The aim of this project is detecting knock during combustion of biodiesel-hydrogen fuel and also the knock is suppressed by timed injection of diethyl ether (DEE) with biodiesel-hydrogen fuel for different loads. Hydrogen fuel is an effective alternate fuel in making a pollution-free environment with higher efficiency. The usage of hydrogen in compression ignition engine leads to production of knocking or detonation because of its lower ignition energy, wider flammability range, and shorter quenching distance. Knocking combustion causes major engine damage, and also reduces the efficiency. The method uses the measurement and analysis of cylinder pressure signal for various loads. The pressure signal is to be converted into frequency domain that shows the accurate knocking combustion of fuel mixtures. The variation of pressure signal is gradually increased and smoothly reduced to minimum during normal combustion. The rapid rise of pressure signal has occurred during knocking combustion. The experimental setup was mainly available for evaluating the feasibility of normal combustion by comparing with the signals from both fuel mixtures in compression ignition engine. This method provides better results in predicting the knocking feature of biodiesel-hydrogen fuel and the usage of DEE provides complete combustion of fuels with higher performance, and lower emission.
The challenges in a manufacturing system are lack of timely, accurate, and lack of information to featured product prediction, shop floor resources, product flow, product inspection, product status to customer, product delivery status and factory adaption for customized product. The proposed idea is to design IoT visualization based Smart Factory for Additive Manufacturing System (ISFAMS) that creates a way towards progressively from traditional automation to a fully connected mass customization and flexible cyber-physical system. The ISFAMS utilize a consistent stream of information from associated tasks and creating frameworks to learn and adjust factory productions to new requests from the customer. The system utilizes the Industrial Controller to control the operation of individual systems and sequence of product flow in the Smart Factory setup. The wireless sensor network acquires real-time manufacturing information and information is stored, accessed and visualized using cloud computing. The vision system and automated platform enable the inspection of products shape and dimensions based on the machine learning approach and to transfer the product from section to section and separate the product for packaging section. This digitization of manufacturing system increases flexibility, reliability, smart sensing and control, resource wastage, easy access to manufacturing information and logistics management.
Automation feeding machine helps to replace the manual feeding of the components to achieve the production rate. Even so, all industrialists have been trying to get 100% efficiency from every machine and to give more production. The production rate of the machine is depended on certain factors like feeding, accuracy, Manpower, etc. However, feeding is the most important factor, because the production will be fast only while the component is federal quick. This paper is providing an automation solution of feed ball joints for an automotive industry when the vehicle gathers the steering assembly. There were many feeding mechanisms available. Still, the ball joint is such a large component and should need a certain interval to feed it correctly as required. In this machine, the hoppers to be a trapezoidal tanks stores the sorted of long components. The two-step feeders consist of cylinders, which make the movement of steps. The steps that are used the EN-8 materials are used to make the feeder assembly, and those are connected with the cylinders that are used to construct the up and down movements, when the cylinder makes the forward and retracts motion. The steps scoop up the components and feed them to the additive chute. The linear chute transfers the properly oriented components to the singling unit feeds the components to the machine for making further operations.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.