Volume 3 Issue 11 November 2021
In this Issue
Welcome to Industree 4.0 for November 2021, exclusively sponsored by SAP.

By Alfred Becker, Head of Mill Products Industries Business Unit, SAP
The Power of Industry 4.0 to enhance Paper Manufacturing Processes
Digitization Delivers for Manufacturers

We recently worked with the MPI group to examine the extent to which manufacturers are leveraging Industry 4.0 across their organizations. This summary specifically looks at how manufacturers (including paper companies) have applied digital technologies to improve plants, processes, and production performances (e.g., quality, on-time delivery, inventory turns, manufacturing costs). It also explores the opportunities and challenges manufacturers encounter when applying digital technologies to plants and processes. Since the Industry 4.0 Study was initially fielded more than five years ago, manufacturers have dramatically increased the pace at which they use Industry 4.0 technologies to enhance their operations. They’ve recognized that it’s not a question of if they should digitize their production, but when: digital laggards are falling behind digital leaders, and the gap is widening. This summary also highlights how self-described digital Leaders manage operations and perform vs. other companies.

Industry 4.0 Is a Foundation for Manufacturing

A majority of manufacturers (58%) have a strategy in place and implemented for applying Industry 4.0 technologies to processes, and 45% (average) of their production processes and equipment incorporate smart devices and/or embedded intelligence.

Among the 32% of executives who described their company’s Industry 4.0 capabilities as “Leaders,” 78% have a strategy implemented for Industry 4.0 technologies vs. just 56% of companies described as “competitive” and 22% of those described as “industry catchup/no Industry 4.0.” Digital Leaders also are more likely to report higher percentages of production equipment and processes that incorporate smart devices and/or embedded intelligence.

The papermaking industry is not famous for change, because often it is held back by the scale and capital investment required to adopt new technology. Progress has come slowly and incrementally, in cycles of planning, investment and build. But we see that industry 4.0 is accelerating the rate of change and implementation of digital solutions in the paper industry has rocketed from just 6% to 32% in 5 years (Source: 1StepChange).

The manufacturing activities most likely to incorporate at least some application of smart devices and/or embedded intelligence are manufacturing (78%), shipping/logistics/ transportation (75%), maintenance (74%), and document management (75%). Most of those areas represent key steps in the paper value chain. A higher percentage of Leaders report significant application for these activities. Industry 4.0 enables the delivery of critical information in real time. 

A good example is Koehler Paper Group, a mid-sized producer of thermo-papers based in Germany. They to do predictive (production) quality in their mills. In correlating sensor data in real-time combined with enterprise data, they learned so much about their processes, that they can predict product quality parameters and they can correct production processes before issues occur. In this way they can stay within the allowed quality interval and less rework or scrapping will be required. Koehler says this approach paid off instantly.
More than half of manufacturers invested more than 5% of sales in implementing an Industry 4.0 strategy in their plants, processes, and supply chains in the past year. Some 74% of digital Leaders invested more than 5% of sales vs. 55% of competitive and 32% of catchup companies.

Impact from Industry 4.0 to Manufacturing Performance

The vast majority of manufacturers report that the application of smart devices and/or intelligent devices has improved production-related activities. Digital Leaders are far more likely to report “significant improvement” for these activities. Not surprisingly, these improvements also lead to better production performances.

And it doesn’t necessarily require huge budget for achieve significant advances. Family-owned Steinbeis Papier supplies magazine, office, and digital printing paper, made from locally sourced recycled paper. The company is exploring use of advanced analytics and artificial intelligence (AI) to analyze their data in real time for automated production monitoring and value chain optimization.

Being a relatively small paper company with limited IT resources, Steinbeis had to find a way to manage onboarding tens of thousands of sensors to their data model. Their approach is a good example of a company beginning to “industrialize” the application of technology. Steinbeis worked with a partner that provided a kind of web crawler to analyze their internal network for sensor data streams. This helped them to automate much of the onboarding process. Today, every second more than 25,000 sensors on the production lines deliver data, which is then analyzed in conjunction with data from the MES and SAP ERP systems in near real time. They check for inconsistencies in product quality, identify malfunctions easily, or simply benchmark equipment or production runs.

