What is Statistical Quality Control (SQC)?
Statistical Quality Control (SQC) is the application of statistical tools in the manufacturing process for the purpose of quality control. In SQC technique attempt is made to seek out systematic causes of variation as soon as they occur so that the actual variation may be supposed to be due to the granted random causes.
Statistical quality control refers to the use of statistical methods in the monitoring and maintaining of the quality of products and services.
Statistical quality control (SQC) is very important branch of Statistics, as in the today’s age of globalization quality of the product has become important aspect of the life. In this competitive age, as the customer has lot of choice, the companies whose products are of good quality will only survive in the markets. Thus, SQC is the branch of statistics, which deals with the statistical tools or the methods, which are used for controlling the quality of the product.
Basic Categories of Statistical Quality Control (S.Q.C): All the tools of SQC are helpful in evaluating the quality of services. SQC uses different tools to analyze quality problem. SQC comprises the set of statistical tools used by quality control professionals. It can be divided into three broad categories:
Descriptive Statistics
Statistical Process Control (SPC)
Acceptance Sampling
1. Descriptive Statistics: Descriptive Statistics involves describing quality characteristics and relationships. This group includes the mean, standard deviation, range and distribution of data.
2. Statistical Process Control (SPC):
The statistical process control (SPС) is applied in established technological processes in order to observe, analyze, and regulate them. The use of SPC allows for timely warning in case of a deviation and, if necessary, to correct the parameters of the process. The application of SPC is a prerequisite for the timely detection of the reasons behind quality deterioration. It helps in decreasing the defects, maintaining the quality at a selected level, and improving the technological process. The application of statistical techniques to determine whether a process is functioning as desired. SPC is used to determine whether the process is functioning properly or not.
3. Acceptance Sampling: This involves random inspection of a sample of goods. The application of statistical techniques to determine whether a population of items should be accepted or rejected based on inspection of a sample of those items.
The tools in each of these categories provide different types of information for use in quality analysis. Descriptive statistics are used to describe certain quality characteristics, such as the central tendency and variability of observed data. Although descriptions of specific characteristics are helpful, they are not enough to identify whether there is a problem with quality. Acceptance sampling can help to solve this problem. However, although acceptance sampling is helpful in deciding on acceptability after the product has been produced, it does not aid in identifying a quality problem during the production process. To do this it is necessary to use tools from the SPC category.
Variation in the quality of manufactured textiles is inevitable. The manufacturing processes currently in use are not capable of producing completely identical products.
Variations of Statistical Quality Control (S.Q.C):
Allowable or cause variation
Assignable or preventable variation
Functions of Statistical Quality Control (S.Q.C):
Evaluation of quality standards of incoming material, product process and finished goods.
Judging the conformity of the process to establish standards taking suitable action, when deviation is noted.
Evaluation of optimum quality, obtainable under given condition.
Improvement of quality and productivity by process control and experimentation.
Main Purposes of Statistical Quality Control (S.Q.C): The main purpose of Statistical Quality Control (S.Q.C) is to divide statistical method for separating allowable variation from preventable variation.
The Significance of Statistical Quality Control (S.Q.C) in the Textile and Apparel Industry:
The expected quality of product can be produced and hence customers satisfaction can be achieved which brings higher profit.
It is very easy to separate allowable variation from the preventable variation by this.
It ensures an early detection of faults in process and hence minimum wastage.
With its help one can easily defect the impact of chance in production process in the change in quality.
It ensures overall co-ordination.
It can be use in the interpretation control chart.
Importance of Statistical Quality Control (SQC) in Textile and Apparel Industry: The modern textile industry is a complex, high technology industry facing numerous competitive challenges. Markets are becoming more complex. Short life cycles are common, and demands for rapid response and just-in-time delivery are growing. As competition continues to increase, textile companies must rely more on superior quality, innovative products and rapid response to customer needs, to secure markets and continue to grow. To cope with these challenges, many textile companies have implemented quality management initiatives, to reduce costs and increase both product quality and customer satisfaction.
One of the most recent trends in automation is the use of continuous monitoring systems for on-line quality measurement and for recording defects. The continuous monitoring of a process often produces more data than manufacturers are equipped to use profitably, and continuous correction of a process based on a data stream may actually decrease product quality or mask problems needing attention.
Statistical quality control (SQC) in textile industry is designed to sample a large population on an infrequent basis. Quality assessment therefore only takes place on a small portion of the total product. It has been argued that the use of continuous monitoring would mean that there would be no need for SQC. This attitude assumes that the sole function of SQC is to catch the defective product before it reaches the customer (i.e. acceptance sampling), and ignores the potential for statistics as a tool for product improvement. In recent years, those SQC techniques that worked well for final product quality control have been applied to both the materials being processed and to process conditions. This procedure is now known as statistical process control (SPC). However, some SPC techniques that work with infrequent sampling may not be useful when very frequent or continuous sampling is necessary. Nevertheless, SPC is currently widely used in the textile and apparel industry.
Founder & Editor of Textile Learner. He is a Textile Consultant, Blogger & Entrepreneur. He is working as a textile consultant in several local and international companies. He is also a contributor of Wikipedia.
