Nefise Gönül Şengöz

By Nefise Gönül Şengöz

Control charts are important tools of statistical quality control to enhance quality. Quality improvement methods have been applied in the last few 10 years to fulfill the needs of consumers. The product has to retain the desired properties with the least possible defects, while maximizing profit. There are natural variations in production, but there are also assignable causes which do not form part of chance. Control charts are used to monitor production; in particular, their application may serve as an “early warning” index regarding potential “out-of-control” processes. In order to keep production under control, different control charts which are prepared for dissimilar cases are established incorporating upper and lower control limits. There are a number of control charts in use and are grouped mainly as control charts for variables and control charts for attributes. Points plotted on the charts may reveal certain patterns, which in turn allows the user to obtain specific information. Patterns showing deviations from normal behavior are raw material, machine setting or measuring method, human, and environmental factors, inadvertently affecting the quality of product. The information obtained from control charts assists the user to take corrective actions, hence opting for specified nominal values enhancing as such quality.

Part of the book: Quality Management Systems

By Nefise Gönül Şengöz

Predicting properties of end product from known properties of raw material is an important part of quality control in manufacturing. Main concept in this research is to reach a specified property of end product from known properties of raw material by attaining response surface designs with feasible region. The Ne20–19.21 T/inch yarn breaking strength (response, desired value 450 cNs) is acquired from cotton fiber properties (variables). The relationship between response and variables are obtained in response surface drawings and contour plots. The area showing the desired value in contour plots are colored in lilac and are intersected to obtain the feasible regions. By reading backwards from the feasible region borders, the variable value ranges are reached which will give the desired value of the response is obtained. When this information to start the yarn production is ready, the cotton lots containing these fiber property value ranges will be bought or from raw material in hand we will be read which yarn breaking strength will occur at the end of production. It was concluded that response surface designs with feasible region are quick, practical, and effective tools, provide valuable results, contribute a lot to quality control, and are beneficial in textile quality control.

Part of the book: Response Surface Methodology in Engineering Science

By Nefise Gönül Şengöz

A novel statistical approach for multiple-stream processes is proposed in this manuscript. As important as quality control in manufacturing is, hypothesis tests are an important part of it if utilized and constructed the most logically to evaluate and decide on a special matter in a production line or a production machine. The proposed statistical approach is explained in detail in a spinning mill having 20 spinning frames. The spinning frames are adjusted according to customers’ orders and to the technology of spinning frames first. Then, the result of that adjustment is controlled statistically by means of hypothesis testing, χ2, t-test, and F statistics are used. Later, they are pooled one by one, and at the end, all 20 spinning frames are considered as one machine producing the same yarn, the same variance of yarn count, and the same yarn count. Performed literature review claims that control charts are appropriate for multiple-stream processes. But, the application of this proposed statistical approach guarantees that production starts with correct adjustments on machines, and control charts become more sensitive to the assignable causes. The application area of this proposed statistical approach is wide, leading to higher quality in products, a requirement that is in demand more every day.

Part of the book: Quality Control