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Microrolling is an advanced manufacturing process for the mass production of miniaturized components. At the micrometer scale, small deviation in material thickness or roll misalignment can lead to significant variation of the pressure distribution across the product, resulting in dimensional inaccuracy of the imprinted texture. To address this problem, an embedded sensing system has been developed to monitor in situ the spatial pressure distribution across the tool–workpiece interface. A key element of the sensing system is a pressure reconstruction algorithm, which determines the deformation across the roll structure from a limited number of sensing points, and converts the data subsequently into pressure distribution across the workpiece. This paper investigates how backprojection and interpolation can be integrated synergistically to improve the accuracy and robustness of pressure reconstruction. Specifically, interpolation is performed as a pre-possessing step to increase the resolution in capacitance variation estimation and improve the robustness of back-projection in solving the inverse problem of capacitance–pressure conversion. Experimental study confirmed the performance of the developed method. [ABSTRACT FROM AUTHOR]

Roll bonding is a solid-state welding process performed by means of rolling. During the process, virgin metal is extruded to the surface from underneath the surface through micro cracks leading to the formation of new metallic bonds. Electrically-assisted roll bonding (EARB) was applied to roll bond 127 μm aluminum sheet to 127 μm aluminum or copper sheets. The quality of the bonds was examined through micrographs and peel tests. It was found that the Joule heating effect in EARB lowered rolling forces and increased the bond strengths of bonded sheets by as much as three times. [ABSTRACT FROM AUTHOR]

Abstract: Electrically-assisted micro-rolling (EAμR) takes advantage of localized heating by loading current through the deformation zone to enhance the texturing capability of Ti-6Al-4V and AA3003-H14. The challenge to achieve a desired deformation pattern is the lack of reliable models to capture the often non-uniform mechanical and thermal behaviors. In this paper, pressure distributions are measured by a custom-designed, tool-embedded sensor. Furthermore, the effects of current on texturing are first characterized using a coupled mechanical and thermal model. Comparison between modeling and experimental results confirmed the effectiveness of EAμR on texturing and the importance of multi-physics modeling. [Copyright &y& Elsevier]

Abstract: The temporal and spatial distributions of pressure across the roll-workpiece interface during the micro- form-rolling process are critical indicators for the quality of the formed textures. This paper presents a novel method for monitoring the pressure distribution through a set of capacitive sensors embedded within the roll. Numerical and analytical models of the sensor-embedded roll have been established for determining the optimal sensor dimension to maximize the capacitance output in the pico-Farad range, under space constraint. A transfer function of the sensor is established for retrieving the pressure distribution. The technique is evaluated by simulation and confirmed through experiments. [Copyright &y& Elsevier]

Abstract: On-line monitoring of polymer melt state is critical to ensuring part quality in injection molding. This paper presents a novel, dual-parameter sensing method for simultaneous measurement of pressure and temperature variations within the mold cavity through a modulator circuit. Pressure variation during the molding cycle, which is proportional to the electrical charge output of a piezoceramic stack, is discretized into acoustic pulses that are subsequently frequency-modulated by a temperature-sensitive oscillator (TSO). The ability to measure two parameters using one sensor package without batteries and cables for data transmission provides a new platform for monitoring injection molding processes. [Copyright &y& Elsevier]