Due to a high rate of bolt breakage in sag mills, which became a stoppage of activities; We created a real-time industrial bolt failure prevention and monitoring system software.
We achieve this through sensors located on the bolts with IoT technology implemented by Forcast, where the different data on the status of the assets is displayed through an interactive interface and predictive maintenance alerts are also generated.
As result, the performance of the asset increased, and the maintenance cost were reduced.
In order to increase the production capacity of label printers, we were able to implement a system for monitoring and predicting failures in real time.
This system, thanks to the IoT technology implemented by Forcast, monitors the temperature of the printer heads, activating maintenance alerts on different platforms that warn when the temperature levels are reaching their maximum, in order to anticipate failures without stopping production. In addition, the data is presented graphically in an interactive interface.
As a main benefit the asset’s performance increased, as well as a significant reduction in maintenance costs.
In order to know the energy consumption of the municipality building and the generation capacity of its photovoltaic panels, we developed a monitoring system and created intelligent alerts of the consumption and status of the equipment in real time.
For this, an IoT system was installed and obtained the information from the equipment through a converter that was later displayed graphically through an interactive interface.
In order to optimize energy production in solar plants, we designed a web platform to process images and obtain graphical results.
In this platform, thanks to the image processing modules developed by Forcast, the detection of hot spots in the solar panels was achieved using thermal and infrared cameras, in addition to the detection of cracks, dents, dirt and dust with HD cameras and microcracks. by micro-luminescence.
This led to an improvement in the estimation of energy generation of the plant, as well as in the taking of preventive actions, and a better prediction of the damage and useful life of the solar panels using AI.
Due to the large number of cables in the poles of the metropolitan region and the risks that this can cause, we designed a web platform for a geographic information system of detected events, where, through image processing modules developed by Forcast, failures on poles and transmission lines are detected through HD cameras, performing an automatic and intelligent analysis of videos and images to alert, warn and geolocate faults.
With the aim of improving the efficiency of payment boxes in the stores, we designed a Real-time Monitoring Web Platform, where images of how many people are in line are processed to convert it into an estimate of the waiting time for 200 pool of boxes.
We achieve this by connecting to the security cameras and integrating with the VMS system in order to apply our detection modules, generating alerts in real time for more efficient personnel management and obtaining new KPIs to make decisions based on facts.
In order to optimize the review of incidents found by security operators, we carry out an intelligent camera monitoring system.
Through Forcast’s Image Processing Suite platform, critical events are filtered in an automated way to alert when one is detected, for example, unauthorized entry. In this way, the operator only needs to be attentive to critical events detected by the system.
In addition, thanks to machine learning, the system reduces the detection of false positives, which improves the operator’s performance and allows him to control a greater number of cameras.
Looking for a way to predict energy production in order to analyze the market and thus economically value of a solar power plant, we developed a monitoring platform to optimize the performance of solar plants, which standardize the data capture and detect failures in the panels analyzing the information obtained.
This brought as a main benefit a significant decrease in maintenance costs, a sustainable extension of the business and a significant increase in the return of the assets.
With the purpose of standardizing and concentrating virtually in the same place all the quality audits that are carried out in production plants, we build a web platform where updates can be uploaded to see all the content online and in the same place , in addition to generating automated alerts on different platforms in the case of a critical event.
This brought as a main benefit the generation of new quality indicators and the monitoring of the plants in real time.
In order to reduce maintenance and the costs that are implied in solar panels, we developed an online platform for monitoring I-V tracers.
Through the monitoring of these tracers, the current status of the photovoltaic panel can be seen individually, thus our software works as a real-time scanner and provides automatic alerts when a problem is detected.
The main benefit of this was the generation of new quality indicators, and a significant increase in asset performance.
Seeking to re-attract escaped customers and increase demand based on digital marketing, we designed a segmentation, demand prediction and customer re-acquisition system,.
For this, we first made a prediction of national demand of more than 1MM clients based on analysis of new consumer behavior data such as weather, economic indices, and others, and then segment them according to different parameters such as consumption, age, trends, etc.
The next step was to automate SMS shipments with personalized promotions at key times according to the type of target that had been previously generated. This brought as a main benefit new revenues at the SMS level, visibility, higher demand and a significant decrease in operational costs.
In order to optimize and automate the automotive fraud scoring, we generated a new high-precision Scoring using all existing variables and business rules in the evaluation process. Achieving fraud behavior predictions based on historical data per customer.
We achieve this by creating models through the integration of Data Science and Machine Learning using both historical and new critical data that we generate in the process of integrating our service. This brought as a main benefit the rapid generation of ROI, prediction of fraud behavior based on historical data per client and decompression and optimization in internal areas of the company.
Due to the fact that the energy market work with the financial field, we program a bot based on Artificial Intelligence and Machine Learning whose purpose is to review large amounts of data automatically, thus evaluating different risk scenarios and viability of future projects of different nature.
Also we provided an estimate of the optimal ROI that uses all existing variables and business rules in the stochastic evaluation process.
The main benefit of automating these tasks was decompression and optimization in internal areas of the company and better decision-making in asset trades based on facts.