RF MEMS phase shifter is a device that is used to modify the transmission phase of RF signal and provide signal control. Phase shifters are high-value components used in phased array antenna architectures. In phased array antenna the phase shifter is used to provide reliable electronic beam steering. The proposed 3-bit distributed MEMS transmission line (DMTL) phase shifter is designed using elevated coplanar waveguide (ECPW) transmission line for the first time, which results in better return loss of [Formula: see text]14.23[Formula: see text]dB and an average insertion loss of [Formula: see text]1.46[Formula: see text]dB. This paper discusses the development of ECPW-based 3-bit DMTL phase shifter designed to operate at 15[Formula: see text]GHz.

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Analyses a standardized item with a flawed production process' limited replenishing modelling techniques. A predetermined percentage or an arbitrary amount of the things generated throughout this technique are flawed. The renewal rate is regarded as a component. A surcharge above the manufacturing costs determines the command's cost of goods sold. And use a horizontal stripe integer programming strategy for improvement; it is advised that the commodity be produced at its most profitable level. The inventory management process used both the crispness and imprecise models to repair broken goods. The proposed model is solved by the Nonlinear Mathematics Engineering Lagrangian Method, which uses a Trapezoidal Fuzzy Number to discover the lowest pricing. The purpose of this study is to advocate the Lagrangian methodology as a means of lowering defective products in production management. The distorted produced inventory framework optimal solution, which integrates the defective entire value in the appropriate course of action, is corrected using a modified version of the KuhnTucker Technique for promoting equity. The optimal evaluation of the various fuzzy function membership functions is demonstrated with the aid of a mathematical model developed utilising properly analysing. The objective of this study is to utilize the Lagrangean and Kuhn-Tucker methods to discover the ideal method for some of these models. Ultimately, a simulation results is provided to illustrate the individuality found in both the crisp and fuzzy inventory management systems. The expenses made to prevent or reduce the number of issues that originally arose in the Matlab programming functions

To mirror the real world, the various inventory cost characteristics are also shown as interval numbers. The assumption is that the relationship between the product's demand and selling price is linearly descending. The supply chain has been optimized in this article using these two techniques with random demand. These two approaches have been compared, and a potential machine-learning strategy combining these two approaches has also been offered. The demand is thought to be random. Crisp and fuzzy models were utilized in this study to fix perishable products in the manufacturing process. The proposed model is solved using both the nonlinear mathematical Programming Lagrangian and Kuhn-tucker Methods. The Grade Mean Integration Representation technique is used to defuzzify data in the Fuzzy Inventory Model, which uses a Trapezoidal Fuzzy Number to determine the lowest prices. To support the solution process, a numerical example that includes sensitivity analysis is done at the end. Lagrangian, Kuhn-Tucker, and fuzzy logic analysis are used to analyze the Economic Order Quantity (EOQ) for changeable demand in this study. This research compares and contrasts their approaches, and the findings demonstrate the superiority of fuzzy logic over traditional approaches. To explore the price-dependent coefficients with variable demand and unit purchase cost over variable demand, trapezoidal fuzzy numbers are used in this research. The outcomes closely resemble the clean output. To validate the model, sensitivity analysis in Matlab was additionally carried out