Learning outcomes of the course unit
KNOWLEDGE AND ABILITY TO UNDERSTAND
At the end of the course, the student must have acquired the main knowledge related to the classification of production systems and the methods for (i) the calculation of their performance, (ii) the management of industrial production, in terms of programming, planning and control of production.
ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
Students must be able to autonomously plan the organization of operations as a whole, considering the main processes connected to it, defining the most suitable management policies in relation to the application context. The student must be able to use the knowledge acquired to analyse and process numerical data and to support the relevant decision-making choices.
Students must be able to critically evaluate a production system, starting from its classification and analysis of its performance; they must also be able to design, choose and implement a system for planning, programming and controlling production.
The student must acquire the specific vocabulary related to production management. It is expected that, at the end of the course, the student will be able to transmit, orally and in writing, also through the resolution of numerical problems, the main contents of the course (for example: MPS, MRP, MRP II and operational programming, etc.), also through the use of tools commonly used in the field, such as tables, block diagrams or flow diagrams.
Students who have attended the course will be able to deepen their knowledge in the field of production management in general, through independent consultation of specialist texts, scientific or popular journals, even outside the topics covered strictly in class.
No mandatory prerequisites.
Frequency and overcoming of lessons related to the design of production systems, mechanical technology and statistics are desirable.
Course contents summary
Managing the “production system” requires both direct experience gained in the field and knowledge, models, techniques and tools that have theoretical foundations and that hardly can be taken exclusively from the activity carried out in the field.
This course, starting from a methodical classification of the “production systems” and their performance analysis, aims to present the main models and techniques that can be used to address the processes of planning, programming and control of production including inventory management.
Part I: INTRODUCTION TO PRODUCTION SYSTEMS
1.1 - Definitions of production system and production process
1.2 - The classifications of the production processes
1.3 - Information on the logistics system
Part II: BASIC CONCEPT FOR THE MANAGEMENT OF PRODUCTION SYSTEMS
2.1 - Introduction
2.2 - Why measure the performance of a production system?
2.3 - Measuring performance within improvement processes: the check-up of the production system
2.4 - Measuring performance and operating conditions: classification models
2.5 - Measurement of operating conditions
2.6 - Measuring internal performance
2.7 - A brief outline of the design of a measuring system
2.9 - Costs for decisions
PART III: PRODUCTION-RELATED MANAGEMENT TECHNIQUES
4.1 - General concepts for stocks
4.2 - Material management
4.3 - Stock management
4.4 - The EOQ-ROP model (economic lot)
4.5 - The fixed interval reordering model
4.6 - The Maximum/Minimum Stock Model
4.7 - Stock efficiency measures
PART IV: NEEDS MANAGEMENT SYSTEMS
5.1 - The general framework of management systems based on needs
5.2 - Planning and forecasting demand
5.3 - Aggregate sales planning and capacity management
5.4 - Needs Planning (MRP)
5.5 - Notes on short term scheduling
1 ) Andrea IANESI, (2011), “La gestione del sistema di produzione”, Editore: Rizzoli Etas, ISBN-10: 8817068063; ISBN-13: 978-8817068062
Alberto F. DE TONI, Roberto PANIZZOLO, (2018) , “Sistemi di gestione della produzione”, Editore: ISEDI; ISBN-10: 8880083821; ISBN-13: 978-8880083825
Theory lessons alternated with numerical exercises and case studies.
Assessment methods and criteria
Examination written for both theory and numerical exercises.