Statistica Prcess Cntr文档.ppt

Control Charts for Attributes:p Charts This chart is employed to track the proportion of defective units in a series of samples. The procedure: Calculate the mean sample proportion. Calculate the control limits as follows: The proportion of defectives in a computer disks production line has to be monitored. The experiment Every hour a random sample of 200 disks is taken. Each disk is tested to determine if it is defective. Based on the first 40 samples, draw a p chart and determine whether the process was out of control. Control Charts for Attributes:p Charts Solution Sample Defective Proportion 1 19 .095  2 5 .025 3 16 .080 ..……………………………... Mean sample proportion = p = (.095+..25+.080+…)/40 =.05762 The zones Zone A .05762+3(.01648) =.1071 .05762+2(.01648) =.09057 .05762+(.01648) =.0741 Zone A Zone B Zone B Zone C Zone C There is no evidence to infer that the process was out of control * * * * Lamar University Statistical Process Control Introduction Statistical Process Control (SPC) is a form of hypothesis testing employed in industry. Its objective is to monitor the quality of a firm’s products and services. There are two general approaches to quality management. The inspection approach (inspects the finished product) The detection approach (focuses on the production process, and detects when it starts going out of control). Inspection With inspection, products are produced and at the completion of the production process, someone inspects the product to determine if it conforms to specifications. If it does not conform, it is either discarded or repaired. ?Inspection has several drawbacks: It is expensive to produce substandard products regardless of whether they are discarded or fixed. Detection Rather than inspecting the product after it has been produced, we inspect the process to determine when the process starts producing units that do no conform to specifications. ? This approach allows us to correct the production process before it creates a