Dec 2, 2024

Achieving Greater Resilience and Flexibility Through Standards

To succeed in today’s market, companies need flexibility and transparency in production to significantly lower costs than before. However, companies in the manufacturing or process industries often find themselves trapped by the technologies they use and the associated methods, requirements, and mindsets, some of which are decades old.

• #innovation
• #ITgoesOT
• #manufacturing
• #resilienteproduktion
• #resilientproduction
• #sdm
• #softwaredefinedmanufacturing
• #standards

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Steven Vettermann

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In daily operations, only selected optimizations are made, which can consume a lot of resources. For example, when it comes to using an outdated serial interface on a machine to integrate it into the new board project for the introduction of AI. This leads to what can be described as “I don’t have time to sharpen the saw; I’m too busy sawing!”

When companies in the manufacturing industry ask themselves, “We’ve achieved a strong position in the global market, but what do we need to do to survive the coming years?” the answer is clear: “Master processes, digitize consistently, and adopt standards”.

Creating Information-Flows and Breaking Down Silos

More than 30 years ago, product development began to focus on processes and standardization opportunities. Only by truly understanding their processes can companies start to optimize them or replace them with better ones. This marked the birth of PLM (Product Lifecycle Management) and its accompanying methodologies, which had a massive impact on workflows and the IT systems used. This was accompanied by the need to establish and adhere to data and process standards. Transformation isn’t always enjoyable, and this new world didn’t emerge on its own. But at the end of the day, the result was structured and seamless information-flows, even across company boundaries.

If companies want more flexibility and lower costs in production, they must first understand what resources are working together and how. They also need to cultivate a natural interest in modularizing and standardizing as much as possible, regardless of vendor or solution. Otherwise, optimizing existing heterogeneous, sometimes manufacturer-specific machine environments and traditional automation solutions becomes a tedious task, and companies will fail to fully leverage the digitalization opportunities available today and in the future.

The Path to Software-Defined Manufacturing and Production

Solutions for software-defined manufacturing offer an alternative to traditional, resource-intensive, and outdated automation technologies. They provide transparency in production, flexibility in the use of available resources, and the ability to dynamically adjust processes during operation. These are the goals companies must achieve to remain competitive in the global market.

The prerequisite for this is a clear understanding of processes. This includes not only the value streams, and the machines and systems involved but also the data exchanged between machines and between machines and humans. The more you describe these processes in (standardized) modules and defined interfaces, the more flexibly you can operate in production. This approach enables the creation of a future-ready, intelligent production network. Ascon Systems supports this journey with its consulting program, Ascon AIM.

With our software solution, Ascon Qube, we provide the technical means to implement software-defined production. Digital twins manage value streams in production online. To facilitate communication with operational assets as well as enterprise IT systems, our “Connectivity” module delivers a protocol-agnostic layer that makes information easily accessible, including for AI applications. Our connectors for standards such as EtherCAT (IEC 61158), OPC UA (IEC 62541), MQTT, and many others ensure seamless collaboration between IT and OT. This breaks down the silos between these domains and offers our customers unprecedented flexibility and scalability (see image).

IT-OT-convergence enables seamless data flow in production

Software-Defined Manufacturing: Flexibility for the Future of Manufacturing

Software-defined manufacturing, through clear abstraction and modularization, provides the flexibility required for the production of the future (see also The Evolution of PLCs: What Will the New Normal be?).

With its strong process orientation, it also naturally bridges the gap to the data spaces of Industry 4.0, notably Catena-X and Manufacturing-X or Process-X. At the technical core lies the asset administration shell (IEC 63278), which supplies data and information about assets and products. Solutions for software-defined manufacturing are uniquely positioned to continuously fill this pool and make it available in the data spaces—for instance, in production-related applications like the digital product passport to track CO2 emissions

Just as standards are effectively used in communication, many other established standards can also be leveraged to save costs. There’s no need to reinvent the required services and modules—they have long been defined in ISA-95/IEC 62264 or IEC 61499 and, as demonstrated below, can be seamlessly utilized.

Software-defined manufacturing takes existing standards into account

In the production of the future, where design changes, logistics updates, or AI-results automatically reconfigure production, it is critical to know your processes, keep information flowing, and easily leverage existing standards.

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Sep 4, 2024

Digitalization push in the process industry

The process industry includes sectors such as the pharmaceutical and chemical industries, where raw materials are converted into products through chemical, physical, or biological processes. The VDI/VDE/NAMUR 2658 series of guidelines defines recommendations for automation concepts for modular systems, interfaces, and information models that herald a new era of digitalization in the process industry. The manufacturing and process industries have different automation and system design requirements, but similar needs and solutions.