Deployment of Industry 4.0 in plants has increased productivity and profitability for nearly all manufacturers, with many reporting sizable increases: 66% report increased productivity of more than 5% over the past year, and 63% report increased profitability of more than 5% over the past year. Increases are even more pronounced among digital Leaders. A vast majority of manufacturers expect productivity and profitability improvements to increase over the next five years.

Industry 4.0 Manufacturing Challenges

The application of Industry 4.0 to production has not been without some difficulties: many manufacturers report that Industry 4.0 initiatives have not achieved all their objectives or sometimes have unforeseen challenges.

One example came from both a metal and paper producer – that had remarkable similar processes in their approach to using sensors to monitor and control quality. Both have sensors set up at very frequent intervals along the metals and paper rolling production lines – approximately every 10 cm – but both are only taking measurements every 100 cm. Despite their desire to track even more measurements, their infrastructure for sending, processing (in real time) and storing the data would not be able to cope with this amount of data – or would simply become unrealistically expensive.

Industry 4.0 Takeaways

Manufacturers are already reaping rewards from their investment in Industry 4.0 technologies. But the MPI Industry 4.0 Study finds that many aren’t taking full advantage of digital tools to improve operations. Given the range of opportunities to improve processes, productivity, profitability, and other performances via Industry 4.0, nearly all manufacturers should aggressively invest in their development by:

  Identifying the targets for application of Industry 4.0 technologies based on opportunities to improve critical operations measures (e.g., safety, quality, environmental).
    Applying smart devices to deliver real-time data to plant managers and executives to improve scheduling, asset management, workforce productivity, etc.
     Digitizing processes to facilitate widespread information sharing (with suppliers and customers) and to establish automated, proactive decision-making on the plant floor.
By Pat Dixon, PE, PMP

Vice President of Automation, Pulmac Systems International (pulmac.com)

Once upon a time, industry was operated manually. Along came analog to digital converters, and the age of Industry 3.0 automation was born.

Like the origins of Rome with Romulus and Remus, there was not a single baby birthed. There were 2 distinct babies brought into Industry 3.0. One of these babies grew up in our world of continuous processes, such as paper mills, chemical processing, and utilities. The other baby grew up in the discrete world of factories like automotive plants. These babies had very different personalities.

In the continuous world, the child needed to connect many sensors and valves into a comprehensive system that could monitor and control them. The early generation of children had a single mainframe host computer performing all the processing and data storage. Because such an approach did not scale well and posed a single point of failure, later generations evolved to system where this processing was distributed to field data acquisition and control devices, with a control network connecting them to HMI, historical data storage, supervisory processing, and other such functions. The name for this generation was Distributed Control System (DCS).

In the discrete world, the child had to connect to motors and limit switches on a piece of equipment to perform high speed operations. This child was known as the Programmable Logic Controller (PLC). It featured a programming language called Ladder Logic that was intuitive for electrical engineers accustomed to looking at single line drawings. The engineer could connect to the PLC with a terminal for programming and monitor in runtime to see which contacts are preventing the energization of a coil. Eventually a more intuitive user interface was desired, so a market grew for Human Machine Interface (HMI) software. This allowed process graphics to be developed on commercially available desktop computers and connect to addresses in the PLC. The market grew to the point where it was desired to build control systems that connected PLCs and HMIs together to handle larger processes. These systems were called Supervisory Control And Data Acquisition (SCADA).

These 2 children were very different but had a lot in common. Principally, they were both doing essentially the same thing, but because they were separated at birth they really had completely different personalities.   

When children with different personalities meet, there can be clashes. Since PLCs were very fast and well suited to motor control, the continuous world began using them in motor control centers. SCADA systems were lower cost than DCS, in part because they were assembled with combinations of PLCs with HMI and other applications from various vendors running on commodity computers and operating systems. What SCADA systems lacked was a Unified Name Space. When an address for a limit switch was configured in a PLC, only the PLC knew that it existed. In order for an HMI to display it, an interface had to be created to connect the object on the HMI to the address in the PLC. In the DCS, as soon as a sensor is configured in the field device the whole system knows about it; the HMI, the alarm system, data historian, and supervisory processing. Therefore, merging DCS and SCADA could be a nightmare of data communication gateways and custom drivers. Trying to maintain systems with such a variety of tools from different vendors presented big problems.

