This paper provides a comprehensive review of literature, mostly of the last 10–15 years, on modeling of machining of composite materials with a focus on the process of turning. The paper discusses modeling of both fiber reinforced and particle reinforced composites. Modeling studies include molecular dynamic simulations, 2-D and 3-D finite element models and the emerging field of multi-scale models. In fiber reinforced composites the focus is on glass and carbon fiber reinforced polymeric composites as well as long fiber reinforced metal matrix composites. On the other hand modeling of particulate composites is restricted to that of metal matrix composites (MMC). The paper includes recent modeling work to predict cutting forces, tool–particle interaction, cutting temperatures and machined sub-surface damage. A case study on the machining of the MMC A359 aluminum matrix composite reinforced with 20% by volume fraction silicon carbide particles is included to showcase the hierarchical multi-scale machining model.

Modeling of machining of composite materials: A review

Preparation and some properties of SiC particle reinforced aluminium alloy composites

Evaluation of tool wear when machining SiCp-reinforced Al-2014 alloy matrix composites

Tool wear acceleration in relation to workpiece reinforcement percentage in cutting of metal matrix composites

Metal matrix composites (MMC) have become a leading material among composite materials, and in particular, particle reinforced aluminum MMCs have received considerable attention due to their excellent engineering properties. These materials are known as the difficult-to-machine materials because of the hardness and abrasive nature of reinforcement element-like silicon carbide particles (SiCp). In this study, an attempt has been made to model the machinability evaluation through the response surface methodology in machining of homogenized 20% SiCp LM25 Al MMC manufactured through stir cast route. The combined effects of four machining parameters including cutting speed (s), feed rate (f), depth of cut (d), and machining time (t) on the basis of two performance characteristics of flank wear (VBmax) and surface roughness (Ra) were investigated. The contour plots were generated to study the effect of process parameters as well as their interactions. The process parameters are optimized using desirability-based approach response surface methodology.

O. Quigley

Papers

Factors affecting the machinability of an Al/SiC metal-matrix composite