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Quality Management - I

CHAPTER 9. Quality Management - I. What is ‘good’ or ‘not good’ quality ? customer decides it However, not everything that the customers want can be given by the firm Hence, the firm has to take a strategic decision regarding quality.

malcolm-durham
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Quality Management - I

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  1. CHAPTER 9 Quality Management - I

  2. What is ‘good’ or ‘not good’ quality ? customer decides it • However, not everything that the customers want can be given by the firm • Hence, the firm has to take a strategic decision regarding quality

  3. Quality is either a written or unwritten commitment to a known or unknown customer in the market. • The commitment has to be upheld with efforts from all in the organisation.

  4. Control for quality can be exercised over Are right processes operating? FINISHED GOODS Are the goods okay to be sent to the customers? RAW MATERIALS Are raw materials okay? PROCESS

  5. STATISTICAL QUALITY CONTROL (SQC) SQC involves: • Controlling processes - Statistical Process Control (SPC) • Controlling inputs and outputs – Acceptance Sampling(sample and decide to accept / reject)

  6. SPC charts • x and R chart (controlling the variable) • p chart (percent defectives) • c chart (number of defects) These charts have • Central line or ‘mean’ • Upper and lower control limits (UCL & LCL) at ± 3 sigma from the mean.

  7. STATISTICAL PROCESS CONTROL CHARTS Process gone out of control? Mean + 3sigmaUpper control limit Mean Central line Mean-3sigma Lower control limit Process under control x x x x x

  8. If one of the periodic readings of the process output falls within the UCL or LCL, the process is considered to be ‘under control. • If a reading falls outside the UCL or LCL, the process needs to be checked and corrected if necessary.

  9. When we look for an assignable cause when none exists, this is called Type I error • When we are not looking for an assignable cause when the cause does exist, this is called Type II error • The ±3 sigma control limits are a balance between these Type I and Type II errors

  10. x chart and R chart • We periodically take a sample of the output, measure the relevant quality characteristic (e.g. length, radius, weight , pH) and note - The average or ‘mean’ X, and - The spread or ‘range’ R. • Assuming a normal distribution, the 3-sigma control limits are computed. • The x control chart and the R control chart are independent but complementary.

  11. Quick computation of UCL & LCL for x & R charts • For x chart : μ± A2R • For R chart : D4 .R & D3 .R where • A2 , D3 and D4 are constants readily available from tables for various sample size values. • μ is the mean of the sample means (mean of x) • R is the mean of the sample ranges(mean of R)

  12. p- chart • Controlling fraction defectives is the purpose of a p- chart. • Items are classified into two ways as ‘OK’ or ‘defective’ Samples are taken periodically, and the fraction defective ‘p’ is noted For p-chart, the control limits are : UCL & LCL = p ±3 . p (1- p)/n where p is the mean of ‘p’ and n is the sample size

  13. c-chart • Controlling the number of defects is the purpose of a c-chart. • Assuming a Poisson distribution for the defects process, the control limits are: UCL & LCL= c±3 . c where c is the mean number of the defects

  14. SPC charts have much ‘control’ value and also ‘diagnostic’ value: • Indicate as to when a process may be checked, reset and corrected. • Give indications of abnormality or deterioration in the process.

  15. Diagnostic value of Control Charts Different kinds of deterioration in the process may present themselves differently

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