Paper has been made and has been used for hundreds of years and is so common in today’s world that people don’t think about what it consists of.
Woodcut “Paper Maker” by Jost Amman from “Eygentliche Beschreibung aller Stände”, 16th century, Copyright: Public Domain
But when viewed through a microscope in fact paper is a network of natural cellulosic fibres bound together. And to a large extent, it is the strength of bonding between these individual fibres that controls the strength of paper. And then there is crill – particles too small to be visible under an ordinary microscope. But exactly those particles are of great importance for fibre bonding in paper. Crill makes a cellulosic fibre in paper tissue look “hairy” and it comes at only 1% of the thickness of the fibre itself.
Fig. 2: Schematic diagram: Cellulosic fibre with crill
Unfortunately when creating a paper product with a desired characteristic like strength the only available development method was to perform lab testing until the optimal recipe could be verified. If there had been a way of determining exactly what the paper would be like this would have improved the process dramatically by ensuring stable pulp quality, allowing for quicker grade changes and reducing efforts for lab tests. Crucial in a low-margin business!
Recently we learned this new method – called online “crill measurement” – has been made into a robust online analysis unit and is now in productive use at a first pulp producing unit in Sweden. This shift from reactive processing to predictive processing may have the potential of changing the production process of paper fundamentally – after hundreds of years of process refinement have already taken place!
Applying the “crill approach” to the production, sales and distribution
But what if this fundamental shift from reactive processing to predictive processing was not restricted to production methods but would be applicable to any other process related to production, sales or distribution of paper? Discussions with the Association of Germany Paper Producers VDP in 2014 already indicated there was a strong interest in predictive processing. In fact we believe there are many opportunities to enhance production planning, achieve the expected quality, improve machine uptime (or lower the risk of failure) through predictive processing. If a firm is able to leverage the full potential of shop-floor data being available through historian systems, machinery and sensors it would allow for significant insight into current processes and for recognition of trends in production output, product quality, or machine condition. If this data can be enriched with business data which traditionally has been processed in SAP applications anyway, the result of shop-floor analysis can be correlated with company goals, or product profitability.
Check out SAP HANA IoT (Internet of Things) Edition
Check out SAP HANA IoT (Internet of Things) Edition which can be the basis for connecting the shop-floor with the enterprise layer. The new SAP Internet of Things solutions include SAP Predictive Maintenance and Service and SAP Connected Manufacturing. These new solutions leverage the SAP HANA Cloud Platform for real-time and predictive insights based on sensor data from connected devices.
Predictive Maintenance and Service provides full visibility into current asset health; predicts failures and applies preventive measures by analyzing sensor data combined with business data.
SAP Connected Manufacturing enables the Internet of Things for manufacturing operations. See here for more information: SAP / IOT