The study addresses sustainable manufacturing, focusing of efficiency management in machine tools. A novel approach to energy modelling and machining cycle optimization is introduced. It uses a hierarchical optimization approach, splitting machining cycles into smaller, independent tasks. The analysis starts at the level of workpiece design features, for which a variety of state-of-the-art energy models can be used to link process and machine tool parameters to the resulting energy use. The Pareto front resulting from local optimization of each feature is represented by functions relating execution time and the corresponding minimal energy consumption. This reduced information is passed to the higher levels of the task tree, up to processing units (in multi-spindle machines) and machine level. Propagation is performed through local optimizations of serial or parallel execution of the underlining tasks: under the specified assumptions, the merging process does not affect the global optimality of the solution. This approach strongly reduces problem dimension, allowing to postpone at machine level the optimal selection of all processing parameters. The proposed approach is therefore applicable to system wide analysis of multi-machine manufacturing systems, where machine and system level decisions are tightly coupled. A case study of an industrial flexible transfer machine, on which the developed methodology was applied, is analysed and discussed.

Hierarchical modelling framework for machine tool energy optimization

Wójcicki, Jeremi;Bianchi, Giacomo;Tolio, Tullio
2018

Abstract

The study addresses sustainable manufacturing, focusing of efficiency management in machine tools. A novel approach to energy modelling and machining cycle optimization is introduced. It uses a hierarchical optimization approach, splitting machining cycles into smaller, independent tasks. The analysis starts at the level of workpiece design features, for which a variety of state-of-the-art energy models can be used to link process and machine tool parameters to the resulting energy use. The Pareto front resulting from local optimization of each feature is represented by functions relating execution time and the corresponding minimal energy consumption. This reduced information is passed to the higher levels of the task tree, up to processing units (in multi-spindle machines) and machine level. Propagation is performed through local optimizations of serial or parallel execution of the underlining tasks: under the specified assumptions, the merging process does not affect the global optimality of the solution. This approach strongly reduces problem dimension, allowing to postpone at machine level the optimal selection of all processing parameters. The proposed approach is therefore applicable to system wide analysis of multi-machine manufacturing systems, where machine and system level decisions are tightly coupled. A case study of an industrial flexible transfer machine, on which the developed methodology was applied, is analysed and discussed.
Machine tool, Sustainable manufacturing, Energy efficiency, Multi-objective optimization
File in questo prodotto:
File Dimensione Formato  
Hierarchical modelling framework for machine tool energy optimization.pdf

Accesso riservato

: Publisher’s version
Dimensione 2.21 MB
Formato Adobe PDF
2.21 MB Adobe PDF   Visualizza/Apri

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

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1064240
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 7
  • ???jsp.display-item.citation.isi??? 4
social impact