The Viridis platform is extensively based on the concepts of the Internet of Things, Big Data, and Industry 4.0, as it is capable of capturing, storing and processing large volumes of data on the consumption of energy and utilities of any operational unit, whether a specific machine or a production process as a whole. These data, combined with information about the context in which they were recorded (production plans, process variables, operational parameters, among others), makes possible, using the techniques of Machine Learning, the construction of predictive models that are combined to create a digital representation of that asset – a digital twin. The large integration capacity of the platform facilitates the capture of relevant data, while its modeling and visualization capabilities make the use, interpretation, and evolution of digital twins easy, resulting in significant value creation for our clients. Click here to learn more about our solutions.
Viridis offers a cloud-based commissioning model using Cloud Computing environments, with the option of public or private cloud environments. There is also the option of using the environment contracted by the client from their current cloud providers. In both cases, data communication with the sites is performed by the Viridis IoT Gateway, a technology developed by Viridis exclusively to provide bi-directional integration in real time with multiple local systems, in addition to performing edge analytics. Commissioning in the cloud offers federated authentication, public or private cloud, and encryption, among other features to provide the highest level of trust and security. Click here to learn more about our solutions.
The Viridis platform is extensively based on the concepts of the Internet of Things, Big Data, and Industry 4.0, as it is capable of capturing, storing and processing large volumes of data on the consumption of energy and utilities of any operational unit, whether a specific machine or a production process as a whole. These data, combined with information about the context in which they were recorded (production plans, process variables, operational parameters, among others), makes possible, using the techniques of Machine Learning, the construction of predictive models that are combined to create a digital representation of that asset – a digital twin. The large integration capacity of the platform facilitates the capture of relevant data, while its modeling and visualization capabilities make the use, interpretation, and evolution of digital twins easy, resulting in significant value creation for our clients.
The Viridis system has a built-in BPM tool that is integrated with all its modules. The Viridis BPM tool allows each company to define how they should execute the processes of costing, forecasting, budget management, contract management, performance management, and many others. In addition, it provides metrics of execution of all processes, allowing greater visibility and continuous improvement of managerial workflows. Click here and read more about Viridis's Products.
The Viridis platform manages the whole cost accounting discipline, from meters to uploaded transactions in ERP systems. It supports direct and indirect costing rules from multiple sources, and provides managers with cost tracking resources to further enhance transparency and accountability.
The Viridis platform handles all data management necessary for proper cost accounting, automating the whole workflow from meters and costing rules to indicators and accounting transactions. The Viridis costing module integrates directly with ERP systems, improving process accuracy, timeliness, transparency, and agility.
The Viridis platform explores the concept of a data lake to combine time series sampled in real time with transactional data from management systems. To deal with large volumes of data, the system has a high-performance data historian with efficient storage and response times, capable of holding thousands of time series for many years. All this measurement data is combined with data from legacy systems such as ledger transactions, production orders, maintenance orders, laboratory data, among others. The system automatically correlates multiple types of data, temporal and transactional, allowing disruptive views on energy performance and operational efficiency.
