Servizi per la didattica

PORTALE DELLA DIDATTICA

01QFYNL, 01QFYJM, 01QFYMN, 01QFYNM, 01QFYQR

A.A. 2020/21

Course Language

Inglese

Course degree

1st degree and Bachelor-level of the Bologna process in Industrial Production Engineering - Torino/Athlone

1st degree and Bachelor-level of the Bologna process in Mechanical Engineering - Torino

1st degree and Bachelor-level of the Bologna process in Mechanical Engineering - Torino

1st degree and Bachelor-level of the Bologna process in Industrial Production Engineering - Torino/Barcellona

1st degree and Bachelor-level of the Bologna process in Industrial Production Engineering - Torino/Nizza

Course structure

Teaching | Hours |
---|---|

Lezioni | 40 |

Esercitazioni in aula | 20 |

Teachers

Teacher | Status | SSD | h.Les | h.Ex | h.Lab | h.Tut | Years teaching |
---|---|---|---|---|---|---|---|

Maisano Domenico Augusto Francesco | Professore Associato | ING-IND/16 | 40 | 20 | 0 | 0 | 7 |

Teaching assistant

Context

SSD | CFU | Activities | Area context |
---|---|---|---|

ING-IND/16 | 6 | B - Caratterizzanti | Ingegneria meccanica |

2020/21

The course (which is compulsory for the Bachelor of Science in “Ingegneria della Produzione Industriale”) focuses on the major methodologies, good practices and tools for achieving Quality within industrial environments. Course objectives are:
• Stimulating student awareness of the concepts of Quality of a product/service and competition-oriented design.
• Describing the main techniques of Process Control and Acceptance Monitoring in the acquisition phase of semi-processed/raw-materials and during the introduction on the market of end-products/services.
• Stimulating capabilities of design and verification of the entire supply chain, starting from the market demand analysis, up to the policies of outsourcing/insourcing of facilities and support structures.
Real evidences of Quality practitioners and case studies will complement the course.

The course (which is compulsory for the Bachelor of Science in “Ingegneria della Produzione Industriale”) focuses on the major methodologies, good practices and tools for achieving Quality within industrial environments. Course objectives are:
• Stimulating student awareness of the concepts of Quality of a product/service and competition-oriented design.
• Describing the main techniques of Process Control and Acceptance Monitoring in the acquisition phase of semi-processed/raw-materials and during the introduction on the market of end-products/services.
• Stimulating capabilities of design and verification of the entire supply chain, starting from the market demand analysis, up to the policies of outsourcing/insourcing of facilities and support structures.
Real evidences of Quality practitioners and case studies will complement the course.

Knowledge of the major techniques for implementing Quality Management Systems, according to existing standards.
Mastery of tools and techniques to achieve Quality within industrial environments: FMECA (Failure Mode, Effects and Criticality Analysis), QFD (Quality Function Deployment), SPC (Statistical Process Control), etc..
At the end of the course, students will be able to operate in industrial environments in which Quality Management and SPC techniques are implemented.

Knowledge of the major techniques for implementing Quality Management Systems, according to existing standards.
Mastery of tools and techniques to achieve Quality within industrial environments: FMECA (Failure Mode, Effects and Criticality Analysis), QFD (Quality Function Deployment), SPC (Statistical Process Control), etc..
At the end of the course, students will be able to operate in industrial environments in which Quality Management and SPC techniques are implemented.

Essentials of Mathematical Analysis, Statistics and Production Technologies.

Essentials of Mathematical Analysis, Statistics and Production Technologies.

1. Preliminary concepts
Terms and definitions.
Introduction of Quality Management techniques in industry.
The importance of Quality in design and production.
Basic notions on Statistics.
2. Quality in design
Offered, expected and perceived Quality.
Quality Function Deployment (QFD).
Customer Requirements, Technical Characteristics and Relationship Matrix.
Prioritization of the Technical Characteristics.
FMECA (Failure Mode, Effects and Criticality Analysis).
Quality Costs.
3. Statistical Process Control (SPC)
Introduction to statistical methods for Quality control.
Variability and natural tolerance of the process.
Variability propagation and the Delta method.
Control charts for variables and attributes.
Operating Characteristic (OC) curves relating to control charts.
Design and construction of control charts.
Process Capability Ratios (PCRs).
Theory of inspection and acceptance sampling plans.
Sampling plans for attributes.
OC curves relating to sampling plans.
Design of sampling plans for attributes

