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We invite you to register on our platform and characterize your technological solution, so you can participate in the open innovation processes that we carry on for the main mining companies in the country
Register here
We invite you to register on our platform and characterize your technological solution, so you can participate in the open innovation processes that we carry on for the main mining companies in the country
Register here
ESTADO:
Cerrado
Deadline
26/10/2020
Closing Time
00:00
This challenge seeks to detect early the failures of equipment used in production, for example: pumps, motors, valves, etc. It is expected to avoid unforeseen events and stoppages, improving security, reducing down-time and maintenance costs.
The objective is to develop an MVP of a machine learning model with artificial intelligence that allows detecting anomalies or “silent threats” so that they can be incorporated into the maintenance strategy. For this, information from the DCS control systems will be used. The model must be applicable to any valve, motor and pump, taking into account the different operating points of the processes, using clustering techniques.
This challenge is highly scalable as it is geared towards equipment that is widely used in industry.
This challenge seeks to integrate the information from two management systems (dispatch and maintenance) and model the main causes that can impact a risk condition in the operational continuity of its systems or of the entire mobile equipment.
It is expected to improve the useful life and the mean time between failures (MTBF), as well as to optimize the transport cycles and maintain the operational continuity of the equipment, which is highly sophisticated and high volume.
The objective is to generate an MVP of a mathematical model that allows to determine the main causes of unavailability of mobile transport equipment and to characterize in detail the optimal conditions for their continuous operation. For this, information from the fleet management systems (Dispatch-Modular) and maintenance management (Minecare-Modular) will be used.
Predictive management and artificial intelligence help to design a more sustainable mining, increase safety rates, quality and speed of work and standardization of processes. The challenge is to be able to integrate these innovative solutions and for that BHP believes that collaboration is key.
In this second edition of “Hackamine”, BHP seeks to incorporate data analytics technologies that allow optimizing maintenance activities in mine and plant processes and equipment and Artificial Intelligence. For this, it wants to identify agile teams capable of generating a Minimum Viable Product (MVP) of a predictive model that allows early detection of failures to improve safety and productivity in its operation. The solutions are expected to integrate, process, and model possible causes to generate efficient and safe improvements.
The OTR tire (Off-the-Road tire), is a highly necessary supply for the operation of any load vehicle and plays an enabling role in ore transportation within the extraction process. The […]
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As mining projects increase their operation time and growth, they are subject to changes in their form and structure, which, despite having been considered in their designs and construction, need to be monitored and modeled with precision to avoid catastrophic situations.
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Breakdown voltages and energy leaks are common in EW tankhouses in copper operations. Its monitoring is manual, costly and slow. TESRA adapted existing technology to develop an automatic thermal control […]
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The efficiency of a metallurgic process depends, to a large extent, of the adequate and timely operational decision making in light of the variability of the physical and chemical quality […]
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The climatic conditions and high altitude present in Chilean mining, damage heavy-duty haul truck engines, eroding their components and reducing their lifecycle.
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The Trommel is a classification system per size of ore coming from the mills. It downstream allows passing of the ore complying with required grading and returns the one requiring […]
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Water plays a significant role in copper production. It mainly participates in the concentration, hydrometallurgical, foundry and refinery processes.
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Labour productivity in the mining industry dropped 20% in comparison with 2000, in Chile and internationally, as stated by the Chilean Copper Commission (Cochilco) in 2014. This is an important […]
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HighService Technology developed a mill lining and wear plates abrasion sensor (the SSD technology) which allows online detection of the components
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Landslides and mass movements can endanger workers and could cause the total shutdown of the mine. Gesecology developed a technology that integrates and correlates geotechnical and geological data, using mathematical […]
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Manual technical conciliation for slope design and construction is time consuming and its results may be inaccurate. Geoblast developed and implemented a software, which compares and consolidates geotechnical data and […]
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The availability of mining power shovels is an important factor for extraction and loading processes.
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Companies or teams capable of generating a model that supports the maintenance process in a preventive way. We look for the best companies with experience in mining and / or other industries, that have the technological capabilities of Industry 4.0 (Artificial Intelligence, Machine Learning, Big Data, among others) that allow them to develop data analytics solutions to generate intelligence from a large amount of data. In addition, they must be able to market and scale their solutions.
Small and medium-sized companies, local or international startups (with a presence in Chile), local universities and research centers (with alliances with companies or spin-offs for the commercialization of technologies), which have the technological capabilities of Industry 4.0: Artificial Intelligence , Machine Learning, Big Data, among others. * Participation is limited to legal entities.
If you need information or have any questions about your application process, enter our platform with your account and send us your questions through the Q&A section of the innovation processes where you are participating
