Abstract

The wireless poka-yoke (WPY) is a novel concept that is concerned with profound control for ventilator processes' behavior to enhance their reliability's mechanisms for its importance after the outbreak of the Covid-19 pandemic. The Ventilator's performance based on rapid controlling some of the influencing variables that reset according to the patient's case. The target is to guarantee smooth traffic O2 flows by controllable the created eddies, which based on impacted variables (e.g., viscosity, Reynolds, and its Circulation value) to create a stationary pressure to push the air to patients' muzzles. The stationary pressure used to create oriented and controllable eddies' paths via controlling the liquid full of ventilator's incubator to maintain the uniform O2 velocity flow. The proposed algorithm based on tackling these variables through (IoT) technology that using sensor data in real-time that can enhance the intervention in-time by Neural-Networks (NN) to predict patient's case changes, and take-over the eddies created to achieve the target. The NN not only forecasting eddies' path and bursting position that makes negative pressure in pleural space of alveoli, to push the air in a regular case. The paper adopts a WPY's perspective that derivative from DMAIC tools to improve processes' reliability.