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The IC chip-ejecting and pick-up process plays a critical role in advanced packages since the success ratio and productivity are determined by the delamination of the chip-on-substrate structure. The paper investigates analytically the interfacial peeling mechanism of a chip-on-substrate structure subjected to a transverse concentrated load resulting from ejecting needle from the fracture mechanics point of view. The effects of key factors, including chip size, initial crack length, and substrate material, are uncovered. Finite element calculations are performed to obtain the interfacial peeling energy-release rate by using virtual crack-closure technique with dummy nodes. Analytical formulas and numerical results match fairly well for the entire range of the chip length and the crack length. It is shown that the greater the ratio of length to thickness of the chip is, the smaller the energy-release rate is, and length is the more important factor than thickness to affect the peeling. It implies the interfacial peeling gets tougher for thin or big chips during the pick-up process. Second, as the crack grows, the peeling energy-release rate increases. Third, the softer the substrate is, the greater the peeling energy-release rate is under the action of a constant transverse load. For the pick-up of thin or big chips, in order to achieve high success rate and suppress damage to the chip, it is suggested that more compliant and thinner substrate be adopted, weaker adhesive strength be chosen, and multiple needles be used. [ABSTRACT FROM AUTHOR]

Tool path generation is an interesting and challenging task in free-form surface machining. Iso-planar tool path generation is one of the common approaches to dealing with this task. However, it suffers from an inherent drawback that intersecting intervals of the iso-planar method are limited to surface geometric features. This results in poor machining efficiency in flat regions due to redundant machining paths. For this problem, a new tool path generation method for triangular meshes is proposed based on the least-squares conformal map (LSCM). After LSCM parameterisation with minimal stretching energy, the triangular meshes are unfolded on a plane, where the principal component analysis (PCA) technique is employed to determine a suitable drive line for calculating cutter contact paths by the iso-planar strategy. Therefore, the tool paths are generated in a plane and the unevenness of the traditional iso-planar method is improved. The feasibility and effectiveness of the developed method is demonstrated through a test experiment. [ABSTRACT FROM AUTHOR]

Byline: Yu Liu, ZhouPing Yin, YouLun Xiong Curvatures and the Darboux frame are useful tools for surface classification and 3D object recognition. However, it is still challenging for estimating these features on unorganised noisy points. A method is proposed to calculate these features from a general quadric surface fitted at each point. The TLS3L (total least squares on the three level sets) algorithm is introduced to permit fast, repeatable, and reliable fitting to the noisy input. The efficiency of the estimation is analysed theoretically and examined on several synthetic as well as real data sets. Comparative tests indicate that the proposed method excels the competitive ones.

It is increasingly crucial for flexible electronics to efficiently and reliably peel large-area, ultra-thin flexible films off from rigid substrate serving as substrates of flexible electronics device, especially in industrial production. This paper experimentally investigated the mechanism and technologic characteristics of laser lift-off (LLO) process of ultra-thin (~ 2 μm) polyimide (PI) film. It was found increasingly difficult to obtain desirable ultra-thin PI film by LLO with the decrease of the film thickness. The optimal process parameters were achieved considering laser fluence and accumulated irradiation times (AIT), which were found to be strongly correlative to the thickness of PI film. The process mechanism of LLO of PI film was disclosed that laser ablation of interfacial PI will result in the formation of gas products between the PI and glass substrate, enabling the change of interface microstructures to reduce the interface bond strength. The amount of gas products mainly determines the result of LLO process for ultra-thin PI film, from residual adhesion to wrinkles or cracking. The strategy of multi-scanning based on multiple irradiations of low-energy laser pulses was presented to effectively achieve a reliable LLO process of ultra-thin PI film. This study provides an attractive route to optimize the LLO process for large-scale production of ultra-thin flexible electronics. [ABSTRACT FROM AUTHOR]

In this paper, the non-uniformly distributed and time-varying heat flux at the tool-chip interface of a turning tool was estimated on-line based on the solution of an inverse heat conduction problem (IHCP),using temperatures measured by thin film thermocouples. A sequential Tikhonov regularization method (STRM) is proposed to solve the IHCP, which predicts the heat flux distribution both temporally and spatially and shows superiority in on-line estimation due to its high computational efficiency and independence of future measurements. To deal with the thermal model’s non-linearity, the finite element method (FEM) was adopted to solve the direct heat conduction problem of the tool and obtain sensitivity coefficients needed in the STRM. Thin film thermocouples deposited in micro-grooves at the rake face of a tool insert was used to measure temperatures close to the tool-chip interface with high response characteristic. To analysis the heat flux distribution spatially, the shape of the tool-chip contact area was measured and discretized for each different cutting condition. Numerical tests were carried out to verify the effectiveness and robustness of the STRM. Experimental cutting tests on Ti-6Al-4V titanium alloy were done to validate the thermal model and method. Based on the proposed algorithm and model, the detailed heat flux distribution and variation at the tool-chip interface for different cutting condition can be successfully determined on-line. [ABSTRACT FROM AUTHOR]

Quantile regression, which estimates various conditional quantiles of a response variable, including the median (0.5th quantile), is particularly useful when the conditional distribution is asymmetric or heterogeneous or fat-tailed or truncated. Bayesian methods for the inference of quantile regression have been receiving increasing attention from both theoretical and empirical viewpoints but facing the challenge of scaling up when the data are too large to be processed by a single machine under many big data environments nowadays. In this paper, we develop a structure link between Bayesian scale mixtures of normals linear regression and Bayesian quantile regression (B Q R) via normal-inverse-gamma (N I G) distribution type of likelihood function, prior distribution and posterior distribution. We further explore the detailed methods of B Q R for big data, variable selection and posterior prediction. The performance of the proposed techniques is evaluated via simulation studies and a real data analysis. • Algorithms for Bayesian quantile regression in big data scenario are developed. • The proposed approach is based on ALD-based working likelihood functions. • Big data based algorithms for for variable selection is also provided. [ABSTRACT FROM AUTHOR]