Mgt 449 – Quality Textiles International Paper
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Quality Textiles International Paper
MGT/449
Quality Textiles International Memo
Date: January 23, 2010
From: Student Name, Analyst
RE: Meeting Customer Requirements
The purpose of this memo is to address apparent inconsistencies in the fabric weight of sheet lengths going out to customers from Quality Textiles International and recommend a quality improvement process to eradicate this problem.
To implement successful Quality Control Measures it is important that managers and employees work together in a common interest. Discipline and dedication are required as Quality Control Management is an ongoing process. The organization must agree that the problems found can be fixed and work collectively to that end. Once the problem areas are identified, changes can be made to correct and improve the process in the given areas. If used properly and consistently, organizations do benefit from Quality Control Management processes.
To identify the problem, 50 random fabric samples were taken from the line and weighed. The data collected was analyzed for a sample mean and standard deviation. The mean becomes the average of all the data collected. The mean shows the average production value of the sample collected. One can determine various statistical information including how close the samples come to the specified values needed to meet customer satisfaction. The mean for the sample fabrics is 2.98 ounces per inch compared to the acceptable standard of 2.73 ounces per inch.
The standard deviation measures “how far the data is spread apart”. (ITCOnline, 2008). The standard deviation for the measured samples is 0.52 compared to the acceptable standard of 0.16. This variation signifies a problem in the production.
Using a histogram, the results of the data collection are graphed. The histogram shows in graphic form the indication of the datas spread and also shows the frequency of how often given values occur in a set. Showing a skew to the left, there seems to be some variation in consistency. See chart below.
Control charts are “graphs used to study how a process changes over time”. (ASQ, 2010). Many sources contribute to variations in numbers. One source is called the common cause variation. Common cause variations occur because of the way a process is managed and designed. Another source of variation is known as special causes variations and these are caused by anomalies in the process of production. If only the common cause variation is present, then the process is under control. If both are present, then the process is not under control. A control chart will determine which variations are present in the