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In the case of the existing power equipment business, a variety of insulation and accessories is manufactured with petroleum-based epoxy resins. However, as petrochemical resources are gradually limited and concerns about the environment and economy grow, the power equipment industry has recently studied many insulating materials using bio-based epoxy to replace petroleum feedstock-based products in order to produce insulators using eco-friendly materials. In this paper, the simulation of the automatic pressure gelation process was performed by obtaining parameter values of curing kinetics and chemical rheology through physical properties analysis of bio-based epoxy complexes and applying them to Moldflow software. The simulation results were compared and analyzed according to the temperature control of each heater in the mold, while considering the total curing time, epoxy flow, and curing condition. A temperature condition of 140 °C/140 °C/135 °C/135 °C/130 °C/130 °C/120 °C/120 °C provided the optimal curing conditions. Based on the temperature conditions of the simulation results, the actual GIS spacer was manufactured, and x-ray inspection was performed to check the moldability. Full article

Medium voltage insulators are essential and versatile components in electrical engineering. Quality control of the manufacturing process for the insulators has a significant role in their economic production and reliable operation. As the quality of medium voltage insulator is mainly affected by the process parameters of the automatic pressure gelation process (APG), the optimal process settings are required to achieve a satisfactory quality target. However, traditional process parameters’ optimization methods are often cumbersome and cost-consuming. Moreover, the operational cost of APG for insulator production is relatively high. Therefore, the determination of the optimal settings becomes a significant challenge for the quality control of insulators. To address the above issues, an idea of knowledge-informed optimization was proposed in this study. Based on the above idea, a knowledge-informed simultaneous perturbation stochastic approximation (SPSA) methodology was formulated to reduce the optimization costs, and thus improve the efficiency of quality control. Considering the characteristics of SPSA, the historical gradient approximations generated during the optimization process were utilized to improve the accuracy of gradient estimations and to tune the iteration step size adaptively. Therefore, an implementation of a quality control strategy of knowledge-informed SPSA based on historical gradient approximations (GK-SPSA) was thus constructed. In this paper, the GK-SPSA-based quality control method was applied to the weight control of a kind of post insulators. The experimental simulation results showed that the revised knowledge-informed SPSA was effective and efficient on quality control of medium voltage insulators. Full article