1. Preliminary concepts
Terms and definitions.
Introduction of Quality Management techniques in industry.
The importance of Quality in design and production.
Basic notions on Statistics.
2. Quality in design
Offered, expected and perceived Quality.
Quality Function Deployment (QFD).
Customer Requirements, Technical Characteristics and Relationship Matrix.
Prioritization of the Technical Characteristics.
FMECA (Failure Mode, Effects and Criticality Analysis).
Quality Costs.
3. Statistical Process Control (SPC)
Introduction to statistical methods for Quality control.
Variability and natural tolerance of the process.
Variability propagation and the Delta method.
Control charts for variables and attributes.
Operating Characteristic (OC) curves relating to control charts.
Design and construction of control charts.
Process Capability Ratios (PCRs).
Theory of inspection and acceptance sampling plans.
Sampling plans for attributes.
OC curves relating to sampling plans.
Design of sampling plans for attributes

The central topics of the course will be illustrated through a number of complementary activities that will take place in the classroom and/or laboratory, including an optional group-project about the application of QFD and FMECA.
Other activities will cover:
• analysis of case studies and real-life testimonials from company managers;
• application of QFD and benchmarking techniques;
• construction and use of control charts and sampling plans.

The central topics of the course will be illustrated through a number of complementary activities that will take place in the classroom and/or laboratory, including an optional group-project about the application of QFD and FMECA.
Other activities will cover:
• analysis of case studies and real-life testimonials from company managers;
• application of QFD and benchmarking techniques;
• construction and use of control charts and sampling plans.

Apart from the course notes and documents distributed by the teacher, the following textbooks are recommended:
• Franceschini F., Advanced Quality Function Deployment, St. Lucie Press/CRC Press LLC, Boca Raton, FL, 2002.
• Montgomery D.C., Introduction to Statistical Quality Control, 7th Ed., J. Wiley, New York, 2012.
• Franceschini F., Galetto M., Maisano D., Mastrogiacomo L., Ingegneria della Qualità: Applicazioni ed Esercizi (III edizione, II ristampa). CLUT Editrice, Torino, 2019.
• Franceschini, F., Galetto, M., Maisano, D., Designing Performance Measurement Systems: Theory and Practice of Key Performance Indicators, Springer International Publishing, Cham, Switzerland, 2019.

Apart from the course notes and documents distributed by the teacher, the following textbooks are recommended:
• Franceschini F., Advanced Quality Function Deployment, St. Lucie Press/CRC Press LLC, Boca Raton, FL, 2002.
• Montgomery D.C., Introduction to Statistical Quality Control, 7th Ed., J. Wiley, New York, 2012.
• Franceschini F., Galetto M., Maisano D., Mastrogiacomo L., Ingegneria della Qualità: Applicazioni ed Esercizi (III edizione, II ristampa). CLUT Editrice, Torino, 2019.
• Franceschini, F., Galetto, M., Maisano, D., Designing Performance Measurement Systems: Theory and Practice of Key Performance Indicators, Springer International Publishing, Cham, Switzerland, 2019.

It is not necessary to change the usual method of preparation with respect to the classical exam. The exam will be organized in the form of a “quiz”, with a variety of problems and questions (roughly, between 5 and 10), trying to reproduce the classical configuration illustrated in class. Also, the typical topics are the same ones illustrated in class, i.e.:
a. Statistical Process Control;
a.0 Probability calculation and hypothesis testing;
a.1 Delta method;
a.2 Control charts;
a.3 Sampling plans;
b. Quality in design;
b.1 General notions;
b.2 Quality Function Deployment (QFD);
b.3 Failure Mode, Effects, and Criticality Analysis (FMECA).
The exam mainly consists of problems involving calculations, with the addition of some multiple-choice theoretical questions. In case of wrong answers to multiple-choice questions, penalties may be applied (e.g., -0.5 point); therefore, it is advisable to omit the answer in case of doubt, avoiding “random guessing”. Problems involving calculations are not “sequential”, just to avoid that calculation errors on the initial answers lead to a sort of “error propagation” on the subsequent answers.
Questions/problems are fully “customized”, both (1) in terms of numerical data for problems involving calculations and (2) in terms of order/combination for multiple-choice questions.
As in any normal exam, you can use paper, pen, tables, formulary and calculator.
A technical difficulty of the examination method is to fill in the answer boxes. Since any typing or rounding error may affect the correct outcome of your test, it is recommended to be very careful. In any case, appropriate "tolerance ranges" will be considered around the correct results, to take into account possible rounding errors.
For numerical answers, the platform accepts both “.” and “,” as decimal separator. Also, students must report the probabilities as numbers between 0 and 1 and not in percentage form (e.g., a probability of 2.5% should be reported as “0.025”, not “2.5%”).
For each problem/question, a score will be reported.
The total mark will obviously be 30 (plus the 2-point bonus related to the project work).
Even though the standard exam is an online quiz, the professor reserves the right to perform a supplemental oral exam. On the other hand, requests for oral examination by students will not be accepted.
For students who wish to do so, it will be possible to interact with the teacher during the exam through an optional Virtual Classroom, which can be activated after the beginning of the exam, pressing a dedicated button in the top-left corner of the quiz window, below the countdown.
After the publication of the result of the exam on the Teaching Portal, students are allowed to reject their positive mark by sending an e-mail to the teacher, before the mark-registration date (which will be announced later).
Finally, students are invited to carefully consider the rector's guidelines for online exams and the FAQs available on the course material.

