CHAPTER 7 STATISTICAL PROCESS CONTROL

THE CONCEPT The application of statistical techniques to determine whether the output of a process conforms to the product/service design - to prevent poor quality Control charts are used to detect production of defective products/services OR to indicate that the production process has changed and that the products or services will deviate from their design specification unless something is done to correct the situation

SOURCE OF VARIATION Nothing can be done to eliminate variation in process output completely, but management can investigate the cause of variation to control and minimize it common causes : purely random, unidentifiable and unavoidable, results in symmetric distribution assignable causes : variation-causing factors that can be identified and eliminated, such as unskilled employees and a needing repair machine which affect the mean/plan, spread and shape (skewed distribution)

SOURCE OF VARIATION (continued) A process is said to be in statistical control when the location (of mean/plan), spread or shape of its distribution does not change over time SPC procedures are used after the process is in statistical control to detect the onset of assignable causes so that they can be eliminated

THE INSPECTION PROCESS Quality measurement how to measure quality characteristics (variable, attribute) sample size to collect at which stage in the process to conduct inspections

QUALITY CHARACTERISTICS variables : weight, length, volume that can be measured attributes : can be quickly counted for acceptance, simple yes-no decision, quality specifications are complex, measuring by variables are difficult and costly control charts to establish the control limits and to monitor the process

SAMPLING Complete inspection : the cost of passing defects to the next workstation or external customers outweigh the inspection cost, the need of automated inspection equipment for accuracy and saving time Well-conceived sampling can approach the same degree of protection as complete inspection, randomly selected, inspection costs are high Zero defects (parts per million) oriented  sampling plan that attempts to minimize the possibility of wrongly rejecting good items or wrongly accepting bad items

SAMPLING (continued) Larger sample sizes are for attribute charts because more observations are required to develop a usable quality measure Variable control charts require smaller sample sizes because each sample observation has provided usable information The first and last sample in a small production lot Samples come from a homogeneous source (e.g.: separated samples from different machines, shift, etc)

CONTROL CHARTS A time-ordered diagram where to plot the quality characteristics taken from the samples A sample statistic that falls between upper and lower control limit indicates that the process is exhibiting common causes of variation, while those that fall outside indicate any assignable causes of variation Observations falling outside the control limits do not always mean poor quality and the ones inside the control limit may indicate any “warnings”

TYPE I & II ERROR Control charts are not perfect tools for detecting shift in the process distribution because they are based on sampling distribution Type I error occurs when the employees conclude that the process is out of control based on a sample result that falls outside the control limits, when in fact it as due to pure randomness Type II error occurs when the employee conclude that the process is in control and only randomness is present, when actually the process is out of statistical control

TYPE I & II ERROR (continued) For increasing standard deviation of sampling distribution, the probability of type I error is lower while the probability of type II error is higher Applying high (3) sigma limits when the cost of searching for assignable cause is large relative to the cost of not detecting a shift in the process average Using 2 sigma limits when the cost of not detecting a shift in the process average exceeds the cost of searching for assignable cause

LOCATIONS OF INSPECTION PROCESS The considerations : cost of inspection to achieve good quality, cost of poor quality and the their importance skill and technology required inspection spots (raw material, work in process, finished product/service) customer’s involvement the effect on productivity