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2BM Software takes industry maintenance into a new age

Supported by EU funding, 2BM Software has developed a new SAP-based Predictive Maintenance solution that will help companies globally to optimise maintenance as much as possible, benefiting the bottom line as well as the environment. The solution is currently undergoing testing at a german multinational manufacturing company.

Production companies that utilise the full technological potential of Industry 4.0, gain a significant competitive advantage and help support the UN sustainable development goals. One of the ways they succeed in this is by optimising their ongoing maintenance, benefitting the bottom line and the environment.

They are able to do this thanks to a new type of software, which combines and utilises the possibilities created by the Internet of Things (IoT), Artificial Intelligence (AI) and intelligent ERP systems like SAP, leading the way for Predictive Maintenance.

IT investors have trained their focus on the need for new solutions for Predictive Maintenance, and in Europe, the Innovation Fund has chosen to invest EU funding in a solution developed by 2BM Software that is currently being implemented.

2BM Software is an independent subsidiary and owned by 2BM, one of Denmark’s largest SAP consultancy companies and SAP platinum partner. 2BM Software has developed a new application, Mobile Predictive Maintenance for their existing suite of software solutions (Mobile Work Order suite), designed for maintenance and service companies that use SAP PM (which 90% of the biggest production companies in the world use). Among other things, the MOBILE WORK ORDER suite applications help maintenance personnel and/or employees gain an overview and insight into maintenance tasks for the production plant via their smartphones as they move around the machinery and production lines.

 

Helped by computer power and AI

“We are proud of the recognition and investment from the EU (Editor’s note: Eurostars). Mobile Predictive Maintenance is a natural further development of our product portfolio, which started with digitalisation, so that maintenance personnel no longer needed to use paper. Now we are taking maintenance to the next level. There is now less need for the maintenance employee to be physically present at the machines, when all of the relevant data can be transferred automatically from IoT devices. Now, computer power and AI helps the employee and the company by providing an overview of the need for maintenance for all of the vital machines in real-time,” said Martin Pock, CEO at 2BM Software. “We are also thankful that we choose IBM as the data science and Machine learning platform as a vital part of the solution as they have continuously being named as MAGIC QUADRANDT leaders by GARTNER (https://www.ibm.com/blogs/journey-to-ai/2021/03/ibm-is-named-a-leader-2021-magic-quadrant-for-data-science-and-machine-learning-platforms/)

 

Using the Machine Learning models, it was possible to predict the machine stop in the steam dryers at Nordic Sugar with an accuracy of 84.4 percent.

Explosive market growth

Predictive Maintenance prevents expensive production downtime and increases production uptime. It also extends the lifetime of the production equipment by analysing data that the equipment generates via different sensors and meters. The collected data results in a better decision basis for when maintenance of the industrial equipment needs to be carried out based on the state of the equipment.

According to the market research and advisory company Allied Market Research, the global market for Predictive Maintenance will explode in the coming years. From USD 2.8 billion in 2018, the market is predicted to grow to USD 23 billion in 2026.

 

Optimising at Nordic Sugar

As part of Mobile Predictive Maintenance’s development, the product is currently undergoing testing at the German multinational company Nordic Sugar, which is part of Nordzucker.

“With help from 2BM Software, we will find out how we can use all of the data that we have collected in recent years, which will be the basis for becoming more intelligent and smarter when it comes to our maintenance, so that instead of changing parts based on fixed schedules we can now change parts when it is relevant. If we do not take this step and do not start to utilise the technological potential of Industry 4.0, we will just face further competition from others in the market who did not hesitate to do it,” said Christian Jørgensen Storm, Regional Manager Investment and Maintenance, Nordic Sugar A/S.

 

Nordic Sugar in Nakskov forms the framework for the test process with the Mobile Predictive Maintenance model.

Prevent expensive downtime

Nordic Sugar’s focus includes the sluice part of the company’s steam dryers, which are some of the company’s most expensive and most crucial plant equipment that can lead to downtime.

By training the software to see the correlation in the data from temperature, vibrations, nitrite levels, etc., in the sugar beet and the amount of soil on the sugar beet, the aim is to optimise maintenance and the prevention of downtime due to the steam dryers’ sluice.

“The objective is to gain ongoing improvement in the performance of the machinery by becoming better at predicting when it risks breaking down, so we avoid downtime and in general improve the machinery’s OEE (Overall Equipment Efficiency). And in this way, we can plan a production stop at a time when it will have the fewest negative consequences for our production,” said Anders Jørgensen-Juul, Head of Projects, Nordic Sugar, Nakskov.

 

Supports one of the UN’s Sustainable Development Goals

Predictive Maintenance supports the UN’s Sustainable Development Goal Number 9: Build resilient infrastructure, promote sustainable industrialization and foster innovation.

“Basically, Sustainable Development Goal Number 9 is about getting society to operate in a smarter way. It’s not just about the roads, railway lines and ports that allow us to trade with the rest of the world. It’s also about finding new methods for working in a more sustainable way in factories and companies around the world, so we use resources more efficiently and in a more environmentally compatible way,” said Martin Pock from 2BM Software.

Industry has always required that its maintenance processes are financially efficient. But the climate crisis is forcing companies all over the world to incorporate sustainability into their processes.

“There is a market requirement and historic basis for companies asking for better and less expensive maintenance. And there is a new general understanding around the world that the UN’s Sustainable Development Goals, which Predictive Maintenance supports, are important for all of us.”

Facts

Results

A total of five Machine Learning models were developed for the project: One developed by 2BM Software in collaboration with IBM, and four developed solely by 2BM Software. Each used a different mathematical model, and were used to decide which best met Nordzucker’s requirements.

Using the Machine Learning models, the company succeeded in predicting machine stoppage in the steam dryers at Nordzucker, and with a precision of 84.4 % using the Machine Learning model that 2BM Software developed in collaboration with IBM.

Using the recently acquired data and information relating to machine stoppages, the model and the solution was further improved and “trained”, which means Nordzucker can achieve an even greater precision in the future when it comes to predicting downtime.

The result is a solution that has been added to the 2BM Mobile Work Order suite and will be used to deliver Mobile Predictive Maintenance for the satisfaction and benefit of even more customers who use SAP Plant Maintenance and SAP Customer Service.

 

2BM Mobile Work Order SUITE

2BM Mobile Work Order suite is a mobile and user-friendly cloud-based solution that consists of a mobile app, a dashboard, digital checklists and an IoT module. It is built for mobile-friendly and user-friendly interaction with SAP PM/CS and is perfect for businesses involved in production-friendly maintenance and service. Using the 2BM Mobile Work Order suite, service technicians have the tools for any challenge, whether it’s getting rid of pen and paper or using IoT and AI data-assisted decisions.

Learn more at www.2bmsoftware.com

 

Nordic Sugar

Nordic Sugar is part of Nordzucker, a world leading sugar company. The production is based on natural ingredients, primarily sugar beet, which is grown locally. The sugar beet is also used to produce bioethanol and high-energy animal feed. Sustainability throughout the whole value chain has the highest priority. Nordzucker has 3,800 employees who are based in 21 sugar factories and refineries in Europe and Australia, ensuring service and products of the highest quality – and the foundation for continued growth. Nordic Sugar has one office and four factories in Denmark and employs 450 people.

Learn more at www.nordzucker.com

 

Want to know more about Mobile Predictive Maintenance by 2BM Software

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