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Posts Tagged ‘Digitalisation’

Follow us to the year 2040…

It’s harvesting time. After delivering the wheat to the silo, the harvesting machine delivers the straw to the plant that has been temporarily placed next to the farm. After biotechnical and chemical processing, the bio-based plastic granulate is filled and ready for shipment; over the next couple of days, it will be sold via regional shops to the consumers who use it as feed for their 3D printers at home and produce their own goods as required.

Meanwhile, at the industrial site close by, the chemical plant has switched from producing ingredients for the sun-tan lotion to synthesizing anti-freeze agents. Decoupling one module and replacing the downstream processing unit has been a matter of hours. The central software has calculated the required formulations and production parameters, and the individual components have already started to fine-tune their settings in bilateral communications.

F3 Factory Container_kleinVision, forecast or mumbo jumbo? As far-fetched as the scenario may seem, the technological foundations are being laid today: Modularisation and automation are not only taking the process industry to new levels of efficiency, but they will fundamentally change the business models of the chemical and pharmaceutical industry.

The key to the future lies in the combination of automation and modularization. Experts envision different ways on how these two developments interact: Herman Bottenberg, Zeton, is convinced that “for true flexible manufacturing for multi purpose products and when applying the modular approach both hardware and automation has to become 100% modular!” Axel Haller, ABB, says: “Modular and system independent automation is possible. The market will decide if this will be the next step into the future”.

At first sight, the performance improvements that are enabled within existing processes seem more evolutionary than revolutionary. Marc Richter, Renishaw points out the quality improvements by new techniques and the speed-up development cycles of pharmaceuticals. And Marin Valek, GE, adds: “Companies use less than 10% of the information available to be better in operations. Winners will use IIoT technology and data science to get the competitive advantage of having high predictable performance.”

The technological progress opens up two different pathways: One leads from today’s batch-based production to continuous flows. This is more than a change in process – it calls for a different conceptual approach. Alessandra Vizza, Corning: “Mindset change is required to understand that continuous flow processes are no more a new system to test but the tool to be used for cost reduction; safety; environmental impact and innovation. An appropriate solution to fine-tune chemical production needs with world behaviour and epoch constraints.”

On the other hand, modular plants offer high flexibility and the opportunity for customized or even personalized products in small volumes. This entails a fundamental change in business models. Says Mario Bott, Fraunhofer IPA: “Monolith organizational approaches in process industries will struggle to manage the challenges of mass personalization.” Yet, the chances of the necessary transformation are often underestimated.  Mark Talford, BRITEST, says that “much has been done to develop practical modular continuous production technologies, but there is still a challenge to convince decision-makers to invest. As well as new business models, we need tools and guidance to help decision-makers overcome their perceived fears.” The adaptation will certainly be worth it. Dirk Kirschneck, Microinnova, summarizes the opportunities a successful transformation offers: “Industry 4.0 delivers the bridge between the production flexibility and knowledge-based process performance. Industry 4.0 will transform the chemical industry and will lead to a new efficiency level in terms of speed, quality and resources. Radical new business models will push the chemical industry to a new performance level.”

And what is your opinion? Give us your view and discuss with the expert’s quotes and many others at the PRAXISforum “Future of Chemical and Pharmaceutical Production”…

PF Future Production 2017

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„More than 50% of the companies are not willing to invest in Big Data Applications. These companies will go bankrupt over the next 10 years“. A provoking statement made by Thomas Froese from atlan-tec, a software developing company specializing on process optimization and data mining. And yet, there are many who share his view: Huub Rutten,Sopheon, points in the same direction when he says that „companies that think Big Data Analytics is something for their marketing department, and not relevant to all other functions, will not have a long life anymore.“

The awareness in the process industry is there: According to Accenture’s Digitals Chemicals Survey in 2014, 79% of chemical industry executive expected digital to make the greatest impact over the next five years through improved productivity. On the other hand, only 58% were embracing digital to gain a competitive advantage over industry peers. Taking the expert statements on competitiveness into account, there seems to exist a potentially dangerous gap – big data is introduced, but it might in some cases be too little, too late.

Predictive Big Data Analytics and Machine Learning will transform most industries by supporting better informed and more customized decisions by both, humans and machines, increasing agility and efficiency, lowering costs, enabling better and more customized products and services, forecasting risks and opportunities, and increasing automation. Early adopters will gain significant competitive advantages, while others are likely to be left behind.

Ralf Klinkenberg, RapidMiner

Big Data analytics has become more and more important to the process industries. Sure, the process industry has always collected data to supervise production processes, to identify disturbances, and to ensure product quality, and this will continue.

The application of data analytics will improve efficiency in the chemical industry!

Matthias Hartman, ThyssenKrupp System Engineering

But with the tremendous increase in data storage and processing capacities, new algorithms have become accessible. They open up new market opportunities, enabling process advantages and cost reductions within the production, decreasing time to market and, ultimately, making new customized and individualized products accessible. The application areas in which data analytics can be used profitably are diverse and in process industries nowhere near exhausted.

In the process industry, digital technology provides actionable solutions to challenges and groundbreaking opportunities for innovation.

Matthias Feuerstein, Microsoft

Provided the data is collected, analyzed and used intelligently and efficiently, as Benjamin Klöpper, ABB Research Center, points out:The major challenge for Big Data Analytics in Process Industries are not scalable architectures or clever algorithms, but remains to have the right data in the right quality to address relevant and pressing issues. Today’s information system infrastructure often prevent us often from obtaining this right data in an efficient data.“ Adds Nico Zobel, Fraunhofer IFF: „One of the major challenges will be to generate use cases of the analysis of data from heterogeneous sources.” And the sources in the chemical industry are nearly endless.

Chemical space is big. Very big. Published and unpublished data only cover only an exceedingly small part of possible small molecule space. Machine learning and algorithmic prediction tools can help fill in the explored parts of chemical space. What kinds of data sources and prediction tools will come next?

David Flanagan,  Wiley ChemPlanner

Jens Kamionka, T-Systems Multimedia Solutions, widens the scope by taking security issues into account – a major challenge in times of increasing cyberattacks: „Many companies still fail to address security, infrastructure or data quality issues.” Concepts that allow one the one hand the company-wide or even inter-company integration of data streams along value chains, at the same time preventing data leaks and cyberattacks, are the intensely sought after.

And once these questions are solved – are we looking at a future with fully automized, smart plants that anticipate customers’ wishes before they are even aware of them? No, according to the experts. Human intelligence will always have its place. „Big Data opens up many opportunities in different areas of a chemical company. Besides toolsets and technology, mind-set and communication skills are additional success factors for these novel approaches”, says Sindy Thomas, Clarian. And Drazen Nikolic from Ernst & Young sums it up:““If you do not understand the problem, you are not able to frame the right question. “

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Meet these and other experts and discuss what Big Data analytics might mean for your business at the DECHEMA-PRAXISforum “Big Data Analytics in Process Industry”, 1-2 February 2017, Frankfurt. For the full program and registration, click here DECHEMA-PRAXISforum Big Data Analytics in Process Industry

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