1. SylabUZ
2. Wydział Matematyki, Informatyki i Ekonometrii
3. semestr zimowy 2022/2023
4. Computer science and econometrics - pierwszego stopnia z tyt. licencjata
5. Quality Control

Wygeneruj PDF dla tej strony

Quality Control - opis przedmiotu

Cel przedmiotu

To familiarize students with statistical methods applied in quality control.

Wymagania wstępne

Zapisz zmiany

Passed lectures on: probability theory, mathematical statistics.

Zakres tematyczny

   1. Introduction.
Historical view. Pareto principle. Probabilistic definition of a regulated production process. The role of statistics in quality control. Deming's Fourteen Points. (2 hours.)

   1. Model of the production process with disturbances.
Probabilistic basis for the construction of control charts. Justification of the principles used to conduct research on the production process aimed at providing data for the construction of control cards. (4 hours)

   1. Unbiased estimation of the standard deviation of the production process.
Discussion of constants correcting the unbiased estimators: sample standard deviation, range, median (4 hours)

   1; Control charts.
General principle of construction of control cards. Control card X, control card S, control card R and their modifications. Specific sequences of subsequent points signaling the possibility of a disturbance. (6 hours)

   1. Control charts based on alternative assessments. (2 hours.)
   2. Optimization of the production process.
Study of the impact of control variables on the production process - simplex method, (2 hours) - Taguhi method (application of factorial designs). (4 hours)

   1. Cp and Cpk characteristics. (2 hours.)
   2. Elements of acceptance control. (4 hours)

Labboratory

1. Introductory classes on the software used. (2 hours.)
2. Calculation and analysis of the probability of detecting disturbances at control lines determined on the basis of real parameters in the model with disturbances. Calculating the probability of a false dysregulation signal using the 3 sigma rule for the standard deviation chart (6 hrs)
3. Determining the constant correcting the bias of the sample standard deviation. Illustration of the effect of introducing correction constants. (2 hours.)
4. Comparisons of deviations of control lines (determined by simulation) from exact values for different versions of cards. (4 hours)
5.Tracking the waiting time to detect a disturbance depending on the parameters of the disturbance distribution (including comparative analysis of cards based on the mean and median). (4 hours)
6. Checklists based on alternative assessments (including the 3 sigma rule and sample size) (2 hours)
7. Applications of the simplex method. (3 hours)
8. Analysis of the impact of levels of control variables on quality (actual data). Selection of the optimal set of levels. (5 hours)
9. Final colloquium (2 hours)

Metody kształcenia

Traditional lecture (chalk and blackboard only for the most important formulations, proofs, transformations of formulas), in laboratories, solving tasks using simulation procedures as well as analyzing real data using a selected statistical package.

Efekty uczenia się i metody weryfikacji osiągania efektów uczenia się

Opis efektu	Symbole efektów	Metody weryfikacji	Forma zajęć

Warunki zaliczenia

1. During the laboratory, visual verification of the correctness of the selection of procedures launched at all computer workstations. Random review questions regarding the interpretation of the results of the procedures used. A colloquium with tasks of varying difficulty, allowing for the assessment of whether the student has achieved the minimum learning outcomes.

2. Oral examination (1st and 2nd term) with questions related to the practice of organizing simple experiments used in the statistical control of the production process as well as statistical inference related to them.

The course grade consists of the laboratory grade (40%) and the exam grade (60%). The condition for passing the course is positive grades in the laboratory and exam.

Literatura podstawowa

1. R. J. Thompson, J. R. Koronacki, Statistical Process Control fo Quality Improvements, New York - London, Chaptman & Hall. 

2. T. P. Ryan, Statistical Methods for Quality Improvement, New York, JohnWiley & Sons 1989.

Literatura uzupełniająca

 1.  P.W.M. John, Statistical Methods in Engineering and Quality Assurance, Wiley, New York 1990. 

Uwagi

Zmodyfikowane przez dr hab. Stefan Zontek, prof. UZ (ostatnia modyfikacja: 07-02-2024 11:10)