The optimization of machining processes is of paramount significance because of its pivotal role in modern manufacturing. Efficient machining techniques not only enhance product quality but also reduce costs and environmental impacts. This study focuses on the experimental characterization of energy consumption in a 5-axis milling machine and the simulation of possible solutions to reduce it. The first step is to understand the key drivers of energy consumption which is crucial for enhancing energy management and optimization. This was achieved by developing a mathematical model that uses the most common machining parameters as input using a Response Surface Methodology experimental test plan and an analysis of the contributions of the auxiliary systems to the overall energy consumption. As a second step, the effectiveness of different solutions was simulated considering different application scenario, like the type of operations. Such solutions include the introduction of duty cycle strategies for some auxiliary systems and the optimization of process parameters.

Experimental characterization of energy consumption in 5-axis milling machine and developing optimization strategy / Maurya, Sunil Kumar; Campatelli, Gianni; Veracini, Massimo. - ELETTRONICO. - 122:(2024), pp. 1024-1029. (Intervento presentato al convegno 31st CIRP Conference on Life Cycle Engineering (LCE 2024) tenutosi a Torino nel Giugno 2024) [10.1016/j.procir.2024.01.138].

Experimental characterization of energy consumption in 5-axis milling machine and developing optimization strategy

Maurya, Sunil Kumar
;
Campatelli, Gianni;
2024

Abstract

The optimization of machining processes is of paramount significance because of its pivotal role in modern manufacturing. Efficient machining techniques not only enhance product quality but also reduce costs and environmental impacts. This study focuses on the experimental characterization of energy consumption in a 5-axis milling machine and the simulation of possible solutions to reduce it. The first step is to understand the key drivers of energy consumption which is crucial for enhancing energy management and optimization. This was achieved by developing a mathematical model that uses the most common machining parameters as input using a Response Surface Methodology experimental test plan and an analysis of the contributions of the auxiliary systems to the overall energy consumption. As a second step, the effectiveness of different solutions was simulated considering different application scenario, like the type of operations. Such solutions include the introduction of duty cycle strategies for some auxiliary systems and the optimization of process parameters.
2024
31st CIRP Conference on Life Cycle Engineering (LCE 2024)
31st CIRP Conference on Life Cycle Engineering (LCE 2024)
Torino
Giugno 2024
Goal 9: Industry, Innovation, and Infrastructure
Goal 12: Responsible consumption and production
Maurya, Sunil Kumar; Campatelli, Gianni; Veracini, Massimo
File in questo prodotto:
File Dimensione Formato  
1-s2.0-S2212827124001859-main-3.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: Open Access
Dimensione 699.35 kB
Formato Adobe PDF
699.35 kB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1385599
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? ND
social impact