Electrohydraulic systems with the combination of hydraulic hardware and electronics have offered superior industrial applications in position, velocity, and force/torque control. Position control is the more demanding application of such automated electrohydraulic systems. However, the system performance is affected by many factors with hydraulic and electronic hardware and software and, therefore, impacts the manufacturing process performance and product quality. To optimize the system performance, it is important to identify the key factors that play significant roles. This study presents a quality control application to optimize an electrohydraulic system in the presence of extraneous variability. The electrohydraulic system studied here controls the position of a hydraulic cylinder through a servo valve, a fluid control drive (Compax 3F), and a web-based automation controller (Parker Automation Controller). The performance measures of the system are response time of the cylinder to a target setpoint position, and positioning errors that reflect the deviation of current cylinder position from the target position. The controllable process parameters (factors) in this system include fluid pressure, proportional gain of the controller configuration, and signal communication (local vs. remote). The ambient temperature will be used as the extraneous noise variable to simulate a real manufacturing environment. The study objective is to answer the questions: (1) Which factors affect the system performance measures and to what extent?, and (2) can optimal settings be identified for the system to perform consistently over the range of the extraneous noise variable? To do this, Taguchi experiments will be utilized, and analysis of variance (ANOVA) will be conducted along with signal to noise ratios and factorial plots, to analyze the results. The aim of this paper is to introduce the application of quality control methods in performance optimization for an automated electrohydraulic position control system. The system setup, hardware, software, and programming will be introduced. The research design, measurements, and experimental runs will be demonstrated and explained. The impact on students’ understanding will be analyzed through assessment of their reports and presentations.
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Shraim et al. (2024) studied this question.
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