Process Capability and Statistical Process Control

Topics: Process capability, Quality, Management Pages: 2 (446 words) Published: March 5, 2013
Bayfield Mud Company case study

1. What is your Analysis of the bag-weight problem?
Refer to the case, Quality control analysis for this case will be conducted via X-charts and R-charts. X-charts is to control the central tendency of the process, for this case we refer to the weight of 50-pound bags of treating agents R-charts is to control the dispersion of the process, for this case we refer to the range of weigh or difference between maximum weight and minimum weight of the bag. From the analysis of problems, based on the calculations taken from all three shifts over three days, we can see that the average weights, ranges, upper and lower limits have been out of control. The problem begin when Wet-Land Drilling, Inc. had filed a complaint that the bags it received from Bayfield were short-weight, according to previous send the weight of the bags used to be 50 pounds, however the new arrivals show a weight of 47.5 pounds per bag, causing a conflict to the company. The company present the problem as a increased of demand, hiring new employees with a lack of training, new employees occupy the night shift, where old employees check the production, however the double checking of the bag still a problem to the company. First of all we need to analyze and find the errors the process could have, caused by the increased of demand and a lack of control due the old employees, for the analysis I will use the Statistical Process Control (SPC). ¨Statistical process control (SPC) involves using statistical techniques to measure and analyze the variation in processes. Most often used for manufacturing processes, the intent of SPC is to monitor product quality and maintain processes to fixed targets. Statistical quality control refers to using statistical techniques for measuring and improving the quality of processes and includes SPC in addition to other techniques, such as sampling plans, experimental design, variation reduction, process capability analysis, and process...
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