The online exam will be organized in the form of a “quiz”, of about two hours, mainly consisting of problems involving calculations and multiple-choice theoretical questions. This quiz will be carried out through an e-learning platform (Exam) and monitored through a proctoring software (Respondus), provided by PoliTO to professors and students.
Exercises and theoretical questions will be "balanced" in order to ascertain the achievement of the learning outcomes, expected from the course.
It is not necessary to change the usual method of preparation with respect to the classical exam.
Students will use the material indicated by the professor – i.e., specific statistical tables and a free-formula sheet; lecture notes, books, manuals, or smartphones will be strictly forbidden.
During the course, students will also be involved in an optional teamwork project. In the case of positive evaluation, team members will gain 1 or 2 extra points. The maximum possible grade for the exam will be 30L, including the said extra points.
Even though the online exam is a quiz, the professor reserves the right to perform a supplemental oral exam. On the other hand, requests for oral examination by students will not be accepted.

It is not necessary to change the usual method of preparation with respect to the classical exam. The exam will be organized in the form of a “quiz”, with a variety of problems and questions (roughly, between 5 and 10), trying to reproduce the classical configuration illustrated in class. Also, the typical topics are the same ones illustrated in class, i.e.:
a. Statistical Process Control;
a.0 Probability calculation and hypothesis testing;
a.1 Delta method;
a.2 Control charts;
a.3 Sampling plans;
b. Quality in design;
b.1 General notions;
b.2 Quality Function Deployment (QFD);
b.3 Failure Mode, Effects, and Criticality Analysis (FMECA).
The exam mainly consists of problems involving calculations, with the addition of some multiple-choice theoretical questions. In case of wrong answers to multiple-choice questions, penalties may be applied (e.g., -0.5 point); therefore, it is advisable to omit the answer in case of doubt, avoiding “random guessing”. Problems involving calculations are not “sequential”, just to avoid that calculation errors on the initial answers lead to a sort of “error propagation” on the subsequent answers.
Questions/problems are fully “customized”, both (1) in terms of numerical data for problems involving calculations and (2) in terms of order/combination for multiple-choice questions.
As in any normal exam, you can use paper, pen, tables, formulary and calculator.
A technical difficulty of the examination method is to fill in the answer boxes. Since any typing or rounding error may affect the correct outcome of your test, it is recommended to be very careful. In any case, appropriate "tolerance ranges" will be considered around the correct results, to take into account possible rounding errors.
For numerical answers, the platform accepts both “.” and “,” as decimal separator. Also, students must report the probabilities as numbers between 0 and 1 and not in percentage form (e.g., a probability of 2.5% should be reported as “0.025”, not “2.5%”).
For each problem/question, a score will be reported.
The total mark will obviously be 30 (plus the 2-point bonus related to the project work).
Even though the standard exam is an online quiz, the professor reserves the right to perform a supplemental oral exam. On the other hand, requests for oral examination by students will not be accepted.
For students who wish to do so, it will be possible to interact with the teacher during the exam through an optional Virtual Classroom, which can be activated after the beginning of the exam, pressing a dedicated button in the top-left corner of the quiz window, below the countdown.
After the publication of the result of the exam on the Teaching Portal, students are allowed to reject their positive mark by sending an e-mail to the teacher, before the mark-registration date (which will be announced later).
Finally, students are invited to carefully consider the rector's guidelines for online exams and the FAQs available on the course material.

There will be no exams in BLENDED mode but exclusively in ONLINE mode, as described above.

© Politecnico di Torino

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY

Corso Duca degli Abruzzi, 24 - 10129 Torino, ITALY