The Metals & Mining Industry Can Solve Their Operational Challenges
by Democratizing Analytics & Data
Like most industries during these crazy times, the Metals & Mining industry is facing its own set of challenges. It has to contend with increasing scarcity of high-quality ores, mounting costs, unstable commodity prices, and smaller profit margins. And don’t forget its health, safety, environmental, and carbon footprint challenges. No small feat.
Also, similar to most industrial processes, this industry generates an astounding amount of data, daily, at its mines and mining operations. Now, the Metals & Mining industry is understanding that in order to meet its challenges it needs to integrate all this data and use it to its full potential. There is an answer, and it’s right in front of them: self-service analytics.
Ensure Proper Asset Performance & Reliability
Process manufacturing companies have been gathering sensor-generated time series data for many years. Data analytics is not new. What is new, however, are self-service analytics tools that allow process experts to analyze their plant’s data without the help of data scientists and data modeling.
With a high-speed search engine, pattern recognition technology, and advanced filter options, a self-service analytics tool can analyze data to provide fast and interactive data-driven insights into industrial processes and asset performance.
Additionally, this software can proactively provide recommendations to uncover previously hidden correlations and identify possible root causes of process issues. It can calculate possible process trajectories and predict future evolutions of key variables. It can also be used to monitor degrading asset performance over time. The best part? Process experts without data science backgrounds can use it to easily analyze data.
Imagine being able to easily answer questions like…
- How is our production process performing?
- How often has this problem occurred?
- What is the root cause of this issue?
- Can we monitor deviations from good behavior?
- What is likely to happen next?
- Can we predict when maintenance is needed?
Additionally, valuable contextual information residing in various sources (maintenance data, operator logs, etc.) can be used to enrich the time series data to better understand operational performances. This contextual information can be analyzed separately to get deeper insights into processes and assets. And analytics-driven dashboards can be created with live data so that each stakeholder from “the control room to the board room” can control business outcomes.
These features help process experts identify new areas for optimization. With direct access to analytics insights, actionable information becomes available at all levels of the plant, allowing process experts to improve asset performance and reliability which in turn improves the production process across all stages.
Here are some examples of how the right self-service analytics software can help you with your day-to-day operations:
Provide Quality Assurance
Process experts can use a self-service analytics tool to analyze time-series data and contextual data to also precisely track operating zones. Multiple periods of best process performance can be overlaid and combined into a fingerprint. Fingerprints can be created for multiple tags and various production situations, such as the startup of a continuous process or quality control of a production batch. These can also be used for monitoring deviations and for assuring that the process is within specifications.
For both situations, this software can capture the event and label it automatically. Based on root causes found upstream and on fingerprints, early warnings can be used to improve control over the production process. Such a tooling can also provide appropriate instructions on what work needs to be done and when the work needs to be scheduled to reduce downtime and optimize maintenance. It will allow process experts to assure adherence to product quality and specifications.
Improve Compliance to Environmental Health & Safety Regulations
A self-service analytics tool can continuously monitor processes and send notifications when deviations from predefined fingerprints, process conditions, or operating zones occur. These early warnings improve plant output by allowing the plant to run at optimal energy consumption and waste reduction and at the same time, to comply with safety, health and environmental regulations.
Besides fingerprints, scatter plots based on “best operating zones” can be created. The designated “best operating zones” can be used in the same way as a fingerprint. Alarms can be put in place to notify process experts when deviations from these zones are detected. Monitoring the best operating zones reduces unnecessary equipment stress, increases asset reliability, and extends equipment lifetime.
However, monitoring performance in the control room doesn’t tell the full story. Having an analytics-driven visualization of your operational KPIs (like with TrendMiner’s Production Cockpit) does, and it helps your engineers and operators make educated decisions. Each stakeholder can use personal dashboards using specific trends or context views as KPIs and can see which parts of the process require extra attention or further analysis.
These trends can be shared across the company and used to directly start investigating process anomalies, production losses, or equipment inefficiencies, either via the context item listings or the dynamic trend views. The Production Cockpit provides operators with the opportunity to act and optimize operational performance before issues arise thus improving adherence to environmental, health, and safety regulations
Self-Service Analytics: A Metal Detector for your Data
To increase efficiency and productivity, you really need to be able to dig deeper into your data (no pun intended). TrendMiner helps you optimize your processes, reduce costs, and meet environmental and safety regulations. And if you can provide a safer working environment while at the same increase your profits?
Well, that’s like striking gold.
*Ba Dum Tss*
