Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

Administracja Centralna Uczelni - Wymiana międzynarodowa (S1)

Sylabus przedmiotu Statistical Methods in Manufacturing Processes:

Informacje podstawowe

Kierunek studiów Wymiana międzynarodowa
Forma studiów studia stacjonarne Poziom pierwszego stopnia
Tytuł zawodowy absolwenta
Obszary studiów
Profil
Moduł
Przedmiot Statistical Methods in Manufacturing Processes
Specjalność przedmiot wspólny
Jednostka prowadząca Katedra Technologii Wytwarzania
Nauczyciel odpowiedzialny Daniel Grochała <Daniel.Grochala@zut.edu.pl>
Inni nauczyciele Emilia Bachtiak-Radka <Emilia.Bachtiak-Radka@zut.edu.pl>, Daniel Grochała <Daniel.Grochala@zut.edu.pl>
ECTS (planowane) 5,0 ECTS (formy) 5,0
Forma zaliczenia zaliczenie Język angielski
Blok obieralny Grupa obieralna

Formy dydaktyczne

Forma dydaktycznaKODSemestrGodzinyECTSWagaZaliczenie
laboratoriaL1 30 2,00,38zaliczenie
wykładyW1 30 3,00,62zaliczenie

Wymagania wstępne

KODWymaganie wstępne
W-1Knowledge of manufacturing techniques and machine technology, basic knowledge of statistics.

Cele przedmiotu

KODCel modułu/przedmiotu
C-1To provide students knowledge on types of manufacturing processes and procedures for assessing process stability and performance.
C-2To develop the skills in assessing process efficiency.
C-3To develop skills in preparing control charts and identifying sources of process instability.

Treści programowe z podziałem na formy zajęć

KODTreść programowaGodziny
laboratoria
T-L-1Introduction to exercises, familiarization with the STATISTICA program. Descriptive statistics. Calculating descriptive parameters of random variables based on a sample. Description of the characteristics of a random variable based on histograms. Control charts for continuous quantitative variables. Control charts for discrete quantitative variables. Experimental design, two-level designs.30
30
wykłady
T-W-1Manufacturing process. Process variability, process flow models over time. Distributions of discrete variables: binomial and Poisson. Continuous variable distribution - normal. Population (batch), sample, sample creation. Descriptive parameters of the empirical distribution (mean, median, range, variance, standard deviation, skewness, kurtosis). Histogram - empirical distribution. Process capability indices Cp, Cpk, Pp, Ppk, Cpm, and Cmk. Analysis and interpretation of capability indices. Statistical process control. Process control charts. Structure and conditions of using control charts. Determining control limits. Basic control charts for continuous quantitative variables: mean-standard deviation, mean-range, median-range, individual observations-moving range. Interpretation of control charts. Special control charts: MA, EWMA, CUSUM, Hotelling's. Charts for unequal sample sizes. Charts for short production series. Control charts for discrete quantitative variables: ix, p, np, c, u. Interpretation of control charts. Control charts for short series. Experimental design in process control. Planning experiments in process control.30
30

Obciążenie pracą studenta - formy aktywności

KODForma aktywnościGodziny
laboratoria
A-L-1Participation in classes30
A-L-2Student's own work18
A-L-3consultations2
50
wykłady
A-W-1Participation in classes30
A-W-2Student's own work43
A-W-3consultations2
75

Metody nauczania / narzędzia dydaktyczne

KODMetoda nauczania / narzędzie dydaktyczne
M-1Informative lecture
M-2Laboratories

Sposoby oceny

KODSposób oceny
S-1Ocena formująca: Assessement of lab reports provided by students
S-2Ocena podsumowująca: Assessment of written end-work
S-3Ocena podsumowująca: Assessment of written end-work as regards the course outcomes required

Zamierzone efekty uczenia się - wiedza

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
AAA_1A_CAD/06_W01
The student is able to formulate principles of procedure for assessing process performance and stability and explain the methods of planning experiments used in process control.
C-1T-W-1M-1, M-2S-2, S-3

Zamierzone efekty uczenia się - umiejętności

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
AAA_1A_CAD/06_U01
The student is able to perform calculations necessary to assess the stability and capability of the process. Interpret the results of quantitative analyses and identify sources of process instability.
C-2, C-3T-L-1M-2S-1, S-2

