In today's dynamic global landscape, the paper, packaging, chemicals, metals and building materials industries are forging ahead to embrace innovation and modernization. The SAP for Process Industries and Natural Resources Conference, in Vienna from June 18-20, is poised to shape the future direction of these critical sectors. As change accelerates, it's crucial for industry leaders, professionals, and enthusiasts to collaborate and map out a path for the future.

Discover limitless opportunities

Attendees will have access to a wealth of knowledge, expertise, and resources at the event. More than 30 compelling customer success stories will be shared by industry leaders such as Mondi, Menasha Packaging, UPM, CENIBRA, Billerud, Klabin, Etex, Henkel, LyondellBasell, RHI Magnesita, Mitsubishi Chemical and more. From keynotes and customer panels on AI, cloud and sustainability to interactive workshops and networking sessions, every aspect of the conference is tailored to equip participants with actionable insights and strategies for success.

Whether you're an experienced professional or new to the world of Process Industries and Natural Resources, this community gathering caters to all. Explore cutting-edge technologies and best practices, gaining deeper insights into how SAP solutions can revolutionise operations and drive sustainable growth in these dynamic sectors.

The topics due for discussion are essential to navigating today's complex challenges and opportunities in these industries. Ranging from sustainability and digital transformation to supply chain optimisation and regulatory compliance, shedding light on the most pressing issues shaping the future landscape.

Global Connections, Global Impact

Representatives from leading companies and organisations will converge in Vienna, offering attendees the opportunity to gain insights from a diverse and dynamic audience. Whether seeking inspiration, new partnerships, or expanding professional networks, the event provides a unique stage to connect with like-minded individuals passionate about driving innovation and excellence in these vital sectors.

Come meet with global thought leaders from Paper and Packaging

The two day conference features more than 40 customer speakers focused on real-world experiences, successes and learnings. Top paper and packaging companies speaking include: 

• Mondi: How to Successfully Drive Continuous Innovation with SAP
• Menasha: Innovating Together: Look Back on 18 Years of Successful Partnership
• UPM: Management of an Integrated S/4 System
• CENIBRA: Adopting Advanced Mobile Asset Management
• Billerud: Unifying Vision: CatalysingRadical Transformation
• Pfeifer Group: Implementation of SAP ERP and Digital Manufacturing in Wood Processing
• Klabin: SMART Project -Connecting Klabinwith the Future 

Secure your spot in Vienna

In summary the SAP Conference in Vienna is a pivotal opportunity for those invested in the future of Process Industries and Natural Resources. With its emphasis on innovation, collaboration, and future readiness, this meeting is not to be missed. Join us in Vienna, and together, let's shape the future of these industries. Find out more and make your plans now.

I often get asked if artificial intelligence (AI) can solve a particular problem. This cannot be answered without defining AI.

If we use a dictionary, we would observe that the term “artificial” means it is not a human making a decision or taking action. It is a machine, often in the form of digital logic of an algorithm, that is performing the action. If a human being is looking at the temperature in your office and has their hand on a switch that turns on the heater or cooling unit to maintain temperature at the desired setting, it is not artificial. Therefore, a thermostat is an artificial means of performing this function. In the 2^nd industrial era we had pneumatic control loops and electrical relay logic for interlocks, which replaced humans performing those functions. The 3rd industrial era moved these functions to the digital domain and they remained artificial.

Now comes the hard part. What does “intelligent” mean?

Proportional integral derivate (PID) control loops are prolific throughout industry. They are obviously artificial. Are they intelligent? Obviously they contain some degree of intelligence since they model a control loop as a linear 2^nd order differential equation, and the tuning represents some intelligence about the loop behavior. The nature of this intelligence is similar to a child that goes to school one day and learns the alphabet. The fact that the child can now recite all the letters in sequence shows they have new data in their memory. Therefore, the nature of this intelligence is the same for a PID, advanced control, or multivariable prediction control (MPC) application. There is imbedded static intelligence in an artificial manifestation.

This definition of intelligence can be unsatisfactory. I remember my first class at Miami University was advanced chemistry in a large lecture hall. When the professor took the stage, he told us he was not there to teach us chemistry. He said he was there to teach us how to think.

A human not only has the ability to absorb data. We have continuous sensory input and can adapt our models of reality to improve our decisions when conditions change. This definition of intelligence is adaptive. Machine Learning is the term we use to describe the ability of digital machines to adapt models to realtime data.  

If we accept that our definition of intelligence needs to include adaptation, then much of what is labeled as AI isn’t. To truly represent artificial human intelligence, AI needs to think and adapt like a human. By this metric, AI is really in its infancy. Machine Learning needs to be applied cautiously to be reliable. However, a brave new world is within sight.

My Grandmother Thompson was born before Standard Time Zones were implemented (she was born in 1882, time zones came into use in 1883). She died thirteen years after humans landed on the Moon (1969 vs. her death in 1982 when she was 100 years and ten days old).

I am beginning to think I live in a parallel universe when it comes to lawnmowers. My dad started me out with a reel type manual push mower when I was so small I couldn't reach the handles, which he gladly modified to make them work for me.

Now, I just bought my second generation robotic mower. The first generation robotic mower required a boundary wire and essentially cut in a random path inside the wire. Programming was fairly simple. I used it for five years.

I was enticed this past winter by the idea of a robotic mower without a boundary wire. They call people like me an "early adopter!" The new mower arrives. The complexity of the computer control is probably 100x that of the first generation version. It has a satellite receiver that pulls down signals from 25 satellites and transmits the information via radio to the robotic mower. The mower also pulls down satellite signals. It has three visual cameras to keep it in the space where it is supposed to work. It has three infrared eyes as well to help it stay on task. It has a rain detector.

Programming it is another challenge. I have hired the young man next door, a rising junior in computer science at Georgia Tech, to help me get it properly programmed. He has not succeeded yet.

This is the experience a lot of us have with advanced computer machine learning these days. The first generation stuff, years ago, was pretty simple, not so much today. This is why in industry we need professionals such as SAP to help guide the way.

See you in Vienna next month!

Computer vision is crucial in cybersecurity for enhancing threat detection through pattern recognition and anomaly identification. Its ability to quickly and accurately analyze visual data empowers security systems to identify potential threats—like unusual user behavior or malicious software—that could compromise networks and sensitive information.

Modems used in many industrial Internet of Things (IoT) devices can easily be hacked, allowing threat actors root access, remotely and without authentication. The result could be highly disruptive, as many industries rely on IoT devices and other internet-connected sensors for proper operations of entire facilities.

For the past two decades the manufacturing world has been hearing about Internet of Things (IoT) devices. These devices are designed to not just collect operations data as their predecessors did, but also connect and communicate with a broader array of networked devices to help provide a holistic—or at least near holistic—view of plant operations.

The UK has become the first country to legally mandate cybersecurity standards for IoT devices. The new laws, which came into force today, aim to shield consumers from cyber threats and boost the nation’s resilience against rising cyber-crime.