1st degree and Bachelor-level of the Bologna process in Ingegneria Della Produzione Industriale - Torino/Athlone 1st degree and Bachelor-level of the Bologna process in Ingegneria Meccanica (Mechanical Engineering) - Torino 1st degree and Bachelor-level of the Bologna process in Ingegneria Meccanica - Torino 1st degree and Bachelor-level of the Bologna process in Ingegneria Della Produzione Industriale - Torino/Barcellona 1st degree and Bachelor-level of the Bologna process in Ingegneria Della Produzione Industriale - Torino/Nizza
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.
In the preliminary part of the course, the professor will stimulate the students to fill any remaining gaps in the above-mentioned pre-requisites by proposing some exercises and pedagogical examples.
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.
Modalità di esame: Test informatizzato in laboratorio; Elaborato progettuale in gruppo;
Exam: Computer lab-based test; Group project;
...
The course materials will be taught through a series of lectures, in which classroom participation is strongly encouraged. The exam will be based on a written test, of about two hours, containing:
(i) exercises concerning SPC techniques;
(ii) theoretical open questions concerning the totality of the topics covered.
Exercises and theoretical questions will be "balanced" in order to ascertain the achievement of the learning outcomes, expected from the course.
Students will use the material indicated by the professor – i.e., specific statistical tables and a free-formula sheet; lecture notes, books, manuals, laptops, tablets 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 standard exam is written, 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.
Gli studenti e le studentesse con disabilità o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unità Special Needs, al fine di permettere al/la docente la declinazione più idonea in riferimento alla specifica tipologia di esame.
Exam: Computer lab-based test; Group project;
The ONSITE 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 preferably be carried out through an e-learning platform (Exam) provided by PoliTO to professors and students.The course materials will be taught through a series of lectures, in which classroom participation is strongly encouraged. The exam will be based on a written test, of about two hours, containing: (i) exercises concerning SPC techniques and (ii) theoretical open questions concerning the totality of the topics covered.
Exercises and theoretical questions will be "balanced" in order to ascertain the achievement of the learning outcomes, expected from the course.
Students will use the material indicated by the professor – i.e., specific statistical tables and a free-formula sheet; lecture notes, books, manuals, laptops, tablets 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 standard exam is written through the e-learning Exam platform, the professor reserves the right to (i) agree on alternative examination modes with students, should the need arise, or (ii) perform a supplemental oral exam. On the other hand, requests for oral examination by students will not be accepted.
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.