Volume 4 • Issue 1 • 1000111 Adv Automob Engg ISSN:2167-7670 AAE, an open access journal Open Access Review Article Manjunath Patel et al., Adv Automob Eng 2015, 4:1 DOI: 10.4172/2167-7670.1000111 Keywords: Forward and reverse modelling and optimization; Sof computing; Squeeze casting process; Statistical tools Abbreviations: ABC: Ant Bee Colony; ANFIS: Adaptive Network Fuzzy Interface System; BHN: Brinell Hardness number; BBD: Box Behnken Design; BPNN: Back Propagation Neural Network; CCD: Central Composite Design; DM: Die Material; DOE: Design Of Experiments; DP: Pressure Duration; DT: Die Temperature; FDM: Finite Diference Method; FEM: Finite Element Method; FFD: Full Factorial Design; FL: Fuzzy Logic; FVM: Finite volume Method; FV: Filling Velocity; GA: Genetic Algorithm; GA-FL: Genetic Algorithm Fuzzy Logic; GA-NN: Genetic Algorithm Neural Network; HTC: Heat Transfer Coefcient; HV: Vickers Hardness; MM: Morphological Matrix; NN: Neural Network; PSO: Particle Swarm Optimization; PT: Pouring Temperature; SA: Simulated Algorithm; SP: Squeeze Pressure; SR: Surface Roughness; TD: Time Delay; TLBO: Teacher Learning Base Algorithm; UTS: Ultimate Tensile Strength; YS: Yield strength Introduction In today’s competitive world industries are searching for light weight materials possess high strength to weight ratio with less defective processing methods. Tis drawn much attention towards the research to search for alternative processing method to limit the weakness of one technology with the strength of the other. Casting process considered being one among the most economical route to manufacture the automobile and aerospace components. Te most common problem with the conventional casting method is the probable occurrence of defects like shrinkage and the porosity. To overcome these limitations, researchers tried to integrate the immense features of economy and design fexibility of conventional casting process (pressure die casting and gravity) and strength and integrity of forging process. Tis integrated casting method is termed as squeeze casting which works based on the concept of pressurized solidifcation. Te investigations were carried out in castings with simple geometries by using either gap measurement method or heat conduction methods on heat transfer coefcients (HTC). However, it was observed that interfacial [1-15], processing methods [16-19], casting geometry and size [20,21], physical and chemical conditions [22], mold and casting material properties [23], process variables [24-28] and so on directly afect the HTC. Te combined efect of these factors infuences the HTC, thereby making it difcult to separate and study the main efects of the factors. It is to be noted that the HTC greatly infuences the mechanical and micro-structure properties. Although past few decades researchers\investigators tried to improve the mechanical and micro- structure properties, but it is under intensive study since the existence of the probable squeeze casting defects such as oxide inclusion, porosity, extrusion segregations, centre line segregations, sticking, cold laps, extrusion debonding, blistering, under fll, shrinkages, hot tearing and case deboning [29,30]. Te major parameters that afect the quality of the squeeze cast components such as squeeze pressure, pressure duration, time delay in pressurizing the metal, pouring temperature, die temperature, inoculants, flling velocity, lubrication type, flm thickness and its adherence, melt quality and quantity etc. It is understood that proper control of these parameters may eliminate the possible squeeze casting defects. Tere is no universal standards available to control the above said process variables to achieve the desired squeeze cast components. Hence in the present work discusses the steps followed by various researchers till date to optimize the squeeze casting process are discussed, the scope for future directions in squeeze casting process for achieving the desired results are to identifed through the trends in available literature and their main diferences with squeeze casting process. *Corresponding author: Manjunath Patel GC, Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal-575025, Karnataka, India, E-mail: manju09mpm05@gmail.com Received December 11, 2014; Accepted January 07, 2015; Published January 16, 2015 Citation: Manjunath Patel GC, Krishna P, Parappagoudar MB (2015) Modelling in Squeeze Casting Process-Present State and Future Perspectives. Adv Automob Eng 4: 111. doi:10.4172/2167-7670.1000111 Copyright: © 2015 Manjunath Patel GC, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Abstract The growing demand in today’s competitive manufacturing environment has encouraged the researchers to develop and apply modelling tools. The development and application of modelling tools help the casting industries to considerably increase productivity and casting quality. Till date there is no universal standard available to model and optimize any of the manufacturing processes. However the present work discusses the advantages and limitations of some conventional and non-conventional modelling tools applied for various casting processes. In addition the research effort made by various authors till date in modelling and optimization of the squeeze casting process has been reported. Furthermore the necessary steps for prediction and optimization are high lightened by identifying the trends in the literature. Ultimately this research paper explores the scope for future research in online control of the process by automatically adjusting the squeeze cast process parameters through reverse prediction by utilizing the soft computing tools namely, Neural Network, Genetic Algorithms, Fuzzy-logic Controllers and their different combinations. The present work also proposed a detailed methodology, starting from the selection of process variables till the best process variable combinations for extreme values of the outputs responsible for better product quality using experimental, prediction and optimization methodology. Modelling in Squeeze Casting Process-Present State and Future Perspectives Manjunath Patel GC 1 *, Krishna P 1 and Parappagoudar MB 2 1 Department of Mechanical Engineering, National Institute of Technology Karnataka, Surathkal, India 2 Department of Mechanical Engineering, Chhatrapati Shivaji Institute of Technology, Durg, Chhattisgarh, India Advances in Automobile Engineering A d v a n c e s i n A u t o m o b i l e E n g i n e e r i n g ISSN: 2167-7670