Machinery : Special Purpose : Packaging
For over 40 years, top manufacturers in Life Sciences and Pharmaceuticals, Food & Beverage and CPG have called upon Grantek to solve their most complex business and manufacturing challenges. Grantek automates Pharmaceutical and Food & Beverage manufacturing operations, including integration with business systems for seamless solutions. Grantek helps customers meet the stringent requirements and challenges of the 4th Industrial Revolution. Grantek is a system integrator and solution provider with a specialization in Smart Manufacturing solutions, Manufacturing Automation solutions, Industrial IT/Cybersecurity solutions and Manufacturing Consulting services.
Modern Software Meets Legacy Hardware
However, through the efforts of one of our talented Principal Engineers, Grantek was able to pair the advanced PID Loop Tuning software LOOP-PRO TUNER (from Control Station) with Legacy Siemens/TI 505 PLCs as well as its newest compatible 2500 series PLCs processors manufactured by CTI.
Demo: OEE Accelerator Built with Perspective
Pharma 4.0™ Demystified: Navigating Improvement Opportunities with Solutions from Grantek
How Seeq, a Grantek Partner, Predicts Batch Quality at Life Sciences Manufacturing Facilities
Nothing is more important than protecting patient health. That is why quality is the most critical metric in pharmaceutical manufacturing. During manufacturing of new or existing medicines, drug companies need to test each batch to ensure that the quality consistently meets standards. Predicting the quality of each batch is a challenge for most drug manufacturers. It is a labor-intensive and time-consuming—though necessary—process. Typically, samples are taken and sent to the lab for analysis while the process is actively running. The analysis alone adds several hours to the process time. And, if the lab returns inadequate results, time-consuming—and often expensive—changes need to be made if the batch is recoverable. If not, the manufacturer can lose hundred of thousands to millions for the lost batch.
Using Seeq, the scientists running the processes built a model of process quality based on data from the OSIsoft PI data historian. The manufacturing team uses this model to predict the quality of the in-progress batches. This allows for modifications to be made during the production process before the batch would be lost due to quality issues.
If AI Is So Awesome, Why Aren’t You Using It?
With all these universal applications and clearly understood benefits, the writing appears to be on the wall: AI is the wave of the future, and if you are not using or planning on using AI soon, you will be history! Software, platforms, and technologies are already out there, yet adoption appears to be slow. Financial justification and benefits analysis seem to be no-brainers, yet no one is out rushing to make improvements. Why is that?