86478 - Production Management and Optimisation

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Decent work and economic growth Industry, innovation and infrastructure Responsible consumption and production

Academic Year 2019/2020

Learning outcomes

The student learns the general criteria and methods aimed to the design and management of production systems.

Course contents

  • Introduction and Background (From Ford to Lean Manufacturing and Industry 4.0): Mass production; Lean Manufacturing Systems e Cell Design: Born and development of lean manufacturing; Waste reduction and cultural paradigm; Toyota Production System (TPS); Theorical methods for lean production; World Class Manufacturing; Introduction and principles to Industry 4.0.
  • Classification of Production Systems: Managment approach Entity-Method-Decision-Performance; Flow-shop, Job-shops, FMS, Cellular Manufacturing (CM): Supporting technologies and methods to CM; Clustering methods to Group Technology and CM; Industry 4.0 and smart manufacturing system.
  • Production System Design: Balancing of production mix and production volume; Design equipment and facilities as the number of production resources. Layout Design.
  • Production Management and Lot Sizing: Management system for stock and inventory planning; Economic order quantity and analytical models; Kan-Ban systems and Lean manufacturing for stock reduction.
  • Production Scheduling: Theory and Analytical models for industrial applications.
  • Methods for Analyzing and Optimising Production Systems: Queueing Theory, Simulation.
  • Analogic Methods for the Value Chain analysis: Mapping the value chain through Value Stream Mapping (VMS).

Readings/Bibliography

Dedicated bibliography covering the entire class programme will be uploaded step-by-step on AMS Campus platform. Specific info will be provided at the end of each lesson. Additional readings are available upon request (but they are not mandatory to pass this class).

Teaching methods

In presence.

The course is organized in frontal lectures in which the main topic are discussed and followed by numerical and practical applications. At the end of each topic, a training exercise is proposed and solved in class. Such approach underlines the applied nature of this discipline and aims at teaching the solving methodology beyond concrete problems from the industrial practice.

Lectures may include case studies and applications promoting active partecipation and interactions among the attendants.

Assessment methods

The final exam is a written paper made of numeric applications and open questions covering the entire class programme.

Part of the final score results from the partecipation of attendants and from assignments carried out in team of students.

Office hours

See the website of Riccardo Accorsi