Browse Topic: Production
In order to meet the demand for the transformation of traditional manufacturing industries into intelligent manufacturing, a virtual monitoring system for the production workshops of nuclear - key products has been built. There are problems such as poor environment, long distance and remote collaborative office in this production workshop, and managers lack information tools to master the workshop status in real time. In order to minimize the harm of nuclear radiation to the human body, in view of the problems of low transparency, poor real - time performance and low data integration in traditional two - dimensional forms, configuration software and video monitoring, a remote monitoring system for virtual workshops driven by digital models has been developed. This system realizes the remote dynamic display of real - time information in the workshop based on data collection and three - dimensional modeling technologies. Virtual monitoring technology improves the management efficiency of
Measuring the volume of harvested material behind the machine can be beneficial for various agricultural operations, such as baling, dropping, material decomposition, cultivation, and seeding. This paper aims to investigate and determine the volume of material for use in various agricultural operations. This proposed methodology can help to predict the amount of residue available in the field, assess field readiness for the next production cycle, measure residue distribution, determine hay readiness for baling, and evaluate the quantity of hay present in the field, among other applications which would benefit the customer. Efficient post-harvest residue management is essential for sustainable agriculture. This paper presents an Automated Offboard System that leverages Remote Sensing, IoT, Image Processing, and Machine Learning/Deep Learning (ML/DL) to measure the volume of harvested material in real-time. The system integrates onboard cameras and satellite imagery to analyze the field
The development of 3D game ready models is a critical component of the asset creation workflow in industries. However, traditional modeling techniques often demand extensive manual input, particularly in the areas of modeling, retopology, and texturing. To address challenges, we propose the integration of generative AI technologies into the 3D modeling workflow, aiming to enhance efficiency and streamline processes. This paper presents a comprehensive methodology that leverages advanced algorithms, machine learning techniques, and specialized software to automate repetitive tasks associated with 3D asset creation. By harnessing the power of generative AI, we aim to significantly reduce the manual effort required to produce high-quality 3D models, thereby accelerating the overall development timeline. The aim is to enter a prompt/Image as input to get a fully developed Model. Through a series of experimental implementations, we are aiming to demonstrate the effectiveness of our proposed
Large farms cultivating forage crops for the dairy and livestock sectors require high-quality, dense bales with substantial nutritional value. The storage of hay becomes essential during the colder winter months when grass growth and field conditions are unsuitable for animal grazing. Bale weight serves as a critical parameter for assessing field yields, managing inventory, and facilitating fair trade within the industry. The agricultural sector increasingly demands innovative solutions to enhance efficiency and productivity while minimizing the overhead costs associated with advanced systems. Recent weighing system solutions rely heavily on load cells mounted inside baling machines, adding extra costs, complexity and weight to the equipment. This paper addresses the need to mitigate these issues by implementing an advanced model-based weighing system that operates without the use of load cells, specifically designed for round baler machines. The weighing solution utilizes mathematical
Over the past 25 years, the heavy fabrication and construction equipment industry has experienced significant transformation. Driven by a global surge in demand for construction machinery, manufacturers are under increasing pressure to deliver higher volumes within shorter timelines and at competitive costs. This demand surge has been compounded by workforce-related challenges, including a declining interest among the new generation in acquiring traditional manufacturing skills such as welding, heat treatment, and painting. Furthermore, the industry faces difficulties in staffing third-shift operations, which are essential to meet production targets. The adoption of automation technologies in heavy fabrication and construction equipment manufacturing has been gradual and often hindered by legacy product designs that were optimized for conventional manufacturing methods. As the industry transitions toward smart, connected manufacturing environments under the industry 4.0 paradigm, it
Yamaha Motor Engineering Co., Ltd. provides plastic processing technology based on fuel tank press forming technology, and is developing various plastic processing methods, including forging, and developing mold equipment to realize them. This time, the core parts of the YECVT unit mounted on Yamaha Motor Co., Ltd.'s small premium scooter "NMAX" were not made by welding individual parts to each other, but by integrally forming them from a single thick plate using the cold forming method, resulting in lightweight, compact, high-strength, high-precision parts. By incorporating a composite plastic processing method that takes advantage of the characteristics of the material while making full use of analysis technology and mold technology, we were able to develop a composite plastic processing method (plate forging method) that creates new added value and mass produce it. In addition,this development has made it possible to achieve a thickness increase of 1.7 times the standard material
This specification covers a fluorosilicone (FVMQ) rubber in the form of molded rings.
The high rate of structural changes to the North American Light Vehicle market demands a new approach by the supply base towards strategic planning. A new Supplier Strategy Playbook is in order. First, some historical perspective. For the last several decades, suppliers grew accustomed to a product cadence of approximately five years between all-new platforms and major revisions. In North America, we were constantly pressed to continue improving vehicle efficiency and reduce emissions. Improved powertrain efficiency, vehicle lightweighting, and the advent of enhanced aerodynamics helped an industry that required constant innovation. Additionally, many programs were global in scope, requiring production and tooling in the major regions to launch in close sequence with global scale in tow. Wash, Rinse, Repeat. The textbook for suppliers was complex, though relatively predictable.
Slate bought a factory. The 1.4 million sq. ft. (130,000 m3) facility was formerly a printing company. Sears, JCPenny, and Radio Shack catalogs emerged from the RR Donnelley & Sons printing plant for decades. Beginning late next year, Slate says it will begin production of its low-cost, highly customizable pickup truck.
Celebrating its 35th year, the National Aerospace Defense Contractors Accreditation Program (Nadcap) continues to advance quality assurance and regulatory compliance for aviation, defense, and space OEMs and suppliers. This article summarizes how Nadcap accreditation works, its benefits for manufacturers, and its role in expanding additive manufacturing through industry-wide consensus. The Nadcap program was first established in 1990 by a small group of aerospace and defense OEMs. Their goal was to create an accreditation initiative that provides a common approach to auditing the manufacturing and production processes used by companies supplying parts, components, structures, and services to major aerospace and defense OEMs. This foundation set the stage for Nadcap's continued focus on quality assurance and regulatory compliance in the industry.
This specification covers tungsten carbide-cobalt in the form of powder.
Advances in conformable tank technology have resulted in opportunities to harness and deploy hydrogen energy in a variety of operational environments. Various use cases are described, and the benefits of these unique storage systems in vehicular, stationary, and bulk storage applications are illustrated. The impressive scalability of conformable hydrogen tank production is also explained, as it relates to the cost effective and broad application of these storage systems.
In modern defense manufacturing, achieving technological superiority hinges on both rapid decision-making and unparalleled precision engineering. Advanced machining systems, such as 5-axis CNC machines, play a pivotal role by enabling the production of intricate, free-form geometries with micron-level accuracy. However, these advances often necessitate deep domain expertise for optimal tool selection and machining parameter configuration. This paper introduces GraphLLM, a model-agnostic approach that integrates structured knowledge graphs with large language models (LLMs) to enhance the accuracy and reliability of technical responses. By automatically extracting domain-specific entities and relationships from documents, GraphLLM mitigates LLM hallucinations and improves performance, especially in technically challenging or out-of-distribution queries. Experimental evaluations across various LLaMA models demonstrate significant uplifts of 25%, highlighting the framework’s potential to
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