The Intelligent Enterprise for Paper and Packaging Part 1: Vision 2025
For decades, energy-intensive commodity businesses for paper and packaging aimed for better process control, leading to higher product quality with less energy consumption. This would help to both reduce costs and maintain a healthier environment. A plethora of concepts and devices were invented to control the production and verify or predict the product quality. This approach had some measure of success, but it had its limits.
Use of technology in the paper and packaging sectors has been common for many years. Paper companies were already deploying in-line sensors in the 1970s, and using real-time data from their machines to understand and improve the making of their products. When reading today's definitions of "Industry 4.0," you could think that the fourth industrial revolution already happened years ago in this sector. So what's the hype today?
While concepts for real-time analytics and predictions have been around for many years, information technology has advanced greatly and become affordable. This allows companies to apply IT beyond manufacturing to all steps of the value chain. The use of digitally enabled and connected equipment can create high-quality products, reduce waste, and add recycling capabilities to facilitate a circular economy. In addition, paper and packaging needs to respond to global trends such as empowered customers, disruptors from adjacent industries, the availability and prices of raw materials, and the application of the latest digital technologies.
By 2025, a substantial part of paper and packaging companies' value, reputation, and differentiation will come from services. These services will be delivered around highly customized products, enriched by digital information.
To get there, paper and packaging companies need to focus on five strategic priorities:
Customer centricity
Offering small lot sizes and individualization
Running smart factories and digital networks
Supporting value-added services and new business models
Producing for purpose
To achieve the 2025 vision, companies need to change the way they operate. They must increase the transparency of their own processes and combine this with real-world awareness, including customers and the environment. Winning and keeping business will be based on providing great experiences across all interactions.
By shifting routine tasks from humans to business systems enabled by machine learning and artificial intelligence, they will free up the capacity needed to define and pursue innovative and transformative business models.
The paper and packaging sector is being reshaped by four major trends.
Overcapacity: In some business segments, such as graphic papers, overcapacity leads to price erosion; other areas, such as packaging and hygiene, are doing well. A constant shift in production capacity can be expected.
Automated intelligent network: The digital twin of the value chain representing machines, products, and logistics will lead to higher value for all players. Paper and packaging producers will collaborate along the entire value chain, enabled by digital technologies to form an "outcome network." Disruptors will continue entering from all sides, including from customers, suppliers, and partners.
Individualization: Customers require products that fit their exact and individual needs, provided at the highest service level.
Global uncertainty: Increasing customer expectations and con-tinuing geopolitical uncertainties add ambiguity to the entire supply chain. Paper companies must react quickly to global changes and also to regional demand, tariffs, social influences, and more.
Being able to address industry challenges will determine who will be among the winners in the next 10 years. According to Forrester Research, innovative companies focus on digital priorities to help them achieve digital transformation more than other manufacturing companies.
Where is the industry going - 2025
Paper and packaging is a commodity business, but customers have individual needs regarding dimensions, grade, grammage (weight), and other characteristics of "their" products. To reduce cost and increase efficiency, companies use a mantra of larger lot sizes, process integration, and automation.
Automation has already achieved a level of production that would be difficult to increase, and customers are still demanding higher value-add, higher service levels, and quicker delivery.
In 2025, services will comprise a substantial part of paper and packaging companies' value and differentiation. Services will be delivered around individually customized products and enriched by digital information. Process parameters, once correlated, can provide additional value such as use recommendations. Or, think of quality profiles for each single roll, allowing for optimized subsequent processing. Also, based on purchasing history and intended use case, assistance can be provided to develop the correct product specifications.
As labor is frequently too expensive compared to the often low-margin products, intelligent IT can help companies achieve more-efficient processes and higher customer value. For example, it is already common practice to use manufacturing data analytics for optimizing product quality and avoiding scrap. The application of intelligent IT will spread from core value-creating processes, such as manufacturing and transportation, to all over the company, including procurement, planning, customer interaction, customer service, and so on. Intelligent IT includes automating processes such as resume matching, invoice verification, and even identifying spare parts using a smartphone camera. Finally, it will form the truly intelligent enterprise.
Paper and packaging companies will need to redefine their core competencies in light of digitalization and rebuild their business strategies around them. It's no longer sufficient to sell products at low prices. They will need to take advantage of digitalization to optimize their manufacturing operations, supply chains, and customer interaction to improve their products, services, and the customer experience.