Zamierzone efekty uczenia się - inne kompetencje społeczne i personalne

Zamierzone efekty uczenia sięOdniesienie do efektów kształcenia dla kierunku studiówOdniesienie do efektów zdefiniowanych dla obszaru kształceniaCel przedmiotuTreści programoweMetody nauczaniaSposób oceny
AAA_1A_CAD/06_K01
Student is aware of the need for continuous education in the field of statistical methods applications in manufacturing processes. Is able to effectively plan the implementation of accepted tasks
C-2, C-3T-L-1, T-W-1M-1, M-2S-1, S-2

Kryterium oceny - wiedza

Efekt uczenia sięOcenaKryterium oceny
AAA_1A_CAD/06_W01
The student is able to formulate principles of procedure for assessing process performance and stability and explain the methods of planning experiments used in process control.
2,0
3,0The student is able to correctly define basic process performance indicators and is able to characterize basic control charts.
3,5
4,0
4,5
5,0

Kryterium oceny - umiejętności

Efekt uczenia sięOcenaKryterium oceny
AAA_1A_CAD/06_U01
The student is able to perform calculations necessary to assess the stability and capability of the process. Interpret the results of quantitative analyses and identify sources of process instability.
2,0
3,0The student is able to correctly calculate basic process performance indicators and select a control card for process monitoring.
3,5
4,0
4,5
5,0

Kryterium oceny - inne kompetencje społeczne i personalne

Efekt uczenia sięOcenaKryterium oceny
AAA_1A_CAD/06_K01
Student is aware of the need for continuous education in the field of statistical methods applications in manufacturing processes. Is able to effectively plan the implementation of accepted tasks
2,0
3,0Student demonstrate activity and is engaged at minimal level
3,5
4,0
4,5
5,0

Literatura podstawowa

  1. Mongomery D.C, Introduction to Statistical quality control, Wiley & Sons, Inc., US, 2009, Sixth Edition

Literatura dodatkowa

  1. Hamrol A., Zarządzanie jakością z przykładami., PWN, Warszawa, 2007
  2. Dietrich E., Schulze A., Metody statystyczne w kwalifikacji środków pomiarowych maszyn i procesów produkcyjnych., Notika System., Warszawa, 2000
  3. Iwasiewicz A., Zarządzanie jakością. Podstawowe problemy i metody., PWN., Warszawa, 1999

Treści programowe - laboratoria

KODTreść programowaGodziny
T-L-1Introduction to exercises, familiarization with the STATISTICA program. Descriptive statistics. Calculating descriptive parameters of random variables based on a sample. Description of the characteristics of a random variable based on histograms. Control charts for continuous quantitative variables. Control charts for discrete quantitative variables. Experimental design, two-level designs.30
30

Treści programowe - wykłady

KODTreść programowaGodziny
T-W-1Manufacturing process. Process variability, process flow models over time. Distributions of discrete variables: binomial and Poisson. Continuous variable distribution - normal. Population (batch), sample, sample creation. Descriptive parameters of the empirical distribution (mean, median, range, variance, standard deviation, skewness, kurtosis). Histogram - empirical distribution. Process capability indices Cp, Cpk, Pp, Ppk, Cpm, and Cmk. Analysis and interpretation of capability indices. Statistical process control. Process control charts. Structure and conditions of using control charts. Determining control limits. Basic control charts for continuous quantitative variables: mean-standard deviation, mean-range, median-range, individual observations-moving range. Interpretation of control charts. Special control charts: MA, EWMA, CUSUM, Hotelling's. Charts for unequal sample sizes. Charts for short production series. Control charts for discrete quantitative variables: ix, p, np, c, u. Interpretation of control charts. Control charts for short series. Experimental design in process control. Planning experiments in process control.30
30

Formy aktywności - laboratoria

KODForma aktywnościGodziny
A-L-1Participation in classes30
A-L-2Student's own work18
A-L-3consultations2
50
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta

