Feb '24
ISSN: 0974-6536
A "peer-reviewed" journal included in EBSCO and ProQuest (Part of Clarivate) Database
It is a quarterly journal that publishes research papers dealing with Production engineering, Industrial engineering; Materials engineering; Solid mechanics; Solid and structural mechanics; Fluid mechanics; Fracture mechanics; Biomechanics; Metallurgy, Tribology, Heat transfer; Welding technology; Composite materials; Machine design CAD/CAM; Renewable energy technology; Mechanical maintenance; Refrigeration & Air-conditioning; Quality control and Operational research, etc.
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Article | Price (₹) | ||
Thermal Analysis of Tube-in-Tube Type Heat Exchanger with Augmentation Technique Using Wilson Plot and Modified Wilson Plot Methods |
100
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Federated Learning in Digital Manufacturing: A Review |
100
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Designing Efficient Sugarcane Node Cutting Machines: A Novel Approach |
100
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Thermal Analysis of Tube-in-Tube Type Heat Exchanger with Augmentation Technique Using Wilson Plot and Modified Wilson Plot Methods
The paper explores the application of Wilson plot method, and its modifications, as an alternative approach for determining convective heat transfer coefficients in heat exchangers with complex geometries. For achieving the delicate balance, one needs to introduce heat transfer augmentation techniques in devices, which results in intricate geometries of heat exchanger. For such geometries of heat exchanger, correlations are not available to estimate convective heat transfer coefficients. The Wilson plot method provides a robust tool for deriving correlation equations based on experimental data. The paper discusses the implementation of the Wilson plot and modified Wilson plot methods to establish correlations for tube-in-tube type heat exchangers with wire mesh inserts, and results are obtained for both methods. It is found that modified Wilson plot method provides correlation with great accuracy in the range of 94 to 97%. Furthermore, the paper presents the development of a computational tool using VB.net, designed to facilitate the iterative calculations required for Wilson plot methods. The paper also describes a roadmap for the proficient application of Wilson plot method and its modification in heat exchanger analysis.
Federated Learning in Digital Manufacturing: A Review
Federated learning (FL) is an emerging tool involving a decentralized machine learning (ML) paradigm. It shows lots of promise encompassing viable solutions to address data privacy and efficiency in the manufacturing industry. Though quite expensive, FL is a key process wherein input settings, data collection and analysis in the manufacturing sector become important. These aspects hinder the advanced ML and data-driven methods, which needs to be addressed through offline training program. FL plays a crucial role in effectively tackling significant issues in digital manufacturing (DM) and its advanced version additive manufacturing (AM). The paper provides a thorough analysis of the application of FL in the context of DM and AM. It also reviews the current state of the manufacturing industry with a focus on the difficulties and potential advantages associated with contemporary production methodologies.
Designing Efficient Sugarcane Node Cutting Machines: A Novel Approach
Efficient sugarcane production is crucial in today's competitive agricultural landscape. Traditional planting methods are cost-intensive and time-consuming and often fail to achieve adequate compression of buds due to the stalk planting nature of sugarcane. To address these challenges, a novel approach using machine vision to identify and plant sugarcane nodes is proposed. Sugarcane holds significant economic importance in India and various other countries, making its cultivation a cornerstone of many economies. The development of a sugarcane node cutting machine aims to revolutionize the process of preparing sugarcane seedlings. This machine streamlines the time-consuming task of cutting nodes, thereby reducing waste and effort associated with traditional methods. The paper focuses on designing and testing a machine for efficiently cutting sugarcane buds, intending to mechanize the preparation stage of sugarcane seedlings. By cutting undamaged bud-containing sugarcane stalks, this machine eliminates the need for laborious manual cutting, providing a timesaving and cost-effective solution for farmers. Furthermore, by measuring cutting force and power requirements, the research aimed to optimize the efficiency of sugarcane cutting processes.