April 2, 2021

Glass manufacturer optimizes production line with Makoro™

This glass manufacturer has been using reports and analysis techniques for the last 10 years to understand its production data. They have been using a variety of data aggregation and statistical analysis tools for self-service analytics, building their own “screens” using their home-grown and vendor-supplied tools, and finally, rolling out these tools to their 4 locations globally. 

The manufacturer has an advanced data analysis infrastructure, which supports both mobile and desktop to enable easy access from anywhere. They typically monitor around 800 to 1000 data points in their lines across several processes. The current process looks like this:

1. Aggregate data from OPC servers and data historians.
2. Based on this data, process experts work with a set of tools to monitor the processes to make sure they are working optimally.
3. A separate team of data experts uses this data to visualize, create and share reports and dashboards.
4. At several points during this process, the data engineers transfer parts of the data to a cloud-based advanced analytics system for deeper analytics.
5. If one location built a set of asset monitoring tools to send notifications based on asset conditions, they would then share the tools across locations. This “rollout” happens once in 6 months.

Business Challenge

At a recent virtual event, the manufacturer learned about Makoro™ and how they can potentially move away from rolling out tools to rolling out recommendations to their plant locations. Recommendations are giving them new ideas for improving their production operations. Moving away from making data and tools available to rolling out recommendations give them a faster return on investment as they can see the improvements each quarter, and they can spot the potential for further improvement. 

Transformation Story

With Makoro, they are gradually phasing out reports and dashboards as recommendations and insights are available in almost real-time. Most of the ad-hoc analysis and manual pushing data on demand to the cloud is being taken away as Makoro™ automates the analytics on the cloud and edge as required. Makoro™ makes the rollout process redundant as each location has access to recommendations based on their data, syncing up learning from these recommendations once each month. Lack of manual intervention in Makoro™ will allow them to monitor 500 additional data points on each of the main lines, and also extend monitoring to other auxiliary processes.

Results

With the adoption of Makoro™, they are putting their data historians and OPC infrastructure on the back end of Makoro™ connectivity. They are able to leverage all the data they have been gathering over the last several years, but instead of using the suite of analysis tools, they are letting Makoro™ do all the heavy lifting in terms of analysis, analytics automation, and visualization. 

The end goal is to use Makoro™’s predictive recommendations to eliminate unplanned downtime and production outage completely.