There are various micromachining processes available for manufacturing highly integrated and precise parts, each having its own characteristics and limitations. The degree to which micromachining processes meet the requirements depends on characteristics of parts that are different, making it difficult to determine the most appropriate process. In this context, the present study presents an algorithm for determining the optimal micromachining process by applying the Fuzzy AHP-TOPSIS technique frequently used for multi-criteria decision-making. Fuzzy AHP was employed for calculating weights of requirements for a given part. Fuzzy TOPSIS was employed for determining ranks of candidate processes based on weights of requirements and evaluation of processes. Fuzzy logic was applied to handle ambiguous and inaccurate information encountered in evaluating the relative importance of requirements and performances of processes. The case study in which the optimal process for micro-hole drilling of a fuel injection nozzle was determined showed that the proposed method was effective. It could be extended to micromachining of various shapes.

This paper describes a control system for the servo prep column of High-Performance Liquid Chromatography (HPLC) based on fuzzy inference control. The key technology in pharmaceutical and biotechnology industries is refining performance and efforts to reduce costs by purifying target compounds with high purity at high yield while maintaining target compounds, is the major focus of new product development. Among the many refinement techniques, the most popular chromatographic methods require a column that can charge the resin with excellent performance and reproducibility. However, the present HPLC prep column has a hydraulic for control moving stopper and compressed chemical compound. It always causes irregular performances of the column. This paper presents automation control with a servo motor that prevents slurry issues and improves efficiency of the prep column reproducibility and provides easy automation. As an automation method, cortex-m4 as an embedded processor and operating system with LabVIEW, are used to control the HPLC system. To generate the heuristic data for the fuzzy inference control, experiments are conducted to identify correlation between data such as pressure sensor and motor speed. The result will improve performance of the servo prep column of HPLC for automation control based on fuzzy inference control.