Severe drought conditions in Europe threaten to make the Rhine river too shallow for commercial barges, jeopardizing shipments of millions of tons of raw materials that travel up and down this 800-mile long transportation waterway from Switzerland to the North Sea. The Rhine is among the latest supply chains threatened by the climate economy where extreme weather events – wildfires, droughts, floods – can cause billions in economic losses. Waterway traffic disruptions are worrying because barges are a more cost-effective and therefore preferred mode of transportation for carrying bulk commodities like timber, grain or chemicals, potentially choking off supply chains much closer to the source. However, connected data tips the advantage to everyone trying to balance supply and demand amidst growing weather uncertainties.

“Whether shipping goods by barge, railway, truck, airplane, or ocean liner, transporting goods is a 24/7 operation, requiring orchestration between multiple entities,” said Kevin Schock, global vice president of travel and transportation industries at SAP. “This is the purpose behind SAP Logistics Business Network, which helps bridge demand and supply sides by connecting data between all partners so they can better anticipate disruptions and plan alternatives to preserve profits and meet delivery promises.”

How data can fix broken climate models

Speaking during a recent Climate 21 podcast, Josh Gilbert, co-founder and CEO at Sust Global, also described how companies can mitigate supply chain risks with actionable data. His company collects and analyzes climate data from satellites, ground-based sensors, academic institutions, and other sources, helping everyone including financial investors and chief risk officers, as well as supply chain and product managers, spot hidden risks and act quickly.

“We want to transform the complexity of climate science into business intelligence,” said Gilbert. “It could be the probabilistic risk of wildfire in the future at a supply chain facility, flooding to a manufacturing site, a sea level rise next to a port, or greenhouse gas emissions output from specific assets. We can integrate data every two weeks into the models, making it more relevant and granular to the business. Nobody wants another dashboard or to know what’s going to happen in the year 2100. Companies need to know where to build in secondary points of failure into their supply chains near term. They need better data integrated into the company’s operational workflows.”

Digitalization yields business intelligence

Digitalization can help transportation organizations like barge operators plan and replan in the face of droughts and other unplanned events that could delay shipments. Data analytics can reveal options and cascading ramifications along the supply chain. This is especially valuable for barges laden with commodities slated to meet delivery timetables for just-in-time manufacturing.

“With bulk commodities, recipients in process-centric manufacturing like grains or chemicals may not be able to accommodate early deliveries, and could suffer consequences if shipments are late, forcing costly shut-downs resulting in shipment delays to their customers,” said Schock. “Before the worst happens, companies can build data models to explore scenarios for rerouting shipments or using different transportation modes. For example, with SAP Integrated Business Planning and Transportation Management organizations can calculate the financial impact of various simulations, such as reducing barge loads in synch with lowered water levels on the Rhine. Do I need to double the volume of shipment runs, and does the Rhine have the traffic capacity for that? Will I need more crews, and how does that change delivery times?”

Business value in trusted data

Transportation providers aren’t the only sectors parsing climate data for supply chain resilience. Following pandemic-related supply chain disruptions, Gilbert said that early adopters in banking, finance, and insurance are exploring how updated climate-related information can help gauge sustainability risk as climate change impacts grow.

“There’s a lot of excitement around becoming more climate aware and a lot of net-zero promises, but we haven’t yet seen the full conversion into real action…digging down into the data to understand where, why, and how these climate events actually manifest,” he said. “Sust Global can give a risk exposure score for any asset, anywhere on earth, in a very granular way…Integrating our climate data with existing software applications and other information, incredibly smart people on data science teams can create new insights to help the business end-user better understand actual risks.”

On the heels of last year’s partial shut-downs of the River Rhine due to torrential rains, supply chain experts are making data actionable to blunt the impact of the next challenge that’s sure to come in the climate economy. As for this latest drought, digital innovations can’t come soon enough for barge operators and the commodity manufacturers waiting for shipments at the other end of the run.

If you are interested to discuss these topics and more with colleagues from around the globe – consider coming to the 2022 International SAP Conference for Forest Products, Paper and Packaging in Madrid, Spain (27-29 September). Head over to the event website today to view our international speaker line-up in more detail.

There was a time when driving a car meant you needed to know how a car worked. If something went wrong, you needed to figure it out and fix it. You needed to be able to detect conditions and understand what they meant.

By the time I was born, cars had a dashboard full of gauges. You could see the vehicle speed, engine speed, oil pressure, engine temperature, and numerous other indicators. By monitoring these gauges, a driver could determine if something was wrong and perhaps fix it.

Last week I had a Lyft drive in a Tesla. The only dashboard component was a flat computer screen. With this screen, the driver could navigate as well as get any diagnostic information from the car. If something was wrong, a notification would appear on the screen.

This evolution in cars mirrors that that we have seen in industry. There was a time when we had to walk around and put our hands on equipment to know if something was wrong. Then we had instrumentation that gave us the information we needed to monitor. Today we have computer displays showing everything we need to know from the comfort of a control room or a remote office.

Our computer displays of the process are called Human Machine Interface (HMI). Another common acronym is User Interface (UI). 

