Estimation of a Moving Heat Source due to a Micromilling Process Using the Modified TFBGF Technique

Gupta

et al. 2023

WJE

Purpose Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls. Design/methodology/approach Response surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization. Findings SR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized. Originality/value The GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.

Section: Introductionmentioning

confidence: 99%

A novel hybrid approach GREG-fuzzy-GA for minimizing work piece temperature during 2.5D milling of Inconel625 super alloy

Gupta

et al. 2023

WJE

Journal of Thermal Engineering

“…In recent past, many researchers have applied analytical modelling techniques to estimate the various responses such as thermal stresses (19) (20), heat transfer (21), tool and chip temperature (22) (23), work piece temperature (4) (12) (24), cutting force (6) (25) and face milling temperature(26). In these techniques, very few experiments are required to be performed just for validation of the technique.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, analytical modelling is found more suitable for estimation of responses in the manufacturing of dies and mould manufacturing as these components are manufactured in small size production. In the analytical modelling technique, complex differential equations are required to be solved with the help of various approaches like Green's function (20) (23) (24) (28) (29), moving heat source method (27) Finite difference method (30), Kommanduri and Huang-Liang (31), finite element method (32) and theories like Oxley's theory (33) and inverse heat conduction theory (30) provided by researchers in the recent past. The Separation of variable method has also been used by most researchers for solving non Fourier heat transfer problem (34) (35).…”

Section: Introductionmentioning

confidence: 99%

“…Liu et al 2014 (28) presented a Green's function approach for solving two types of heat sources that is described using the Dirac delta function in helical milling. According to Ribeiro et al 2018 (24), a Green's function approach is a better technique for the estimation of the heat and work piece temperature without use of optimization technique. We only observe nearby values in simulation work such as FEM analysis, but a mathematical technique such as Green's function gives the exact value at the specific point of moving heat source.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Empirical modelling for work piece temperature during end milling of inconel 625 using a green’s function approach based on dirac delta function

Kumar¹,

CHANDNA²,

Bhushan³

2021

Milling is a very versatile process for the manufacturing of dies and aerospace components. Especially in the manufacturing of thin walled components, the dimensional accuracy is greatly affected due to heat generation and deflection in the wall. Therefore, minimization of heat generation during milling by optimizing controllable input process parameters, leads to improved accuracy in thin walls. In the present study, an empirical model for work piece temperature by solving the non-homogeneous partial differential equation using Green's function has been simplified with Dirac delta approach during the end milling of Inconel625 work-piece with the assumption of single-pass cutting and one-point observation. This technique is normally used for solving the complex higher-order partial differential equation, but it is rarely applied in the heat dissipation problem during manufacturing in the recent past. The empirical approach is more effective and accurate as compared to experimental approaches used earlier in the recent past. To verify the adequacy of the empirical model of work piece temperature, 9 conformational experiments have been performed at 3 different cutting speeds with a constant depth of cut 5 mm and feed per tooth 0.05 mm. A good compromise has been observed among the responses obtained among the results obtained from an empirical approach and experimental observations at different cutting speeds. However, by little modification and adding a small algorithm, this single pass problem can be implemented on the multi-pass problems and even can also be applied to complex shapes.

“…Kondratiev's regular regime theory is used to tobtain a relation between convective coefficient and process variables. Ribeiro et al (2018) studied about the heat generated in the work piece during a micromilling process. He used the Greens theorem along with the Fourier transform for the mathematical modelling of the system.…”

mentioning

confidence: 99%

Impact of instantaneous curvature on force and heat generation in manufacturing processes – a mathematical modelling

Sreerag

Gokul

Vinaykumar

et al. 2020

Purpose In any machining process, the surface profile of the workpiece is continuously changing with respect to time and input parameters. In a conventional machining process, input parameters are feed and depth of cut whilst other parameters are considered to be constant throughout the process. Design/methodology/approach The direct and indirect participation of this instantaneous curvature can be used to optimize the strategy of cutting operation in terms of different parameters like heat generation-induced stresses, etc. The concepts of the metric tensor and Riemannian curvature tensor are made use in this study as a representation of curvature itself. The objective of this study is to create a mathematical methodology that can be implemented on a highly flexible machining process to find an optimum cutting strategy for a particular output parameter. Findings The study also includes different case studies for the validation of this newly introduced mathematical methodology. Originality/value The study will also find its position in other mechanical processes like forging and casting where instantaneous curvature affects various mechanical properties.