A.D. Jayal

MODELING OF WHITE AND DARK LAYER FORMATION IN HARD MACHINING OF AISI 52100 BEARING STEEL

In machining of hardened materials, maintaining surface integrity is one of the most critical requirements. Often, the major indicators of surface integrity of machined parts are surface roughness and residual stresses. However, the material microstructure also changes on the surface of machined hardened steels and this must be taken into account for process modeling. Therefore, in order for manufacturers to maximize their gains from utilizing hard finish turning, accurate predictive models for surface integrity are needed, which are capable of predicting both white and dark layer formation as a function of the machining conditions. In this paper, a detailed approach to develop such a finite element (FE) model is presented. In particular, a hardness-based flow stress model was implemented in the FE code and an empirical model was developed for describing the phase transformations that create white and dark layers in AISI 52100 steel. An iterative procedure was utilized for calibrating the proposed empirical model for the microstructural changes associated with white and dark layers in AISI 52100 steel. Finally, the proposed FE model was validated by comparing the predicted results with the experimental evidence found in the published literature.

A Framework of Product and Process Metrics for Sustainable Manufacturing

This paper presents a framework for developing comprehensive product and process metrics for sustainable manufacturing, using machined products and machining processes examples, and addressing all three aspects of the triple bottom line – environment, economy and society. The need for developing standardized metrics is discussed for the wider use of these metrics by different manufacturers. The occurrence of similar measurements in some of the metric categories indicates the potential and need for data sharing between product and process metrics. The differences, relationships, and potential interactions between the product and process metrics are discussed from the viewpoint of their applications.

Priority Evaluation of Product Metrics for Sustainable Manufacturing

This chapter presents a framework to develop comprehensive product metrics for sustainable manufacturing and perform a priority evaluation of the metrics. Recent efforts made in this direction produced a large number of influencing factors and metrics for sustainable manufacturing. It is difficult to evaluate the sustainability content of a product with a large set of metrics and there is a need to prioritize these as per the requirements of different industrial segments. The use of analytic hierarchy process to prioritize the influencing factors for electronic products is illustrated through a case study. The development of product ontology is urged as a prerequisite to the ultimate solution for product manufacturers.

Finite Element Modeling of Microstructural Changes in Hard Turning

The material grain size changes significantly during machining of hardened steels, and this must be taken into account for improved modeling of surface integrity effects resulting from machining. Grain size changes induced during orthogonal cutting of hardened AISI 52100 (62 HRC) are modeled using the Finite Element (FE) method; in particular, a user subroutine involving a hardness-based flow stress model is implemented in the FE code and empirical models are utilized for describing the phase transformation conditions to simulate formation of white and dark layers. Furthermore, a procedure utilizing the Zener-Hollomon relationship is implemented in the above-mentioned user subroutine to predict the evolution in material grain size at different cutting speeds (300, 600, 900 SFPM). All simulations were performed for dry cutting conditions using a low CBN-content insert (Kennametal KD050 grade, ANSI TNG-432 geometry). The model is validated by comparing the predicted results with experimental evidence available in the literature.

Product and Process Innovation for Modeling of Sustainable Machining Processes

Sustainability is recognized as the driver for innovation. However, there is a critical need for improved sustainability evaluation methods, as well as for improved predictive models and optimization methods, to aid decision-making and selection of novel product and process designs for sustainable manufacturing. In the case of machining, increased awareness of the need for sustainability in manufacturing operations has led to significant research in advancing with new and more sustainable processes such as dry, near-dry and cryogenic machining. This paper presents an overview of product and process sustainability evaluation methods and modeling techniques, including analytical, empirical and computational methods, as well as optimization procedures, developed for predicting the performance of sustainable machining processes and major sustainability elements in machined products. The paper also highlights the technological challenges involved, and the future work needed, in developing comprehensive predictive models and optimization techniques for sustainable machining.

A Total Life-Cycle Approach towards Developing Product Metrics for Sustainable Manufacturing

manufacturing including the triple bottom line: environment, economy and society. The developed generic metrics are grouped under different metrics clusters, and are categorized across the four life-cycle stages (pre-manufacturing, manufacturing, use and post-use) of a product. This gives an opportunity to develop a leveling system for the metrics based on the presence of different metrics across multiple life-cycle stages. The development and deployment of relevant product metrics ontology is shown as a prerequisite for the ultimate evaluation and improvement in product design for sustainable manufacturing.

Dry vs. Cryogenic Orthogonal Hard Machining: an Experimental Investigation

Friction, and consequently heat generation in the cutting zone, significantly affects the tool life, surface integrity and dimensional accuracy, apart from other machining results. Application of a coolant in a cutting process can increase tool life and dimensional accuracy, decrease heat generation, and consequently cutting temperatures, reduce surface roughness and the amount of energy consumed in cutting process, and thus improve the productivity. Furthermore, coolant application also affects the surface microstructural alterations (i.e., white and dark layers) due to a machining operation, which have a significant influence on product performance and life. This paper presents the results of an experimental investigation to determine the effects of cryogenic coolant application on tool wear, cutting forces and machined surface alterations during orthogonal machining of hardened AISI 52100 bearing steel (54±1 HRC). Experiments were performed for dry and cryogenic cutting conditions using chamfered PCBN ...