Our first industrial HMIs were obviously more rudimentary than today. They commonly consisted of a panel connected to an individual PLC or a mainframe host driving several displays. The displays were monochrome and data intensive. Any graphical capabilities were primitive.

As control systems evolved, fancy graphics became possible in an HMI. It was common to see very colorful displays with process renderings of equipment and piping, as well as trends and graphs. The HMIs were networked with the processing distributed, so that each HMI was a computer with its own processor and memory. This eliminated a single point of failure.

This was indeed an improvement, but over time some drawbacks were observed. First, the distributed processing meant that each HMI computer needed to be individually maintained. Any time new software or configuration was required, it required maintenance on every single HMI computer. This can be tedious, inefficient, and error prone. The other issue was the fatigue experienced by operators subjected to a kaleidoscope view of colors and objects on multiple HMIs. This approach to HMI overwhelmed the user with sensory inputs that may be distracting, misleading, and confusing.

Todays’ modern HMI has now evolved to systems that can be much more easily maintained and effectively used.

The ISA 101 standard is now widely adopted throughout industry for HMI design. Gone are overwhelming colors, and in come grayscale displays that only show color when there is something abnormal for the operator to notice. Commonly, the colors refer to alarm conditions. The ISA 18.2 standard addresses proper alarm management so that operators are not overwhelmed and can focus on the most critical alarm conditions. These standards have gone a long way toward operating industrial processes more effectively.

For maintenance, the system design has in some ways gone backwards. Instead of having each HMI with its own processor and memory, industry has widely adopted thin clients. This allows low-cost displays to be deployed that individually require little to no maintenance. The processing occurs in a server that can centrally manage displays. Software upgrades and configuration can easily be performed at the server without having to do anything at the thin client. If a thin client has a hardware failure, it can be replaced with another thin client at low cost and with little effort. It seems a bit odd that the old idea of a mainframe driving every HMI seems to be the new standard, but in this case the processing at the field level is distributed while it is only the HMI that is being centralized. Redundant servers address the reliability of a thin client system.

Another maintenance enhancement is the use of virtual machines. This prevents a software application being held hostage by an antiquated piece of hardware and operating system. A virtual machine has all the attributes of an actual computer and operating system other than a hardware dependency. The machine runs in a virtual environment on an actual piece of hardware. The advantage is that when that hardware needs to be replaced, the virtual machine is just moved and redeployed to the new hardware. It is also very helpful for system redundancy, in which a virtual machine can be automatically switched over to another piece of hardware when there is a failure.

One aspect of HMI that seems to have gone backwards is the concept of a single window. When I began in industry, there was a clear separation between a Distributed Control System (DCS) and a Quality Control System (QCS). This meant that an operator used the DCS HMI for everything in the mill except for the final quality measurement and control. The operator had to view and interact with the QCS HMI to ensure the basis weight, moisture, and other quality measurements were on target in the machine direction and cross direction. The DCS and QCS displays looked, operated, and behaved differently, so the operator had to be trained on each one. There was a demand in the paper industry to have the DCS be the single window to the process. I was very involved in the development of this, and we had several mills adopt this single window. This allowed the operator to do everything from the DCS HMI. Today, it appears most mills have independent DCS and QCS systems again.

A consideration in today’s HMI is whether we have lost connection with the process. In the days of walking around and putting our hands on equipment and piping, we may have had a better understanding of how to fix what is wrong. Like the cars we drive today that we typically do not have the skill or tools to maintain on our own, processes have become more remote. However, in many ways we know much more about our processes than ever before. A modern HMI can provide much more insight about the process, not only on specific equipment or unit operations but on the entire operation. It can be argued that we are much more connected today because we have insight that could not be detected through manual inspection.

In the Industry 4.0 era we can become enraptured with technology and esoteric concepts. However, the way we view and interact with the process cannot be overlooked. The HMI is our eyes on the process.

This is as much of a rant as anything else for I have no solution, just a crying need.

I subscribe to one of these password savers, which I hope is secure.  I also have spreadsheets of passwords going back and then there are word docs of passwords that I am afraid to discard on the outside chance that there might be an obscure one that I will need someday.

Then there are the protocols that require me to change passwords every few weeks or months...

Security is a problem in need of a serious, simple and foolproof solution.

Even though LTE 450 networks have been available in many countries for years, interest has been reignited as the industry moves into the LTE and 5G era. 2G retirement and the arrival of narrowband IoT (NB-IoT) are some markets that are also driving the uptake of LTE 450.

A new report published today reveals the current state of IT & OT convergence among manufacturing organisations.

Information Technology (IT) and Operational Technology (OT) are two fundamental areas of manufacturing. Yet, traditionally, they haven’t always functioned as a unified entity. As a result, a gap often existed between the enterprise and the shop floor.

Midsize industrial manufacturing companies have always focused on running highly efficient operations while keeping costs as low as possible. But given current economic and industry conditions, many are beginning to see their traditional Industry 4.0 investments in a new and more strategic light.

C-suite leaders have high expectations of data. They want to be able to whip out their smartphones and bring up beautiful visualizations of trends that give them actionable insights into the business at a granular level.