedures, rules, regulations and laws  Machines: Any equipment, computers, tools, etc. required to accomplish the job  Materials: Raw materials, parts, pens, paper, etc. used to produce the final product  Measurements: Data generated from the process that are used to evaluate its quality  Environment: The conditions, such as location, time, temperature, and culture in which the process operates

6. Histogram method

A histogram is a graphical representation of the distribution of data. It is an estimate of the probability distribution of a continuous variable (quantitative variable) and was first introduced by Karl Pearson.[1] To construct a histogram, the first step is to "bin" the range of values -- that is, divide the entire range of values into a series of small intervals -- and then count how many values fall into each interval. A rectangle is drawn with height proportional to the count and width equal to the bin size, so that rectangles abut each other. A histogram may also be normalized displaying relative frequencies. It then shows the proportion of cases that fall into each of several categories, with the sum of the heights equaling 1. The bins are usually specified as consecutive, non-overlapping intervals of a variable. The bins (intervals) must be adjacent, and usually equal size.[2] The rectangles of a histogram are drawn so that they touch each other to indicate that the original variable is continuous.[3]

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