Bayer Pharmaceuticals, Garbagnate, Italy - Smart Factory

Article part of Smart Engineering for a Better World - Essays for 55th India Engineers’ Day

2022

https://www.capgemini.com/insights/research-library/industry-leader-perspectives-saskia-steinacker-bayer/

"Showing concrete examples where digital has created a larger value, such as the ones we have in our digital health and digital farming space, is a very crucial step for people to understand how digital technologies can help to achieve a better life for our customers."

Yes. Employees have to be given knowledge first. Then concrete examples have to be demonstrated to them. They should be allowed to use and operate smart systems to develop idea regarding application of smart engineering possibilities. Every firm has to do this multiple times, each time enabling some employees to make valuable contributions in new smart engineering applications.

Jul 14, 2021

Every year the World Economic Forum's Global Lighthouse Network honors companies that use Industry 4.0 and Internet of Things (IoT) technologies to make their operations more efficient, environment-friendly, and lower cost. “Smart” applications have been especially valuable to manufacturers during the COVID-19 pandemic for finding ways to maintain operations and stay competitive. To date 69 factories have been honored as “lighthouses” for leading the way in establishing smart operations that are more productive, safer for the environment, and use fewer resources. 

2020

JAMES THOMAS, BAYER AG

James Thomas, Head of Digital Strategy, Bayer AG Pharmaceutical Division, in a talk titled “Driving Digitalization for Pharma Manufacturing” identified several activities and benefits associated with using digitalization to connect key equipment and lines across the manufacturing network: getting real-time operational data, insights from advanced analytics, data and insight sharing to enhance product launches and predictions, and avoiding machine down-time and equipment failure. The challenges are: connecting  historically heterogeneous equipments, the current management of data/buffering, the data integration blueprint, and implementation issues in the brownfield sites.

Thomas expects the achievement of autonomous planning and  a new level of data availability that allows companies to do more comprehensive simulations; the integration of suppliers, raw materials, and contractor‘s activities; and the better identification of downstream costs and opportunities. As challenges, he identified collecting data from multiple internal and external data sources; the last mile access data mechanisms (i.e., the telecommunications networks that deliver data to end users), which often have limitations and costly to manage; the limited willingness of many to share data; and the need to take a leap of faith by management in the absence of hard data to show financial benefits. The qualitative logical ideas regarding benefits are there.

Bayer is actively combining  data in a data and analytics platform to implement use cases, drive collaboration, and create new business models in lighthouse projects. In the process it is developing skills and a “digital mindset” across the organization.

https://ispe.org/pharmaceutical-engineering/march-april-2021/2020-ispe-pharma-40tm-virtual-conference-highlights

2019

Bayer Pharmaceuticals, Garbagnate, Italy - Smart Factory

The plant  produces and packages pills,

The Garbagnate pilot, which was launched in September 2017, uses machine learning and analytics to increase operational efficiency, a digital twin (digital replica technology) for employee laboratory scheduling, and augmented reality (AR) devices to reduce changeover times when switching product lines. In each case the front-end applications are connected to 15 data sources and integrated into the plant’s IT infrastructure. Ongoing operations are now more transparent to employees on the factory floor and they get real-time updates on performance, helping them make smarter decisions, react faster and utilize resources more efficiently,


According to  Hans-Walter Hoehl, head of efficiency, innovation and projects within the product supply unit at Bayer’s pharmaceuticals division, in certain areas, such as coating tablets, further optimization of the manufacturing process and elimination of  root causes for potential variations could be done due to smart features implemented.


Data scientists played a key role in digitizing Bayer Pharmaceuticals’ plant by developing the algorithms that turn data into useful insights to enable more efficient production of drugs. Three steps were required to develop the algorithms. First, the data had to be prepared: different data sources need to be “cleaned” and connected to be applicable for advanced analytics. Next, the algorithms had to be set up through a modeling process. Different machine learning techniques were implemented to enable the algorithms to make predictions. Finally, the company needed to figure out how to visualize the insights in ways that employees on the factory floor could interpret easily.


The digital twin:  A machine learning-powered digital replica of a laboratory now takes care of employee scheduling to maximize efficiency. Output increased by 40% and  it also makes  work better and easier.

AR, another visualization tool, is helping significantly reduce the time it usually takes to change from producing one product to another, increasing the utilization of factory machines.  Not only was the production time reduced but employees no longer have to follow lengthy, complicated paper-based instructions.

 Digital transformation also requires lots of employee training. Internal experts on quality control, packaging and engineering need to be an integral part of the process and managers must learn to make decisions based on data rather than on prior experience only.



https://innovator.news/using-data-as-an-asset-9e3d6d3cbf0b

http://www.boussiasconferences.gr/files/_boussias_conferences_content/presentations/smart_factory/2019/oscar_lazaro_smartfactory_19.pdf

https://www.capgemini.com/research/digital-transformation-review-twelfth-edition/industry-leader-perspectives-saskia-steinacker-bayer/

http://www3.weforum.org/docs/WEF_4IR_Beacons_of_Technology_and_Innovation_in_Manufacturing_report_2019.pdf

Ud 14.9.2022,  5.10.2021

Pub 11.11.2019