Multi Objective Optimization for Sustainable Manufacturing, Application in Turning

Hassine, Hichem; Barkallah, Maher; Bellacicco, Alain

doi:10.2507/ijsimm14(1)9.292

Cited by 25 publications

(13 citation statements)

References 19 publications

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“…It would be reasonable to improve the evolution process of the proposed solution in order to reduce the time exactness of the algorithm; so the system would also become suitable for solving complex products with free surfaces. In the future, it would also be reasonable to test the system's operation with other multi-criterion optimisation methods, such as the multiobjective particle swarm optimiser [34].…”

Section: Resultsmentioning

confidence: 99%

Intelligent CAD/CAM System for Programming of CNC Machine Tools

Klančnik¹,

Brezočnik²,

Balič³

2016

Int. j. simul. model.

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This paper suggests the automated programming of CNC-machine tools with the help of artificial intelligence. Based on a CAD-model of the product, the system, without any help from an expert, automatically prepares a CNC program, so that the machining is safe, accurate and time-efficient. The developed CAD/CAM system uses NSGA-II multi-objective optimisation and swarm intelligence. The system consists of a prediction and evaluation module. In a prediction module artificial intelligence suggests solutions that include information about tool path, selected tools and suggested cutting parameters. The evaluation module estimates the suggested solutions by considering the geometrical, technological and time criteria, and the criterion of efficiency of machining. A simulation model was developed for searching optimal solutions. In this paper, the developed system is experimentally tested using a test case of manufacturing. The test results confirmed that with the help of this method of artificial intelligence, machine tools can be automatically programmed.

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Section: Resultsmentioning

confidence: 99%

Intelligent CAD/CAM System for Programming of CNC Machine Tools

Klančnik¹,

Brezočnik²,

Balič³

2016

Int. j. simul. model.

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“…Hassine et al [10] presented a further multiobjective optimization in turning. The objective functions of their case study were to minimize production time, cost, and energy consumption.…”

Section: Application Of a Force Model Adapted For The Precise Turningmentioning

confidence: 99%

Application of a Force Model Adapted for the Precise Turning of Various Metallic Materials

Horváth

Lukacs

2017

SV-JME

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The cutting force has a significant effect on the geometry and tolerances (e.g. circularity, deviation of circular shape or cylindricity, ovality, conical surfaces) of the workpiece (especially in the case of thin and slim parts), which are key criteria for the products. Moreover, they also affect the tool wear process. Due to the development of technology, the new tool (coatings) and workpiece materials require the exact knowledge of the cutting forces, their investigation during turning is an important field of cutting studies. In the case of turning, the kinetic conditions of which can be seen in Fig. 1, a spatial force system is generated.A new frictional model was constructed by Rusinek et al.[1] in case of orthogonal cutting that took the forces acting on the tool face as well as on the tool flank into consideration. Furthermore, the influence of the tool flank forces on system dynamics was studied.The mathematical modelling of cutting processes can be based on two methods: creating mechanical or phenomenological models. In recent years, several researchers have investigated the machinability of different types of materials, dealt with optimizing, measuring, and calculating cutting forces. The investigation of the machinability of different types of steel is still a basic field of cutting studies.Kulkarni et al.[2] carried out cutting tests on AISI304 austenite stainless steel by using AlTiCrN coated inserts. In their experimental runs, the depth of cut was held at a constant value (a p = 1 mm), the limits of the other cutting parameters were v c = 140 m/min to 320 m/min; f = 0.08 mm to 0.26 mm. The generated forces and the cutting temperature were studied. They said that regarding the force components, the effect of the feed was the most significant; however, the influence of cutting speed was negligible. In contrast, • Novel geometric parameters of the chip cross-section were introduced. Application of a Force Model Adapted for the Precise Turning of Various Metallic Materials• The main values of specific cutting forces characterizing fine turning technology were theoretically calculated.• The applicability of the equations for each material used was investigated by residuals.

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“…Rao and Rai [10] used teaching-learning-based optimization (TLBO) algorithm and non-dominated Sorting TLBO for FDM optimization procedure. Further, in study [11], multi objective optimization was used for sustainable manufacturing. Threedimensional statistical approach for determining the manufacturing tolerances has been used in study [12].…”

Section: Introductionmentioning

confidence: 99%