1. AI (Artificial Intelligence) for your Plant Operations & Maintenance
Why do you need AI
AI (Artificial Intelligence) for your Plant Operations & Maintenance

2. What is AI (Artificial Intelligence)
AI can make machines learn from experience, adjust to new inputs and perform human-like tasks. Most AI examples that you see today e.g. chess-playing computers to self-driving cars, rely on deep learning and natural language processing.
Using these technologies, computers can be trained to accomplish specific tasks by processing large amounts of data and recognizing patterns in the data.

3. Decision: Less Data vs More Data
Engineers have historically used spreadsheets to plot graphs & use limited data to generate reports for decision making. Similarly, financial decisions were also made using the same method.
What do you think, which decision is going to be better, the one based on a few hundred hours of operating data or millions of hours? Based on a thousand rows & columns of spreadsheet data or millions of rows & columns of data?

4. Sensors Data & Written Reports
With all the sensors, probes, analyzers producing data every second, the Chemical plants are generating a lot of data but it is going to waste stored in the process historian because only a portion of that data is used in decision making to increase the efficiency or safety of the plant.
Similarly, the years of written maintenance or safety reports are going to waste because no one has the time or patience to read, understand and create a correlation amongst tens of thousands of pages of reports.

5. What will AI do
All of this can change because now we have computer models which can go through all of the data that your plant is generating and make sense of it to assist you in running your plant safely & efficiently. This is the technology of AI.
Now the computer models can use AI to:
Sift through millions of hours of data
Reject erroneous data
Read through millions of pages of text reports
Develop correlations and predict outcomes with an accuracy of over 90% in some cases

6. Your challenging questions
As an engineer or a manager of a Chemical plant, you are often faced with these or similar questions:
Should I run my reformer at higher temperatures to achieve a greater conversion?
How will this affect my catalyst activity & the overall mechanical integrity of the reformer tubes?
When should I service the intercoolers of my multistage compressor to get the best tradeoff between maintenance cost and the potentially degrading thermal efficiency of the compressor?
Can I can extend the time between plant outages without increasing my unplanned maintenance cost?

7. Answers by AI Example of answers to the above questions based on AI:
You can increase the reformer temperature by 50C. The gain in conversion efficiency will be more than the loss due to shortening of catalyst & reformer tube life.
The optimum duration to service your intercoolers is 6-8 months based on present operating conditions.
You may extend the time between planned outages by 4-6 months as it will increase your unplanned maintenance cost by less than 3%.

8. Sounds interesting? Next steps are…
If you think this sounds interesting then, here are the steps to follow:
We can set up a pilot scale project e.g. “AI Reformers”
You can provide us the operating data of reformers from your historian
We will develop models that will Predict When, Where & Why a particular problem event will occur
The model will be fine tuned & the accuracy of the model will be tested based on the past performance of reformers
The model’s prediction will be confirmed by you through your historical records
If the model proves accurate as per your expectations, you can choose to install it at your site