A novel method for energy efficiency evaluation to support efficient machine tool selection. (1st August 2018)

• Record Type: Journal Article
• Authors: Liu, Peiji; Tuo, Junbo; Liu, Fei; Li, Congbo; Zhang, Xicheng
• Is Part Of: Journal of cleaner production. Volume 191(2018)
• Page Start: 57
• Page End: 66
• Publication Date: 2018-08-01
• Subjects: Energy efficiency -- Machine tools -- Machine tool selection -- Procurement; Factory and trade waste -- Management -- Periodicals; Manufactures -- Environmental aspects -- Periodicals; Déchets industriels -- Gestion -- Périodiques; Usines -- Aspect de l'environnement -- Périodiques; 628.5
• DOI: 10.1016/j.jclepro.2018.04.204
• Languages: English
• ISSNs: 0959-6526

Abstract

Abstract: Increasing energy price and emission limitations are new challenges faced by manufacturers; above half of their energy consumption is attributed to the electricity consumption of machine tools (MT), highlighting the need for manufacturers to select highly efficient MT. However, due to the unavailability of cutting tests and limited information in procurement stage, it is difficult to apply existing methods to evaluate the energy efficiency of MT options to support efficient MT selection. To address this problem, an energy efficiency model characterizing the relationship among energy efficiency, MT-related factors and workpiece-related factors is established to bridge the knowledge gap and a novel method without any cutting tests is developed including three steps: (i) modelling MT-related factors of each MT option; (ii) modelling workpiece-related factors of expected tasks; (iii) energy efficiency calculation and comparison. Furthermore, a selection example of gear-hobbing machine illustrates the application of the proposed method, reducing 2.88E+06 kJ energy consumption per selected MT per year. This study enables manufacturers to select MT for energy efficiency maximisation with the consideration of expected tasks in procurement stage. Highlights: A method for energy efficiency evaluation in machine-tool procurement stage is proposed. The evaluation model based on the available data in procurement stage is established. The workpiece diversity and process uncertainty is considered in this method. This method, without any cutting tests, has a higher practicability in procurement stage. This method is able to provide decision-making support for manufacturers to select efficient machine tools.