Abstract
Cutting temperature is an important factor which directly affects cutting tool wear, cutting tool life, machined surface quality, and accuracy in the high-speed machining (HSM) process. It is very important to study the distribution law of cutting temperature for the HSM process. In this paper, the self-developed embedded temperature measuring tool holder system (ETMTHS) is employed to measure the continuous temperature of carbide end milling tool tip. The dynamic temperature field model of solid cemented carbide milling cutter is established by using heat source method, and the heat flux in power series form is solved by using the particle swarm optimization (PSO) algorithm. At the same time, an optimization algorithm to solve the inverse problem of heat conduction is given. The solution of heat flux is converted into the solution of the optimal value problem. Using optimization algorithm, the inverse heat conduction problem can be solved successfully. The temperature and its gradient distribution of solid cemented carbide milling cutter are obtained by analyzing the continuous milling temperature of ANSYS simulation. The comparison results show a good agreement between the simulation temperature and measuring temperature.
Similar content being viewed by others
References
Abukhshim NA, Mativenga PT, Sheikh MA (2006) Heat generation and temperature prediction in metal cutting: a review and implications for high speed machining. Int J Mach Tools Manuf 46:782–800
Lezanski P, Shaw MC (1990) Tool face temperatures in high speed milling. J Eng Ind 112:132–135
O’Sullivan D, Cotterell M (2001) Temperature measurement in single point turning. J Mater Process Technol 118:301–308
Quan YM, Lin JP, Wang CY (2005) Cutting temperature measurement in high-speed end milling. Trans Nanjing Univ Aeronaut Astronaut 22(1):47–51
Toh CK (2005) Comparison of chip surface temperature between up and down milling orientations in high speed rough milling of hardened steel. J Mater Process Technol 167:110–118
Carlsaw HS, Jaeger JC (1959) Conduction of heat in solids. Oxford University Press, Oxford
Trigger KJ, Chao BT (1951) An analytical evaluation of metal cutting temperature. Trans ASME 73:57–58
Huang Y, Liang SY (2003) Cutting force modeling considering the effect of tool thermal property—applying to CBN hard turning. Int J Mach Tools Manuf 43:307–315
Chakravert G, Pandey PC, Mehta NK (1984) Analysis of tool temperature fluctuation in interrupted cutting. Precis Eng 6(2):99–105
Cheng H, Wang S (1999) A three-dimensional inverse heat conduction problem in estimating surface heat flux by conjugate gradient method. Int J Heat Mass Transfer 42(18):3387–3403
Frank I (1963) An application of least squares method to the solution of the inverse problem of heat conduction. J Heat Transfer 85(4):378–379
Lin J, Lee SL, Weng CI (1992) Estimation of cutting temperature in high speed machining. J Eng Mater Technol Trans ASME 114(3):289–296
Sivasakthivel PS, Sudhakaran R (2013) Optimization of machining parameters on temperature rise in end milling of Al 6063 using response surface methodology and genetic algorithm. Int J Adv Manuf Technol 67:2313–2323
Abukhshim NA, Mativenga PT, Sheikh MA (2005) Investigation of heat partition in high speed turning of high strength alloy steel. Int J Mach Tools Manuf 45:1687–1695
Majumdar P, Jayaramachandran R, Ganesan S (2005) Finite element analysis of temperature rise in metal cutting processes. Appl Therm Eng 25:2152–2168
Haddag B, Kagnaya T, Nouari M, Cutard T (2013) A new heat transfer analysis in machining based on two steps of 3D finite element modeling and experimental validation. Heat Mass Transf 49:129–145
Komanduri R, Hou ZB (2001) Thermal modeling of the metal cutting process—part III, temperature rise distribution due to the combined effects of shear plane heat source and the tool–chip interface frictional heat source. Int J Mech Sci 43:89–107
Hou ZB, He S, Li N (1984) Solid heat conduction. Shanghai Science and Technology Press, Shanghai
Beck JV, Blcakwell B, Clair SR (1985) Inverse heat conduction problems. Wiley, New York
Huang C, Wang S (1999) A three-dimensional inverse heat conduction problem in estimating surface heat flux by conjugate gradient method. Int J Heat Mass Transf 42(18):3387–3403
Deng S, Hwang Y (2006) Applying neural networks to the solution of forward and inverse heat conduction problem. Int J Heat Mass Transf 49(15/16):4732–4750
Ünal M, Ak A, Topuz V, Erdal H (2013) Optimization of PID controllers using ant colony and genetic algorithms. Springer, Berlin
Kennedy J, Eberhart R (1995) Particle swarm optimization. Proceeding of IEEE International Conference on Neural Networks
Eberhart RC, Shi Y (2001) Particle swarm optimization: developments, applications and resources particle swarm optimization. Proceeding of the 2001 Congress on Evolutionary Computation IEEE
Leshock CE, Shin YC (1997) Investigation on cutting temperature in turning by a tool-work thermocouple technique. J Manuf Sci Eng Trans ASME 119(4):502–508
Ning Y, Rahman M, Wong YS (2001) Investigation of chip formation in high speed end milling. Mater Process Technol 113(1–3):360–367
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wei, B., Tan, G., Yin, N. et al. Research on inverse problems of heat flux and simulation of transient temperature field in high-speed milling. Int J Adv Manuf Technol 84, 2067–2078 (2016). https://doi.org/10.1007/s00170-015-7850-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-015-7850-3