REVIEW ON PARAMETERS INFLUENCING THE RICE BREAKAGE AND RUBBER ROLL WEAR IN SHELLERThe present review deals with parameters influencing the rice breakage during rice milling operations and the effect of rubber roll Sheller in rice husk removal process. The main objective of rice milling system is to remove the husk and bran layer to produce the white rice. In this process, rubber roll sheller is used to remove husk from the grains by friction process. If the rubber material is too soft, there may not be sufficient shear force to husk the paddy. Wear will be minimum for rubber material with high hardness but indeed it pronounce the breakage of rice. Hence, for efficient husking the rubber roll material should possess the balance of physico-mechanical properties. Rice breakage depends on several other parameters like the type of harvest, drying temperature, drying methods, physical characteristics of paddy, husking characteristics, paddy moisture content, rubber roller speed, rubber roll pressure, paddy feed rate and fissures. Rubber roll wear depends on the type of rubber material attached to the roller, feed rate, roller speed, pressure etc.
In the present work the effect of nitrogen on WC9 alloy at various weight percentages was analyzed and tested for their microstructural and mechanical properties. The nitrogen was added at 0.05, 0.10, 0.15, 0.20 and 0.25 wt. % in the solid form as nitrided ferrochrome to WC9 alloy. The samples were heat treated by solution annealing process at a temperature of 1100°C for 5 hours to improve the austenitic formation. Microstructures and mechanical properties such as tensile strength, yield strength, hardness, % elongation and % reduction of WC9-N alloy were examined. It was observed that increasing nitrogen wt. % increases the mechanical properties. The obtained mechanical properties were compared with base WC9 and C12A grade steel, where it was found to be replacement for C12A grade steel at its composition at lower end. The material cost analysis for WC9-N and C12A grade steel was done and both were compared.
Indian metro system is comprised of many functional units for enabling smooth run of trains namely tracks, rolling stock, signaling and communication, operations and control center, projects, and design. Among those functional units, Rolling Stock (RS) is an integral part of any rapid transit system and also the most critical space if proper maintenance measures are neglected. The rolling stock department comprises interdisciplinary teams working together to ensure efficient delivery of trains on a service run. The trainsets of Metro Rail Networks are often subjected to both periodic and corrective maintenance based on service requirements. The maintenance schedule of the trainsets is monitored through a wireless communication mode. The train operator is responsible for alerting the nodal person regarding subsequent correspondence in the event of any emergency maintenance necessity. Therefore, this paper concentrates on the development of an IoT-based automatized maintenance prioritizing platform based on the incorrect operational sequence number that pops up in the operator’s cabin. A mathematical model is synchronized with the alert triggering signal from the field to categorize hierarchical decision-making on preventative and corrective maintenance. Simultaneously, a Genetic Algorithm is implemented to analyze the adopted combinations of maintenance say M1, M2, and M3 to identify the model that produced precise results. The test results reveal that the M3 model, which includes both corrective and preventative maintenance exhibits higher efficiency with a probability of 0.92%–0.98%. In addition, the combined maintenance prioritization system M3 offers the quickest analyzing time in the cloud computing platform (0.18 s) and the highest transaction performance on real-time datasets.
Congestion on land, hike in fuel costs, and critical need to cut down environmental emissions have generated the urge to shift from conventional rail transit systems to metro rail and high-speed rail for a mass mode of transportation. The conventional railway network especially in India stages an effective space in the means of mass transit systems. Subsequently, periodic inspection of the state of railway tracks is vital for ensuring rail safety, as tracks are critical components of train transportation networks. Tracks are designed to withstand zero critical incidents, and with the advent of new high-speed train services, there is a greater need to focus on track performance. Track maintenance methods are customized to suit local conditions for enhancing safety and reducing disruptions while guaranteeing the resilience and sustainability of any rail system. In recent years, various aspects of the TMSs (track maintenance systems) have been introduced within the railway industry for both ballasted and ballastless track systems. This study reviewed various approaches to track maintenance measures using traditional methods, statistical methods, and geometry-based methods based on track deterioration. Among all the reviewed methods, track maintenance based on the geometry is said to cater to the needs of the maintainers. The outcomes of this study are expected to support and assist in track maintenance decisions in the railway industry.
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.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.