| KEYWORD |
Gestione del know-how produttivo attraverso l'integrazione tra il Manufacturing Execution System e il sistema PLM.
Tesi esterna in azienda
Parole chiave INDUSTRY 4.0, MACHINE LEARNING, AI, PLM
Riferimenti GIULIA BRUNO, PAOLO CHIABERT, FRANCO LOMBARDI
Gruppi di ricerca Gestione della conoscenza nello sviluppo prodotto/processo
Tipo tesi SYSTEM ANALYSIS AND SIMULATION
Descrizione Product Lifecycle Management (PLM) is the organizational process that allows the management of products throughout their entire life cycle. The main objective of PLM is to support people, data and procedures involved in product development, production and after-sales services so that the entire value chain and the quality of the product are under control. Nowadays, particular attention is paid to OKPs (One-of a-Kind Products) which still have high development costs despite new technological processes (rapid prototyping, additive manufacturing, etc.). Improving product quality and process reliability requires maximizing collaboration between the players involved.
In this framework, the development of work cycles and production tools, including the adaptation of product characteristics and functional requirements, is a fundamental step in the development phase of an OKP.
The purpose of the thesis is focused on this step, where manufacturing companies reuse their know-how to adapt the quality and costs of a new product (OKP) to the facilities available in the factory (in-door) or at suppliers.
In particular, the thesis will address a case study in the automotive field with the aim of developing an intelligent system, based on the integration between the PLM logic and a MES platform, so as to:
- acquire production experiences, classifying and archiving related data and models,
- make this information available and usable in the various stages of product development,
- program the cycles and production activities, internal and external, in accordance with the established deadlines.
Previous knowledge (preferably): production planning and control; Process simulation.
Scadenza validita proposta 29/09/2021
PROPONI LA TUA CANDIDATURA