Illuminate Your Production Process with Context Information
In the world of process manufacturing, there are all kinds of events that can impact your operational performances. Whether you have a continuous production process or work in batches, a wide range of contextual data is available that is probably going underutilized. Think of the different captured events you may encounter… maintenance stops, process anomalies, asset health information, external events, production losses, etc. Is all of the data captured in your organization illuminating your production facilities so you can operate faster? In many cases we’ve seen that even if a factory is run by top experts, with all of the incredible knowledge their minds’ hold, they’re basically running the factory in the dark if the context data isn’t being used.
Shedding necessary light onto time-series data through dynamic contextualization can take you to next level of operational excellence. And when you’re able to capture and combine contextual information about critical events? Well that can illuminate your entire production process and save you and your organization time, money, and resources.
The Value of Contextual Information
Factories today are capturing and storing an enormous amount of data that is either directly or indirectly related to the production process. While contextual information tends to reside in various data silos like your LIMS, MMS or OEE systems, captured contextual information can easily be leveraged.
Many factors influence operational performance and therefore the product quality, which can be included to analyse, monitor and predict operational performance.You may already be aware that self-service analytics sheds light on operational performance but if you have all of the available contextual information from other applications, you have a much better visibility to your operations. You can drive much faster over an illuminated highway than in the dark. That’s also the case when contextual information: it helps you to analyze faster, run more efficiently, and have more yield.
Many factors can influence operational performance
Using a self-service analytics tool like TrendMiner’s ContextHub allows users to search for context items and gives them the power to actively utilize it within the time-series data analysis itself. Users can visualize, filter, and overlay time periods in the trend views so context items can become a rapid starting point for trend analysis.
Additionally, this contextual information can be used in many other beneficial ways to jump your day-to-day manufacturing hurdles streamlining your work. You’ll be able to:
- Track events
- Create tags to follow equipment efficiency
- Create new fingerprints and monitors for operations
- Set alerts to notify operators when deviations or issues occur
Real World Uses
Tracking Recordable Reportable Events
One of the biggest concerns for manufacturing plants is tracking recordable, reportable events. If your plant passes a certain threshold, for whatever permit your plant might have, you are required to report the event to the government to explain what happened. This information is often saved in separate Excel files depending on what had happened or how it is related to the event, which can result in a multitude of separate files that need to be kept track of. And this approach also makes it difficult to keep detailed and accurate notes and records of the event.
Self-service analytics allows process experts to add context items and detailed annotations for the recordable and reportable events you need to track. And with this information, experts can pinpoint the incident using the data available through the historian.
Creating Monitors to Track Emissions
Another extremely useful way contextualized data can make an impact on a day-to-day basis is with the creation of monitors. In this instance an environmental team is able to keep track of emissions and alert other teams of a possible deviations.
For example, alarms could be set to monitor the flow of emissions to the flare and other environmental safety equipment. There could even be a series of alarms that could notify personnel once the flow goes out of normal range but is still within the permit limits so action can be taken.
An additional alarm could also be set for the actual permit limit which would help pinpoint when the event actually happened. Once the investigation starts, all the quantitative information would be available in the platform, and all the qualitative information can be added to the context item. This lets the environmental team gather all relevant data quickly and reliably without missing any valuable information that could get lost in Excel files. The information is centralized and accessible to all personnel within TrendMiner’s easy-to-use solution.
Creating Tags to Track Equipment Efficiency
TrendMiner could be used to create tags to follow the efficiency of equipment. For example, tags can be created to track the efficiency of a heat exchanger feeding the kerosene scrubber. The efficiency of the heat exchanger practically determines how much VOCs are recovered before being burned at the flare. If the level gets bad enough, a permit deviation can be seen from the flare outlet.
With process monitors in place, an email can be sent to inform personnel that deviations are likely to happen or are happening, so they can check the processes. This is especially beneficial as the people out on the plant floor are not necessarily familiar with the governmental rules and regulations regarding environmental permits, so they might not know to share the information with environmental team. Additionally, if the subject matter experts in this area can get the information directly from the process, they can act much faster. The end result is a decrease in the number of deviations from permitted process emissions.
The light TrendMiner can shine lets process teams be proactive instead of reactive – lets them run the best operations possible.
Created by Engineers, for Engineers
TrendMiner was created by engineers, for engineers and with the mindset that the best results are gained when subject matter experts can analyze the data themselves. With that, you get a better understanding of your operational performances as well as new potential starting points for your optimization projects.
As previously mentioned, whether you have a continuous production process or work in batches, putting your context data to use with a self-service analytics tool can shed new light on your operational performances. Don’t forget your shades.