Digital tools will enhance and transform internal and external processes and drive even more productivity gains and cost savings through autonomous health reporting of assets, predictions of manufacturing outcomes, supply chain issues, or the actual needs of a customer. This will allow for better asset usage, better product quality, and in-time fulfillment of customer needs.
In a next issue, we will talk about the strategic priorities of paper and packaging companies.
If you would like to learn more or talk with SAP about how we support the paper and packaging industry, check out our Mill Products home page.
Alfred Becker, SAP SE, Global Lead for Paper and Packaging
Asset Management
I recently attended an hour-long technical presentation entitled "The Latest in Process IIoT". Over half of it discussed HART protocol. If you have spent much time in process control, that should tell you something.
HART was introduced in 1986; its 39 years old. It allowed the traditional 4-20 milli-amp signal from an analog transmitter to have an additional digital component super-imposed on it. The additional digital information could give you configuration and calibration information, as well as additional features such as accumulation calculated in the device. For example, if you have a mass-flow measurement for a critical material that you are adding to a tank and want precise control of how much you are putting in, the mass flow meter could do the accumulation itself and send it to the control device through a digital HART signal. Therefore, your control device could have one pair of wires that connects to the mass flow transmitter in the same way as before and get the same 4-20 milli-amp signal for the real-time mass flow measurement, but also enable you to get an accumulation, calibration, and configuration information.
What is new about 39-year-old technology? The answer is not much, other than the fact that it is not the only protocol of its kind.
Around 1999, Fieldbus was introduced. This allowed instrumentation to be connected with a multi-drop cable instead of having to wire each instrument individually. While it does not provide for 4-20 milli-amp signals like HART, it can provide power to the field device, which can reduce the number of power supplies needed. It is a digital-only communication protocol that (like HART) provides a lot more information than just the measured signal.
Over time, new field protocols have proliferated. What used to be a standard analog 4-20 milli-amp approach has become a buffet of services. An engineer designing their control system has choices to make that didn't exist prior to 1986. These more recent protocols put the conversion of analog to digital communication in the transmitter, instead of at a field termination panel at a controller.
The issue that arises with digital field communication is the configuration and maintenance of this instrumentation. To map the signals to meaningful tags/parameters, a configuration data file is loaded into the controller so that it knows what to do with the signals it is receiving. Each instrument can have its own data file that is required to make it communicate.
How do we manage all of those data files? How do we effectively maintain these instruments?
Asset Management is an application that maintains an inventory of assets (like instruments) and can manage the associated configuration files. Having a centralized system makes it much more manageable than having to hunt around for disks or Internet downloads to get devices to talk. When you have operating system or control system upgrades, you want to be able to restore communication to the field without having to figure out what may or may not work after the upgrade.
Instrumentation is one kind of asset. Motors are another kind of asset. There are Asset Management applications that can maintain motor runtimes to help determine when maintenance is merited and can process work orders and maintain a history of prior maintenance. Managing maintenance this way is helpful for any asset, including instrumentation.
Valves are also assets. An Asset Management application that could help diagnose stiction and hysteresis can be very helpful. Work order history and processing is also a desirable attribute of such a system.
More complex equipment, like a compressor, is also an asset. An Asset Management application could be used for maintenance not only of the motor that drives it, but to also include the complete asset. Can we use machine learning in this Asset Management application to predict required maintenance? Can it include maintenance procedures and checklists for the entire unit, not just the motor? Can it include an inventory of spare parts for the asset?
At this point, it should be clear that Asset Management could mean a lot of things. Depending on what assets we are referring to, an Asset Management System could have different meanings.
Motors, valves, and compressors are not new assets. Many of the digital communication protocols to field devices (like HART) are not new. However, the proliferation of these digital protocols has created a new environment in which Asset Management Systems are increasingly desirable. That has led to the application of these systems for instrumentation as well as other assets.
Notice that nowhere in this discussion of Asset Management have we mentioned the Internet. When a controller communicates by HART or Fieldbus to an instrument, the Internet is not in that path. So why is HART pertinent to "The Latest in Process IIoT" (Industrial INTERNET of Things)?
The confusion that arises in Industry 4.0 is that a mash up of technology and terminology produces confusing and interchangeable terms. Asset Management is one of those terms. It is clear why an Asset Management System was not as necessary when every instrument had a pair of wires landed on a termination panel providing a single analog value to a controller. Now that digital field communication has made it more of a necessity, Asset Management Systems are being applied to assets that may or may not include instrumentation. It is another technology that is being branded as part of IIoT, even though there is no inherent Internet component to it.
