This work presents a framework of tolerance analysis of microparts in microassembly. Tolerance analysis at the micro scale has not been investigated so far even though tolerance analysis at the macro scale has extensively been investigated to improve an assembly yield. It is important to know the positional uncertainties and statistical distribution of parts before and after untethering to improve assembly yield. Positional misalignments of microparts are extracted from raw CCD images and the statistical distribution of parts variances are computed using clustering and transformation of Gaussian distribution. The distributions are not pure Gaussian in nature as might be expected. There are several location peaks found, usually centered at the fabrication location, and at the hard-stop locators.

This paper presents analytical, simulation and experimental results from a study of compliant insertion tasks in microassembly. Gripper compliance is desirable to compensate for positional errors and to prevent the breakage of a gripper during assembly tasks. An analytical model is derived to study the motion and force profiles during compliant insertion. Thermal bimorph microgrippers with a compliant tip are designed and fabricated using a silicon DRIE process, and are mounted on a precision motion stage. A series of micropeg manipulation tasks such as pick up, rotation, and insertion are successfully performed. Finally, a comb structure is integrated in the gripper to calculate insertion force by measuring the deflection of a gripper, which is essential for automated microassembly.

Thermal bimorphs are a popular actuation technology in MEMS (micro-electro-mechanical systems). Their operating principle is based on differential thermal expansion induced by Joule heating. Thermal bimorphs, and other thermal flexure actuators have been used in many applications, from micro-grippers, to micro-optical mirrors. In most cases open-loop control is used to difficulties in fabricating positioning sensors together with actuator. In this paper we present several methods for extracting reduced-order thermal flexure actuator models based on experimental data, physical principles, and FEA simulation. We then use the models to generate optimal driving signals using input shaping techniques. Both simulation and experimental results are included to illustrate the efficacy of our approach. This framework can also be applied to other types of MEMS actuators, including electrostatic comb drives.