In the initial six to eight months, I used it for process analysis, like identifying the different tags through a historian and then making some use cases out of them. This is a very simple yet powerful tool that can connect to the historian in real time, and then we can perform some formula-based calculations. It is very useful. So, I started with basic process analysis and then went into the predictive part, which is also very useful. I've used the prediction part to create different inferences in my industry. Some lab results and analyses take time, like eight hours or seven days. So, to create real-time inferences for such signals, Seeq was very useful through its predictive capabilities.
The solution is used for time series data analysis. It is very useful for the oil and gas industry, where we use compressors, pumps, and gas turbines and need to monitor them remotely. Seeq is useful in such cases. I support more than 100 pieces of equipment for a customer in the oil and natural gas industry. There are ten gas turbine generators for power generation. We have to monitor them. A gas turbine has 150 to 200 parameters to monitor. We have to monitor vibration parameters, lube oil system, and auxiliary systems and notify the organization if we notice any abnormalities. We use Seeq to analyze the parameters daily, weekly, or monthly. If we notice any deviation, we must analyze it. For example, if we see an increase in the bearing temperature, we immediately discuss it with the on-site team. The team checks whether the lube oil is contaminated. If there is contamination, the team takes action accordingly. It could also be a bearing issue. We must run the machines without any damage to avoid catastrophic failures. Seeq is a useful product. The systems are not operated manually in the oil and gas industry. They are operated remotely. Usually, if pumps are used, there will be two or three pumps. Two pumps would run, and one would be on standby. If a pump needs to run for 500 hours, we can calculate it using Seeq. Once the 500 hours is up, the pump stops, and the standby pump automatically starts running. It is one of the biggest advantages of the solution.
I primarily use Seeq to monitor various process tags and notify me when they are outside the expected parameters. The software allows me to analyze substantial amounts of data, which I find quite interesting and valuable.
We use Seeq to convert real-time data into graphs for monitoring and surveillance. It helps us track real-time data and visualize it effectively. In the oil and gas industry, we use Seeq for process optimization. We analyze real-time data to understand downtime and other issues from the previous day at specific wells. This data helps us make informed decisions and plan future actions based on past performance.
We used real-time sensor data to predict equipment failures and other issues. The data came from a fracturing process, including lubrication systems, and was processed in Seeq. Seeq has three apps: one for visualization, Workbench (a point-and-click tool), and DataLab, which is Python-oriented. I used all three to build use cases. For process optimization, predicting equipment failure helps save costs by preventing downtime. This directly impacts production and reduces non-production time. Seeq is cloud-based and connects to various data warehouses like Amazon, Microsoft Azure, and others. You can integrate it with around 200 data providers, which gives flexibility for data storage. However, Seeq doesn’t store data; it requires connection to external databases.
I'm a process engineer in the oil and gas field. I use the solution for daily monitoring, surveillance, and time series analysis, where I can build prediction models and root-cause failure models. We're building a model with Seeq.
I first used Seeq for a customer who was starting up their facility. We used it to diagnose problems such as water utilization and tuning control loops, along with various other process issues.
I represent the consulting part of our company. We support multiple customers in India, Southeast Asia, US, and Europe. Our daily requirements involve building data science algorithm applications using Seeq Data Lab, building workflows using Seeq Workbench, and developing dashboards on top of Organizer topics.
Supply Chain Analyst at a manufacturing company with 10,001+ employees
Real User
Top 20
May 21, 2024
I generally use it for time series data analysis. Seeq is famous for doing time series analysis, like statistical process control, quality control, and different types of analyses like regression analysis or correlation relationships. All these different kinds of analysis can be done in Seeq, which is very efficient.
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In the initial six to eight months, I used it for process analysis, like identifying the different tags through a historian and then making some use cases out of them. This is a very simple yet powerful tool that can connect to the historian in real time, and then we can perform some formula-based calculations. It is very useful. So, I started with basic process analysis and then went into the predictive part, which is also very useful. I've used the prediction part to create different inferences in my industry. Some lab results and analyses take time, like eight hours or seven days. So, to create real-time inferences for such signals, Seeq was very useful through its predictive capabilities.
The solution is used for time series data analysis. It is very useful for the oil and gas industry, where we use compressors, pumps, and gas turbines and need to monitor them remotely. Seeq is useful in such cases. I support more than 100 pieces of equipment for a customer in the oil and natural gas industry. There are ten gas turbine generators for power generation. We have to monitor them. A gas turbine has 150 to 200 parameters to monitor. We have to monitor vibration parameters, lube oil system, and auxiliary systems and notify the organization if we notice any abnormalities. We use Seeq to analyze the parameters daily, weekly, or monthly. If we notice any deviation, we must analyze it. For example, if we see an increase in the bearing temperature, we immediately discuss it with the on-site team. The team checks whether the lube oil is contaminated. If there is contamination, the team takes action accordingly. It could also be a bearing issue. We must run the machines without any damage to avoid catastrophic failures. Seeq is a useful product. The systems are not operated manually in the oil and gas industry. They are operated remotely. Usually, if pumps are used, there will be two or three pumps. Two pumps would run, and one would be on standby. If a pump needs to run for 500 hours, we can calculate it using Seeq. Once the 500 hours is up, the pump stops, and the standby pump automatically starts running. It is one of the biggest advantages of the solution.
I primarily use Seeq to monitor various process tags and notify me when they are outside the expected parameters. The software allows me to analyze substantial amounts of data, which I find quite interesting and valuable.
We use Seeq to convert real-time data into graphs for monitoring and surveillance. It helps us track real-time data and visualize it effectively. In the oil and gas industry, we use Seeq for process optimization. We analyze real-time data to understand downtime and other issues from the previous day at specific wells. This data helps us make informed decisions and plan future actions based on past performance.
We used real-time sensor data to predict equipment failures and other issues. The data came from a fracturing process, including lubrication systems, and was processed in Seeq. Seeq has three apps: one for visualization, Workbench (a point-and-click tool), and DataLab, which is Python-oriented. I used all three to build use cases. For process optimization, predicting equipment failure helps save costs by preventing downtime. This directly impacts production and reduces non-production time. Seeq is cloud-based and connects to various data warehouses like Amazon, Microsoft Azure, and others. You can integrate it with around 200 data providers, which gives flexibility for data storage. However, Seeq doesn’t store data; it requires connection to external databases.
I'm a process engineer in the oil and gas field. I use the solution for daily monitoring, surveillance, and time series analysis, where I can build prediction models and root-cause failure models. We're building a model with Seeq.
I first used Seeq for a customer who was starting up their facility. We used it to diagnose problems such as water utilization and tuning control loops, along with various other process issues.
I represent the consulting part of our company. We support multiple customers in India, Southeast Asia, US, and Europe. Our daily requirements involve building data science algorithm applications using Seeq Data Lab, building workflows using Seeq Workbench, and developing dashboards on top of Organizer topics.
I generally use it for time series data analysis. Seeq is famous for doing time series analysis, like statistical process control, quality control, and different types of analyses like regression analysis or correlation relationships. All these different kinds of analysis can be done in Seeq, which is very efficient.
I use the solution for trend visualization and real-time data. We use Seeq to connect various pipelines and create dashboards.