Formy aktywności - wykłady

KODForma aktywnościGodziny
A-W-1Participation in classes30
A-W-2Student's own work43
A-W-3consultations2
75
(*) 1 punkt ECTS, odpowiada około 30 godzinom aktywności studenta
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięAAA_1A_CAD/06_W01The student is able to formulate principles of procedure for assessing process performance and stability and explain the methods of planning experiments used in process control.
Cel przedmiotuC-1To provide students knowledge on types of manufacturing processes and procedures for assessing process stability and performance.
Treści programoweT-W-1Manufacturing process. Process variability, process flow models over time. Distributions of discrete variables: binomial and Poisson. Continuous variable distribution - normal. Population (batch), sample, sample creation. Descriptive parameters of the empirical distribution (mean, median, range, variance, standard deviation, skewness, kurtosis). Histogram - empirical distribution. Process capability indices Cp, Cpk, Pp, Ppk, Cpm, and Cmk. Analysis and interpretation of capability indices. Statistical process control. Process control charts. Structure and conditions of using control charts. Determining control limits. Basic control charts for continuous quantitative variables: mean-standard deviation, mean-range, median-range, individual observations-moving range. Interpretation of control charts. Special control charts: MA, EWMA, CUSUM, Hotelling's. Charts for unequal sample sizes. Charts for short production series. Control charts for discrete quantitative variables: ix, p, np, c, u. Interpretation of control charts. Control charts for short series. Experimental design in process control. Planning experiments in process control.
Metody nauczaniaM-1Informative lecture
M-2Laboratories
Sposób ocenyS-2Ocena podsumowująca: Assessment of written end-work
S-3Ocena podsumowująca: Assessment of written end-work as regards the course outcomes required
Kryteria ocenyOcenaKryterium oceny
2,0
3,0The student is able to correctly define basic process performance indicators and is able to characterize basic control charts.
3,5
4,0
4,5
5,0
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięAAA_1A_CAD/06_U01The student is able to perform calculations necessary to assess the stability and capability of the process. Interpret the results of quantitative analyses and identify sources of process instability.
Cel przedmiotuC-2To develop the skills in assessing process efficiency.
C-3To develop skills in preparing control charts and identifying sources of process instability.
Treści programoweT-L-1Introduction to exercises, familiarization with the STATISTICA program. Descriptive statistics. Calculating descriptive parameters of random variables based on a sample. Description of the characteristics of a random variable based on histograms. Control charts for continuous quantitative variables. Control charts for discrete quantitative variables. Experimental design, two-level designs.
Metody nauczaniaM-2Laboratories
Sposób ocenyS-1Ocena formująca: Assessement of lab reports provided by students
S-2Ocena podsumowująca: Assessment of written end-work
Kryteria ocenyOcenaKryterium oceny
2,0
3,0The student is able to correctly calculate basic process performance indicators and select a control card for process monitoring.
3,5
4,0
4,5
5,0
PoleKODZnaczenie kodu
Zamierzone efekty uczenia sięAAA_1A_CAD/06_K01Student is aware of the need for continuous education in the field of statistical methods applications in manufacturing processes. Is able to effectively plan the implementation of accepted tasks
Cel przedmiotuC-2To develop the skills in assessing process efficiency.
C-3To develop skills in preparing control charts and identifying sources of process instability.
Treści programoweT-L-1Introduction to exercises, familiarization with the STATISTICA program. Descriptive statistics. Calculating descriptive parameters of random variables based on a sample. Description of the characteristics of a random variable based on histograms. Control charts for continuous quantitative variables. Control charts for discrete quantitative variables. Experimental design, two-level designs.
T-W-1Manufacturing process. Process variability, process flow models over time. Distributions of discrete variables: binomial and Poisson. Continuous variable distribution - normal. Population (batch), sample, sample creation. Descriptive parameters of the empirical distribution (mean, median, range, variance, standard deviation, skewness, kurtosis). Histogram - empirical distribution. Process capability indices Cp, Cpk, Pp, Ppk, Cpm, and Cmk. Analysis and interpretation of capability indices. Statistical process control. Process control charts. Structure and conditions of using control charts. Determining control limits. Basic control charts for continuous quantitative variables: mean-standard deviation, mean-range, median-range, individual observations-moving range. Interpretation of control charts. Special control charts: MA, EWMA, CUSUM, Hotelling's. Charts for unequal sample sizes. Charts for short production series. Control charts for discrete quantitative variables: ix, p, np, c, u. Interpretation of control charts. Control charts for short series. Experimental design in process control. Planning experiments in process control.
Metody nauczaniaM-1Informative lecture
M-2Laboratories
Sposób ocenyS-1Ocena formująca: Assessement of lab reports provided by students
S-2Ocena podsumowująca: Assessment of written end-work
Kryteria ocenyOcenaKryterium oceny
2,0
3,0Student demonstrate activity and is engaged at minimal level
3,5
4,0
4,5
5,0