下载PDF
Intelligent Visual Detection of Contaminants
技术
- 分析与建模 - 机器学习
适用行业
- 矿业
适用功能
- 流程制造
用例
- 物体检测
服务
- 软件设计与工程服务
挑战
如果未检测到输送机上的污染物，可能会导致成本增加和机器停机时间增加。
客户
诺镍
关于客户
俄罗斯镍和钯的采矿和冶炼公司。
解决方案
基于人工智能的污染物检测解决方案，防止设备损坏。
运营影响
数量效益
相关案例.
Case Study
Underground Mining Safety
The goal was to produce a safety system to monitor and support underground mining operations; existing systems were either too simple (i.e. phone line) or overly complex and expensive, inhibiting deployment, and providing little-to-no support in event of an accident. Given the dangerous nature of the mining work environment and the strict regulations placed on the industry, the solution would have to comply with Mine Safety and Health Administration (MSHA) regulations. Yet the product needed to allow for simple deployment to truly be a groundbreaking solution - increasing miner safety and changing daily operations for the better.
Case Study
Mining Firm Quadruples Production, with Internet of Everything
Dundee Precious Metal’s flagship mine, in Chelopech, Bulgaria, produces a gold, copper, and silver concentrate set a goal to increase production by 30%. Dundee wanted to increase production quality and output without increasing headcount and resources, improve miner safety, and minimize cost.
Case Study
Fastenal Builds the Future of Manufacturing with MachineMetrics
Fastenal's objective was to better understand their machine downtime, utilization, quality issues, and to embrace cutting-edge manufacturing technology/process improvement capabilities to bring their team to the next level. However, there was a lack of real-time data, visualization, and actionable insights made this transition impossible.
Case Study
Joy Mining Systems
Joy equipment faces many challenges. The first is machine integration and control. The business end of the machine has a rapidly-spinning cylinder with 6-inch diamond-studded cutting teeth. It chews through rock at rates measured in tens of tons per minute. The system grinds through the rock in front, creating a rectangular mine tunnel. Hydraulic lifters support the ceiling as the machine moves forward. Automated drills and screws drive 3-ft long screws into the ceiling to stabilize it. The rock and coal fall into a set of gathering "fingers" below the cutting cylinder. These fingers scoop up the rock and coal and deposit it onto a conveyor belt. The conveyor passes under the machine and out the back. A train of conveyor belt cars, up to a mile long, follows the cutter into the mine. The rock shoots along this train at over 400 feet per minute until it empties into rail cars at the end. Current systems place an operator cage next to the cutter. Choking dust (potentially explosive), the risk of collapse and the proximity of metal and rock mayhem make the operator cage a hazardous location.
Case Study
Improved Monitoring in Industrial Manufacturing Facility
When your crane is moving tons of magma-hot iron, you can’t afford an unexpected failure. McWane Ductile knew monitoring the crane motor metrics within their facility could help prevent a mechanical failure that would strand an enormous bucket of molten metal overhead. Unfortunately, their legacy wired monitoring system couldn’t work with moving objects in this extreme environment. If they could integrate wireless capabilities into their existing equipment they could extend their monitoring capabilities without starting over from scratch.
