This paper provides a comprehensive review of the literature, mostly of the last 10–15 years, that is enhancing our understanding of the mechanics of the rapidly growing field of micromachining. The paper focuses on the mechanics of the process, discussing both experimental and modeling studies, and includes some work that, while not directly focused on micromachining, provides important insights to the field. Experimental work includes the size effect and minimum chip thickness effect, elastic-plastic deformation, and microstructure effects in micromachining. Modeling studies include molecular dynamics methods, finite element methods, mechanistic modeling work, and the emerging field of multiscale modeling. Some comments on future needs and directions are also offered.

Plasticity theory aims at describing the yield loci and work hardening of a material under general deformation states. Most of its complexity arises from the nontrivial dependence of the yield loci on the complete strain history of a material and its microstructure. This motivated 3 ingenious simplifications that underpinned a century of developments in this field: 1) yield criteria describing yield loci location; 2) associative or nonassociative flow rules defining the direction of plastic flow; and 3) effective stress–strain laws consistent with the plastic work equivalence principle. However, 2 key complications arise from these simplifications. First, finding equations that describe these 3 assumptions for materials with complex microstructures is not trivial. Second, yield surface evolution needs to be traced iteratively, i.e., through a return mapping algorithm. Here, we show that these assumptions are not needed in the context of sequence learning when using recurrent neural networks, diverting the above-mentioned complications. This work offers an alternative to currently established plasticity formulations by providing the foundations for finding history- and microstructure-dependent constitutive models through deep learning.

No abstract

In this paper, a summary of work performed in the area of modeling of the dynamic metal cutting process is presented. A general view of evolution of the dynamic cutting process models is depicted. Specifically four modeling approaches including analytical, experimental, mechanistic and numerical methods are critically reviewed. A brief assessment of future research needs is also given.

Carbon fiber reinforced plastieslpolymers (CERPs) offer excellent mechanical properties that lead to enhanced functionat performance and, in turn, wide apptications in numerous industrial fietds. Post machining of CERPs is an essential procedure that assures that the manufactured components meet their dimensional tolerances, surface quality and other functional requirements, which is currently considered an extremely difficutt process due to the highly nonlinear, inhomogeneous, and abrasive nature of CERPs. In this paper, a comprehensive literature review on machining of CERPs is given with a focus on five main issues including conventionat and unconventional hybrid processes for CERP machining, cutting theories and thermatlmechanical response studies, numerical simulations, tool performance and tooting techniques, and economic impacts of CERP machining. Given the similarities in the experimental and theoretical studies retated to the machining of gtass fiber reinforced polymers (GERPs) and other ERPsparaltet insights are drawn to CERP machining to offer additionat understanding of on-going and promising attempts in CERP machining.