While the DCS had the benefit of a Unified Name Space, it required a large investment in a single vendor. Once that investment is made, there were limits on the flexibility to customize the system to the scale or requirements of the process. When you buy a DCS, you are buying a system.

When you buy SCADA, you are not buying a system. You are buying components that someone has to integrate into a system. This gives you more flexibility and lower capital cost, but higher design and engineering cost.

The way these systems are marketed are very different. For a DCS, the vendors carefully control who can access training, documentation, and support because they have a service business as part of their offering. SCADA vendors are wide open; they put their products, training, and support on the shelf for anyone to buy. Therefore, the System Integration business is nearly entirely focused on SCADA.

Unfortunately, the terms DCS and SCADA often get applied incorrectly. I have worked on SCADA systems that everyone at the facility, as well as the vendor, called a DCS. There are many in the industry that assume SCADA only applies to the HMI application. Therefore, it is common for people to misunderstand the differences between the 2.

Today’s generation have made the differences between SCADA and DCS much more subtle. The cross breeding of these systems has made the DCS much more open and flexible, and SCADA systems have come closer to a Unified Name Space. It is likely that the future will eliminate such distinctions.

As we mature in Industry 4.0, we will see the birth of control systems that can be more easily connected and offer the same attributes of both DCS and SCADA. That baby will need a new acronym.

Antique Control Ancestry
I really enjoyed Pat Dixon's article this month (above). It brought back many memories and leaves us with a cautionary warning.

When I started in industry, way back in 1970, PLCs were a dream of the future. Where I worked, I was taught to design ladder diagrams for the machines we built (industrial washing machines for products such as the then new two piece aluminum beverage can). I learned this even though I was a mechanical engineering co-op student.

When PLCs came along, about 1972 or 3, it made sense to bring the nomenclature of ladder diagrams along with it. This made for an easy transition for discrete component electrical system control designers such as me.

I was jolted the other day when talking to a client about the transition from one paper machine to another in their facility. They were talking about the obsolete Fisher ProVox system on their old machine. Hey, wait a minute! I installed one of those in 1984 when they were on the bleeding edge of the latest in control systems! Of course, that was nearly forty years ago, a millennia in the world of process control.

I am all for technological progress. Where I see the challenges is this. How do we break the legacy habits and move the human interface to a level that keeps pace with the progress?

Ladder diagrams are still being used, for instance. But you would have to be as old as me to understand the legacy of their origin. Back in the day, you could go to a control cabinet and see the wiring and discrete components laid out just like you had drawn them (by hand) on the electrical diagram.

Today, they are as obsolete as the QWERTY keyboard (a relic we still use).

There are other philosophies and protocols in the DCS and SCADA worlds that suffer from the same legacy conditions. The challenge is how to shed these methods and move to thinking in today's world of advanced electronics and programming demanded by Industry 4.0.
IOT in Logistics: Edge vs. Cloud Computing Analytics
By Crystal Bedell
The Internet of Things is giving the trucking and logistics industry the visibility it needs to improve efficiency and safety. However, like any technology, IoT deployment decisions must be driven by a cost-benefit analysis. That includes the decision of which analytics types should be at the edge or in the cloud.
Impact of the Metaverse on Manufacturing
By Roshan Srinivasan
Ernest Cline’s Ready Player One provides an apt conceptualization of the metaverse where any individual can create and participate in virtual experiences. In the novel, a near-future world grapples with an energy crisis and global warming. So the novel’s version of the metaverse known as the OASIS provides virtual games, experiences, and economy. In many ways, the metaverse acts as its unique society.
What the Infrastructure Bill Means for IoT
By Dan Jones, EE Times
The $1.2 trillion U.S. infrastructure bill recently signed into law is among the most consequential pieces of legislation in decades. The landmark legislation will shape spending on broadband, energy, transportation, water and more for years to come.
6 IoT adoption trends for 2022
IOT Business News
IoT Analytics, a leading provider of market insights and competitive intelligence for the Internet of Things (IoT) and Industry 4.0, recently released a IoT Use Case Adoption Report 2021 revealing where 200 executives at companies adopting IoT technologies across 48 different use cases are investing their money.

Industree 4.0 is exclusively sponsored by SAP