Project Excerpt
A light MES solution that scales quickly and easily. One that would help standardize data collection across global facilities to improve production performance.
- Client: Carlsberg, a Danish Brewing company with a global presence and that is one of the world’s leaders in the brewing industry, founded 172 years ago
- Date: 2019
- Link: Carlsberg Group
The Company
Carlsberg turned to Autoware, an Italian software company focused on implementing digital transformation in the manufacturing sector, as the technology partner to help them improve their data collection and processes.
The need
Carlsberg had already laid much of the groundwork toward standardization across facilities, but their MES Light solution better address the gaps created by legacy equipment and variations in data collection, architecture, and software. Notably, the standardization of data and metrics allows Carlsberg to evaluate machine performance and productivity relative to other factories. After launching in just three months, it also helps satisfy the need to scale quickly across multiple facilities. To date, the application has been rolled out at 29 Carlsberg facilities.
The Autoware’s Solution
To develop the application, Autoware utilized Kepware, a software that automatically pulls data from a variety of automation devices and software applications and aggregates it into a uniform data model. In addition, Autoware used ThingWorx, an end-to-end industrial IoT platform that provides visibility into production and asset health with real-time data analytics and a rich array of insights and production reporting. Together, the technologies allowed Carlsberg to monitor machine data and project it onto dashboards.
The data gives operators a clear understanding of how the line performs against targets, while real-time alerts help them quickly identify and resolve any production issues. Similarly, some floor operators have tablets equipped with an app that leverages ThingWorx data to track the downtime of a specific machine and proposes the reason in real-time; the operator can then confirm the next actions to take, even from a remote location in the facility.
