Technology
Subject: PRODUCTION MANAGEMENT AND OPTIMISATION (A.A. 2021/2022)
master degree course in ADVANCED AUTOMOTIVE ENGINEERING
| Course year | 2 |
|---|---|
| CFU | 6 |
| Teaching units |
Unit Production Management and Optimisation
To be chosen by the student (lesson)
|
| Moodle portal |
Aula virtuale su Microsoft Teams (immatricolati: 2020) in attesa di attivazione da parte del docente |
| Exam type | written |
| Evaluation | final vote |
| Teaching language | inglese |
Teachers
Overview
The student learns the general criteria and methods aimed to the production system planning, management and optimization. Students learn the general criteria and methods aimed at managing and optimizing production systems and operations improve their skills in developing decision-support tools for Industrial environments.
Admission requirements
A prior knowledge and understanding of industrial facilities and manufacturing system is recommended.
Course contents
- Introduction and Background: The evolution of Manufacturing systems from the Industrial Revolution to Industry 4.0 (and days ahead).
- Production System Design and Planning: Decisional framework based on Problem-Entity-Methods-Decisions-Performance; Classification of Manufacturing Problems and related Hierarchy: Resource Requirement Planning and Optimization problems, Materials Requirement Planning, Demand-driven Planning Methods (Push vs Pull approach), Stock-driven Planning Methods.
- 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; Lot-sizing Problems with deterministic and stochastic demand; News Vendor Problem and applications.
Production Optimization: Optimization techniques for manufacturing systems and resources.
- Production Scheduling: Uncapaciteated and Capacitated Scheduling methods for Production Systems; Theoretical and Analytical models for industrial applications and different production layout configurations.
- Design and Development of Decision Support Systems for Manufacturing Problems: Collection and management of Manufacturing data and records; Fundamentals of Object-Oriented Programming (Visual Basic); Excel Solver; Languages for Mathematical Programming and Optimization (AMPL).
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 comprehensive exercise is proposed and solved in class. Such an 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 applications promoting active participation and interactions among the attendants.
Assessment methods
The final exam lies on discussing a team-project based on developed Decision-support systems for manufacturing problems. Selfmade teams are made of 2 students. The project bases on an application written in Visual Basic and AMPL languages through the MS Excel Interface, and includes a paper document describing the rationale of the project, the model implemented, the input dataset, and the obtained results. Part of the final score results from the partecipation of attendants during class. Previous computer science skills are not necessary, whilst proactivity and curiosity are broadly encouraged.
Learning outcomes
The student learns the general criteria and methods aimed to the production system planning, management and optimization. Students learn the general criteria and methods aimed at managing and optimizing production systems and operations improve their skills in developing decision-support tools for Industrial environments.
Readings
Bibliografia e supporti allo studio verranno forniti durante lo svolgimento del corso tramite la piattaforma AMS Campus. Al termine di ogni lezione si forniranno ragguagli in merito. Testi aggiuntivi per approfondimenti sono disponibili su richiesta ed hanno carattere addizionale e di approfondimento