Combining Quality, Energy and Operational data to determine which line is the best to produce a specific product on
Beaulieu International Group
Beaulieu International Group (B.I.G.) is a global specialist in raw chemical materials (polymers), semi-finished engineered products (yarns, fibres, technical textiles and technical sheets) and is a leader in a broad range of floor coverings for the residential and commercial markets (vinyl rolls, vinyl planks, laminate, parquet, carpet, needle felt, artificial grass and mats) as well as upholstery fabrics. Headquartered in Belgium, B.I.G. employs more than 5,000 people across 29 plants with a major presence in 17 countries all over Eurasia, the Americas and Oceania. For more info see the website.
A Proof of Concept to determine the added value of Manufacturing Analytics
Beaulieu initiated a Proof of Concept on one of the plants to see if Wonderware Intelligence could help them gaining insight in the performance differences between the lines for the products that are produced on multiple lines. The performance score of a product on a line is determined by a combination of 3 factors: Quality, Energy Consumption and Meltpump Deviation. Because data for each of the 3 factors was stored in different source systems, their challenge was to merge all data (automatically) into a single data store, suitable for analysis.
Choosing the best production line for each product
The Wonderware Intelligence software was used to build to create a contextualized data set that refreshes automatically. On top of that data set a performance dashboard has been built. This dashboard gives insight in the best line(s) to produce a specific product on looking at each factor, or all factors combined. Thanks to Wonderware Intelligence, Beaulieu was not only be able to detect optimizing possibilities, improve quality results and reduce energy costs, they could also spare a lot of time because process engineers will not have to collect, clean and prepare data manually anymore.
Data made visual to gain insights
The image below shows one of the dashboards that was delivered during the Proof of Concept. Each KPI is calculated by comparing several process parameter actuals with their given targets. With the software we managed to create relationships between different types of data coming from different source systems. This resulted in a single contextualized data set that made it possible to build a set dashboards.