Key to Digital Transformation in Cement Production
The key to the digital transformation in cement production Is Sage, Sabia’s most recent advance in technology to provide Better performance Better value and a Better customer experience.
Quality Management Pioneers
SABIA has been helping customers manage their material quality for over 15 years and has continued to incorporate new technologies into our products as we evolve. Over time SABIA has managed to show value in ever broader areas of Cement Production to include the following applications
- Receipt Monitoring
- Coal Blending
- Pile Building
- Quarry Operations Control
- Raw Mix Control
- Finish Mill Control
SABIA’s flexible hardware and software platform has allowed us to develop a sophisticated system that can easily adapt to new applications and develop algorithms that can be easily adapted to new environments.
Over time we began integrating more and more data into our various Cement applications. This made us realize the vison of being able to manage quality and operating costs across the entire plant using Artificial Intelligence, and Machine Learning methods. PGNA analyzers are sensors providing key data to the system, but Sage can use data from anywhere in the plant.
This was the beginning of Sage, which works as an analysis and control system. Separate from the DCS or plant control system, Sage is based on Machine Learning. This tool can be the basis for the Digital Transformation of a Cement plant.
What is Digital Transformation? Key to Digital Transformation in Cement Production
Digital transformation is the process of using the vast amounts of data generated by todays cement plants and fuel yards to greatly improve efficiency, quality and cost control. This is made possible by using a combination of Machine Learning and Artificial Intelligence.
All Cement Plant operators are experts in forensics. After a significant problem or failure, they go back to dig through the data, find out what went wrong, and hopefully determine how to prevent it in the future.
What if this long investigative process could be avoided altogether? Most of the time there were indicators, precursors, or Anomalies showing that something was wrong, that if acted upon may have prevented the failure entirely.
Experienced operators have gone through enough problems recognize some of these anomalies, but they can’t see them all due to their limited scope of information, human capabilities, current work load, and authorization restrictions. This prevents them from putting warning signs together quickly enough to prevent problems from occurring.
But what if you could capture every anomaly at all times and see how each anomaly is connected to any failure? What if someone was always paying attention to everything all the time?
This is what happens with Digitization and Machine Learning. It has the effect of having very smart, very experienced, eternally vigilant “people” with great judgment, lighting fast reaction times and perfect communication in every seat on every shift, forever, with no training costs. It gives you the ability to see potential problems in time to take action to prevent them. In some cases, it can find and fix the issue without any intervention at all.
Threshold Management Key to Digital Transformation in Cement Production
Recently I was speaking with a Cement plant manager and I asked him about his plant capacity. He said his plant was rated at 4000 TPD but he ran it at 3400 TPD. He was uncomfortable running it at higher capacity due to variations in operating parameters. His level of control was limiting his capacity.
Tighter and faster responding control systems, coupled with anomaly detection allow plants to be run more efficiently as well as to run closer to their design capacity.
Many maintenance intervals are determined by factory recommendations or operator experience. We all used to religiously change the oil in our cars every 3000 miles. Now we do it when the computer in the car tells us to. A smart dashboard management system of maintenance can be used to better plan outages or to increase the time between outages. Part wear can be monitored by IoT enabled devices so replacement can be performed before failure, but not before the use of the part has been maximized.
Unscheduled outages are the worst nightmare of plant operators. Anomaly detection is key to being able to prevent these costly events. Smart systems can provide the alarms and alerts needed to give of potential problems in time to act.
Digital Twin Key to Digital Transformation in Cement Production
Having all the data accessible to one application coupled with strong Business Intelligence, Analytics, and Data visualization tools allow customers to create simulations of their processes, a digital replica of their operation. This allows close study of processes as well to the ability to understand the effects of making a process change without risking poor results or equipment damage. Having a simulation tool like this can greatly enhance a plants ability to implement changes and improvements.
Data Extraction: The Plumbing
This is the least glamorous and most important part of the product. SABIA experts work with your IT team to gather data from disparate parts and systems in your plant. Once data is gathered it is stored in an optimized way for easy retrieval including strong data links for reliability, security and integrity.
Business Intelligence: Data Democracy
Business intelligence is the sort of data that utilizes reports, status screens, and other tools to manage the business. These tools allow for a significant modernization of processes while using state of the art methods of data visualization. Data is also “democratized”, meaning that everyone has access to the same data in the same way. This reduces the practice of using multiple spreadsheets to manage operating data and reporting, which frees up time and eliminates error.
Statistical Modeling: Putting the Data Together
New statistical modeling languages like Python and Hadoop allow for simple and fast creation of control algorithm modeling. They languages allow you to set and modify control rules in algorithms simply and easily. This allows system providers to build tools allowing your best people to change and model process specific control algorithms. These modeling languages also allow users to consider many more variables in equations to allow a much higher degree of control. This allows plants to capture the experience and wisdom of their best people inside control modeling software, multiplying that knowledge in ways never seen before
Machine Learning: The Quantum Leap
Sage provides unprecedented access to great data being used to create new plant control algorithms. Sage can also use these tools to monitor IoT equipped hardware to control maintenance intervals and warn of potential failures. These are huge strides and can transform the plant performance. Still, this is just the beginning of Sage.
Problems must be observed, solutions theorized and tested, algorithms created and installed. All of this takes substantial time and resources…. But what if the machines themselves could learn? Machine Learning tools can continuously study outcome data and compare it to input data, identifying patterns and continuously optimizing inputs for the best possible output. Machine Learning can consider as many inputs and outputs as needed. The process of optimization can be reduced from weeks to a day, or even a few hours.
This optimization takes into account changes and degradations in inputs like equipment performance or additive and fuel changes. This results in optimum solutions to the very complex problem of the compromise that is running a Cement plant, day in and day out.
Security and Administration: Getting the Details Right
This is not the exciting part but it is critical for any software platform’s success. Logins, user access profiles, user specific security settings, as well as access to settings and control parameters for the software itself, set up simple and secure.
The Unified Console: Data Visualization
One of the challenges of having all of this data is finding a way for people to use it. Modern analytical and display tools allow users to quickly create, change and reconfigure reports, then display and provide real time analysis of parameters as they change. This turns data into information in the way that you need every day.
Sage Process Key to Digital Transformation in Cement Production
Upon agreement to engage, SABIA’s international team of experts will visit the site in question to meet with management and technical personnel. We will conduct a process assessment, data assessment, and participate in setting goals.
Though interview and observation SABIA will obtain an understanding of your process, pain points, and key areas of desired improvement. This can take 1-3 days depending on size and scope of the desired process.
Data Assessment Key to Digital Transformation in Cement Production
A SABIA representative will take the time to gain a thorough understanding of specifically what data is available, additional data that may be desired, where/how data is stored, and how data is accessed. From this process we can understand what hardware and networking modifications may be required.
Sage is designed to run on cloud servers. These can either be installed on-premises or purchased from a cloud service. SABIA will recommend optimal changes to your computing environment needed to support Sage.
Setting Goals Digital Transformation in Cement Production
This is the most important part of the process. Now that we understand the capabilities your existing system and process, we can help you to quantify expected improvements the Sage system and set goals with deliverables for the project. Once these goals are understood and agreed on, SABIA provides a detailed quotation and project schedule.
ROI Guarantee Digital Transformation in Cement Production
The specific process improvements and tools that Sage can provide will be a dramatic performance improvement. We are confident Sage will provide value so in this process we will jointly agree to specific cost savings or productivity improvements that will be the basis for price and pay