When considering an investment in an Asset Management System, it should be noted that nearly every instrument or controller on the market today supports HART. However, the vast majority of HART enabled systems do not make use of these capabilities. Even though additional functionality is provided by the digital capabilities, most of the industry with these with digital capabilities just wire in the 4-20 milli-amp signal and do nothing more. To justify an Asset Management System for instrumentation, these capabilities need to be applied.
As with any system, it breaks if it is not used. It may sometimes be more convenient to use a handheld meter to diagnose or maintain an asset in the field, but if information bypasses the Asset Management System you will have a system with bad information. Therefore, investing in such a system requires a commitment to use it.
When you are presented with an Asset Management System, some questions to ask are:
What assets does it manage?
Will it include management of data files for digital field communication?
Are we going to make use of the digital field communication capabilities we have?
Are we going to be disciplined in our use of the system?
How does the system commission new assets or decommission out of service assets?
Will it need to synchronize inventory with an ERP/SAP type of system?
In this confusing era of buzzwords, it can be hard to know what is or is not IIoT. Regardless, Asset Management is an application of growing importance and benefit if used properly.
Pat Dixon is Southwest Region Engineering Manager for Global Process Automation (GPA), a controls system integration firm.
Pat and his colleague Bill Medcalf will be presenting a tutorial "The Internet of Things/Machine Learning" at the IEEE Pulp and Paper conference on June 27. This tutorial is intended to help the user base know what questions to ask and what concerns to address before investing in IoT based technologies. The registration link is https://pulppaper.org/tutorials/
Why Australian Internet of Things business Reekoh is thriving
To understand how to build an award-winning Internet of Things (IoT) business with high profile clients, look no further than Australian data integrator
Reekoh.
Founded in 2015, the business already boasts the likes of Brisbane Airport Corporation, Moreton Bay Regional Council, UTS and WaterGroup as clients. Not only that, but Gartner named it a Cool Vendor and featured it in various research. Reekoh has also won various cross-industry awards.
So, why has Reekoh received such recognition in a relatively short space of time?
Before co-founding the company, Reekoh CEO Dale Rankine worked in the enterprise software and system integration industry. Despite the opportunity to work in the IoT space, there were already some 500 entities that called themselves "IoT platforms". Rankine acknowledges that there was zero point in building another one.
But he believed that the market was - and still is - confused about what the term, "IoT platform" meant. Many companies were using the same moniker to deliver disparate services and applications.
Seven Things You Need to Know About IIoT In Manufacturing
Louis Columbus is currently serving as Principal, IQMS, part of Dassault Systèmes.
IoT cybersecurity innovates as more businesses adopt devices
The Internet of Things (IoT) has come a long way since
Kevin Ashton coined the term in 1999. It is not only a reality in 2019, but it is on the verge of becoming a mainstream feature in our era of connectivity.
Cybersecurity measures must consider how the presence of the IoT will change the surface of a network.
The burgeoning growth of the IoT is presenting new opportunities for data, and new ways for cybercriminals to access sensitive information. Here is what the IoT means for networks and how its presence creates new challenges for
cybersecurity.
One can look at a slew sharing economy applications (cars, scooters and bikes) and realize that none of these things would be possible without being able to connect to them digitally. One can check the utility meters on most homes and apartment buildings, and realize they are all smart meters that can be read and interacted with remotely. One can even get behind the wheel of almost any new car and be able to access navigation controls, music or a connected anti-theft system.
Artificial Intelligence might seem like a dystopian science-fiction future for some, but it's already transforming our daily lives and will certainly play a growing role in IoT applications and deployments.
The Internet of Things (IoT) is about sensors embedded into devices of all kinds, which are connected to the internet and provide data to be analyzed to take action, be it sending a drone to a complex construction site or detecting free parking spots. In any case, the success of those actions depends on the analysis previously made by Artificial Intelligence, better, Machine Learning.
As the data created by devices keeps growing -it's expected to reach 847 zettabytes by 2021, according to Cisco-, Industrial IoT (IIoT) markets are becoming aware that the combination of IoT and Machine Learning not only enables new products and services but also increases efficiency and competitiveness, which is no small development. And I'm not just talking about predictive maintenance, which is probably the most widely recognized application of AI in IIoT at this time.
