State Key Laboratory of Mechanical Manufacturing System Engineering

Presented in this paper is a development of a high-performance piezoresistive microaccelerometer based on the slot etching in the quad flexures for the vibration detection of high speed spindle. The proposed structure consists of a proof mass supported by four thin flexures with slots etched in the middle. Boron diffused piezoresistors located near the stress concentration regions are used for sensing the localized stress resulting from the incorporation of the slots into the flexures. Theoretical analysis and finite element analysis show satisfactory results of an improved sensitivity and favorable natural frequency higher than 10 kHz, conforming to the initial design requirements. The microfabrication techniques are described to prototype the two accelerometer chips, one with slots and the other one without slots. The tested microaccelerometers with 3 V DC power supply show an average sensitivity of 0.424 mV/g normal to the proof mass plane, increased by 60.6% than the ones without slots. An average transverse sensitivity is found to be 9.2 μV/g along X axis and 14.2 μV/g along Y axis, either of which is less than 3.5% of prime-axis sensitivity. Concerning the resonant frequency, dynamic experiment shows about 12.46 kHz and is available for the proposed design with a tiny loss of 3.5% compared with the quad-beam design. When taking the product of sensitivity and natural frequency as judgment criteria, an inspiring increase by 28.6% of the figure of merit is accomplished for the proposed accelerometer. Overall, the findings of this study confirm the feasibility of incorporating slots into the conventional configurations to improve the sensor sensitivity while maintaining a comparatively high natural frequency.

Dielectrophoresis is employed in micro total analysis systems to manipulate micro targets in recent years including sorting, transporting, separating, and collecting microparticles for further applications. This research reported a dielectrphoretic trasporting application with interdigitated electrodes and high frequency alternating waves. A kinetic model was proposed to describe the movement of particles in microchannel, which were driven by the DEP force induced by a non-uniform electric field. This electric field was generated by the interdigitated electrodes on the bottom surface of the channel, which transmitted two alternating waves 180 degrees out of phase. Numerical simulation was also utilized to investigate the generated electric field. Both the electric field strength and the gradient of squared electric strength were determined to show the non-uniformity distribution in the channel. Blood cells solution was injected into the dielctrophoretic micro-channel and flow images were recorded to investigate their flow behavior. The experimental results demonstrated the DEP driving force acting upon the sample cells, which changed their orientation and moved in the fluid medium with an obvious acceleration process. Because of the viscosity and friction between the cells and the fluid, a steady flow was formed in the micro-channel. The obtained velocitytime curve of one cell also confirmed the observation by tracing a blood cell flowing in the channel. In this experiment the cell achieved a 4.2μm/sflow velocity within 2.3s which remained almost constant in later motion. The experiment also indicated that the moving velocity of the cell was related to the electrode shape, gap, amplitude, and frequency of the applied alternating wave.

Stressed lap, compared to traditional polishing methods, has high processing efficiency. However, this method has disadvantages in processing nonsymmetric surface errors. A basic-function method is proposed to calculate parameters for a stressed-lap polishing system. It aims to minimize residual errors and is based on a matrix and nonlinear optimization algorithm. The results show that residual root-mean-square could be >15% after one process for classical trefoil error. The surface period errors close to the lap diameter were removed efficiently, up to 50% material removal.

With the advancement of the dual-carbon goal and energy consumption revolution, demand-side management relying on smart grids has gradually become the focus of related research. Due to the obvious surging and high uncertainty of the power load of energy-intensive enterprises, it is difficult to obtain the best control strategy for demand charge. In this paper, we solve the problem of multi-equipment demand charge control for multi-batch tasks with discontinuous production by controlling the load of controllable equipment to reduce electricity costs. To solve the problems of long-time sequence with time coupled and complex systems with difficult modeling, we established a Markov decision process (MDP) model for real-time demand charge control innovatively. To avoid the curse of dimensionality caused by the increasing state space, we introduced the deep Q learning (DQN) algorithm, which successfully solves MDP problems with large state space. Moreover, we introduced constrained deep Q-learning (CDQN) aiming at a large number of action constraints in the problem, which selects the optimal action from the feasible action zone instead of the whole action space to improve the training efficiency and data utilization. Finally, we conducted experiments on simulation case experiments. Under the basic day-ahead production scheduling plan, real-time demand charge control can reduce costs by 10.4% compared with uncontrolled, indicating that this method has achieved excellent performance in obtaining demand charge control strategies.

Under the environment of agile and decentralized manufacturing, manufacturing enterprises are increasingly outsourcing their business. From the perspective of protection and acquirement of manufacturing specification, companies' strategic outsourcing decision-making is been focused on. The requirement analysis derived from strategy outsourcing decision is conducted. The system of outsourcing decision is analyzed and designed by UML. Requirement model, objects model and system structure are developed

The structure and performance of micromixer with Ytype channel was investigated with computed fluidic dynamics and digital image process.The influences of micromixer such as inlet angle,channel size,and flow velocity of fluid on mixing process,were analyzed.Numerical simulation results reveal that a suitable mixing can be achieved in a microchannel mixer with an inlet angle of 60°,the width of 200 μm,and the in-flow velocity of 0.02 m/s.Numerical simulations were also executed to compare the performance of mixers such as twisted,blocked,and straight channel.The results indicate that the blocked channel mixer has higher quality than its counterparts.According to the numerical results,a new mixer with convex block arrays on two-side walls was adopted,which can accelerate mixing process by squeezing and spreading the streamline of fluids repeatedly.The new mixer was fabricated with MEMS techniques and mixing experiments were carried out to verify the results.Mixing process was also observed.The recorded images were processed and the specific index of fluid mixing along the flow axis was identified according to the constructed standard curve in advance.The identified results validate the performance superiority of the new mixer.In the end,the errors in mixing results were analyzed to find their sources,and some useful advice was also proposed to improve the performance of the experiments.