No formal requirements,
*but* knowledge about Statistics is required to understand most topics in this course.
Why Quality Management?
'per se' (*main educational goals*):
- learn basics about Quality Systems;
- study cases of Statistical Process Control;
for its educational content (for use in the near future, note that Quality tasks are often given as an entry level job):
- multi-functional (good viewpoint over a Firm);
- useful (to comply with Quality Standards);
- awkward (sometimes Quality is felt like a nuisance).
- introduction: definition of "Quality", brief history of Quality, basics on Statistics;
- the "7 quality tools": check sheet, histogram, Pareto chart, cause and effect diagram, correlation diagram, stratification, control charts;
- special focus on control charts : c. for variables x-R, x-S, x-MR, cusum; c. for attributes p, np, u, c;
- sampling: OC curves, sampling types, indexes ATI, ASN, AQL, AOQ;
- standards (overview): guidelines, q. assurance, q. manual and procedures, audit, product traceability;
- not included in this course: ANOVA, DOE, FMEA (covered by the course «Gestione Industriale della Qualita’ 2»).
- course slides (as PDF)
- D.C. Montgomery, Introduction to Statistical Quality Control, John Wiley & S. (also in Italian, Controllo statistico della qualita’, McGraw Hill).
Other suggested readings (in Italian):
- K. Ishikawa, Guida al controllo di qualita’, Angeli (popular in Italy);
- W.S. Messina, Il controllo statistico di qualita’ per il responsabile di produzione, Francoangeli;
- G.Vicario, R.Levi, Vicario, Calcolo delle probabilita’ e statistica per ingegneri, Prog. Leonardo ed. (some interesting topics for further reading on Statistics, not available in our library).
lessons and numerical laboratories
written and oral tests
no mid-term ('in itinere') tests are planned