CLICK AI is applicable to virtually every part of the energy industry. We provide solutions such as maintenance prediction, safety monitoring, energy consumption anomaly detection, production optimization, process parameter optimization, energy demand forecasting, and electricity contract capacity optimization.
It is important to make the right decisions quickly. In a typically one-way manufacturer's process, planning and data can be organically linked to each stage via CLICK AI, enabling rapid and agile development.
It is difficult to determine where power is being used from the power consumption data. This also makes it difficult to detect malfunctioning equipment. Malfunctions or misconfigurations within the system can lead to negative effects such as fire. CLICK AI using the deep learning artificial intelligence can detect abnormalities in energy consumption through continuous monitoring, energy consumption analysis, and new problem detection and analysis to make decisions very quickly. This improves performance and helps you avoid financial losses.
Deep learning can be used to analyze and predict video and image-based data to detect and warn safety risks in real-time. Customers can remotely verify remote operational security and detect asset integrity through upstream, midstream and downstream operations. You can avoid dangers through fast processing and feedback in the field by monitoring risks such as smoking behavior with image classification or object recognition AI using CLICK AI.
When the factory is measured with IOT, the available data will surge. CLICK AI enables operators in digital factories to use data insights to identify potential production refinement and predict quality, cost and throughput. As a result, waste and disruption can be reduced and yields can be improved to develop operational efficiency.
CLICK AI can accurately predict asset failure by aggregating data from sensors, device enterprise systems, and operating systems. CLICK AI provides planners and operators with a comprehensive insight into asset risk to maintain higher asset availability, service-based differentiation, and lower maintenance costs.
Optimizing process parameters using deep learning can be effective even in well-established industries such as energy. The data-driven approach allows you to find complex nonlinear patterns in your data, transform them into models and apply them to fine-tuning process parameters. Existing systems relied on a specific technician's rule-based framework, expertise, and domain knowledge. Today, however, the process is becoming more and more complex due to the interconnection of each system, and the limitations of including all aspects of the process in a rule-based expertise-based model are becoming clear. The deep learning of CLICK AI artificial intelligence provides a solution to overcome the problems caused by increasingly complex processes.
Research shows that 79% of companies with good performing and optimized supply chains have achieved greater sales growth. Deep learning helps you optimize your supply chain by identifying problems across individual and collective supply networks, and streamlining operations to address supply network variability. Artificial intelligence models trained through CLICK AI continuously analyze supply chain data to find new patterns. This pattern provides an opportunity for companies to optimize their supply chain processes by identifying with predictive accuracy a set of factors affecting the supply chain.
The growing world population and the growth of smart devices are a major cause of high power consumption. In particular, the prediction of a sudden increase or decrease depending on the specific situation is important for energy supply. Deep Learning can predict how much energy demand will be on a given date by analyzing the change in daily energy consumption of individual customers over time. Deep learning models using CLICK AI can predict energy demand and consumption with high accuracy. These forecasts can be used by facility and building managers, energy and utility companies to deploy energy-saving policies, and manufacturers can plan how to optimize specific operations and energy storage systems.
CLICK AI can leverage deep learning in real-time to improve operational efficiency and profitability across sales, marketing, and customer services. CLICK AI's CRM can provide real-time AI generation forecasts and scores with insights from the integration of internal and external datasets.
Cost reduction is one of the important factors in competitiveness. The penalty for usage time factor and excess capacity in the electricity supply bill can be a big penalty for large corporations such as businesses and hospitals. The deep learning of CLICK AI can reduce costs by optimizing electrical contract capacity by leveraging data accumulated from customers' past behaviors to balance excess contract terms in contracts and properly predict future needs.