• #automation
• #industry40
• #innovation
• #manufacturing
• #OTgoesIT
• #processindustry
• #SDM
• #softwaredefinedmanufacturing

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Steven Vettermann

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The VDI/VDE/NAMUR 2658 series of guidelines provides a framework for modular systems and information models that increase production flexibility and improve production efficiency. It is critical for process industries looking to improve ROI and increase plant efficiency through modular and flexible production approaches. By standardizing interfaces and data models, the VDI/VDE/NAMUR 2658 guidelines enable better interoperability between components from different manufacturers and simplify the expansion or reconfiguration of process plants.

NAMUR Open Architecture (NOA) was developed in parallel. Its goal is to make it easy and safe to use production data to monitor and optimize systems and devices.

Components of the Guidelines 

The series consists of several concepts that describe technical solutions. They are used together to improve manufacturing processes through modular automation. 

The guidelines support the development and implementation of modular process units known as Process Equipment Assembly (PEA). Specifically, PEA refers to the automation technology of individual modular units designed to perform specific process tasks within a plant. This modularization is intended to make the planning, launching and operation of process plants easier and more flexible. PEAs are integrated into a process orchestration layer (POL). This is a higher-level control layer that coordinates and manages the various PEAs. In addition, the Module Type Package (MTP), a standardized file format derived from AutomationML, is defined and used for integration between the PEA and the POL. It allows modules to be easily integrated into the overall system. 

This set of recommendations fundamentally changes the interaction between process engineering and automation technology and represents a paradigm shift in the process industry.

Comparability of solutions in the manufacturing and process industries

Software-defined production in the manufacturing industry must also implement a process orchestration layer (POL) and address the aspects required in the NAMUR Open Architecture (NOA). Following the software-defined paradigm, the process industry’s Module Type Package (MTP) could also be realized through digital twins and the associated microservices. 

With its Ascon Qube software, Ascon Systems offers a solution to build this bridge. From a technological perspective, Ascon Systems’ approach is to separate hardware and process control in production, whether in manufacturing or process industries. This dissolves the rigid and inflexible connections between hardware and software, as implemented in traditional automation solutions, and replaces them with a network of modules and services.

The underlying hardware functions are abstracted, and the actual capabilities are determined purely by the software. This decoupling of hardware and capabilities or behavior is also the technical basis for the apps on your smartphone, for example. The smartphone’s built-in hardware sensors are used by apps as spirit levels, business card scanners, sound meters, and so on. A piece of hardware no longer executes a program (1:1), but a piece of hardware is dynamically used for a variety of applications (1:n). To achieve software-defined production, it is therefore necessary to decouple the physical modules of the production systems (hardware) from the software that runs on them. This is exactly what the Ascon Qube was designed for.

In today’s production systems, however, hardware and software, including process control and consideration of company-specific communication standards, are often very closely linked and programmed on PLCs. This prevents the full potential of digitalization from being realized. By separating hardware and process control and following the software-defined paradigm, it is possible to implement a software service architecture that replaces the traditional automation pyramid with its rigid point-to-point connections and in which the behavior and interaction of modules is flexibly and efficiently orchestrated at a higher software level. 

Ascon Systems shows a migration path: from traditional to modern (keyword: OT goes IT). A step-by-step approach makes sense when introducing new technologies. 

For the process industry, for example, this could mean reading out existing MTP implementations via Ascon Connectivity and making analysis, AI or other tools available independent of the manufacturer. In the future, this rigid, file-based data communication can then be transferred to a service environment (XaaS), allowing processes to be controlled online in an optimized way. The Ascon Systems technology can be integrated adaptively. 

Experience can be gained, functionalities can be extended and new features can be integrated. It does not always have to be the remote control of multi-variant and/or complex processes. Quality and documentation scenarios, for example, are worthwhile: Process monitoring and documentation of batches, with the ability to react flexibly to variations. Another promising area is the implementation of solutions that enable faster commissioning through the use of prefabricated function blocks. These are easy to use independently of the system and can be loaded remotely (no on-site programming), which also reduces errors during commissioning and operation. Such implementations enable the consistency of information that is increasingly required in today’s enterprises. The information is available and can be used easily.

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Jul 3, 2024

Use Case: How digital twins help save up to 29.5 percent energy in mechanical engineering

A crucial step in manufacturing is machining, which includes turning, milling, drilling, and grinding to shape workpieces. Coolant lubricants are frequently used in this process. However, their use is associated with high energy costs. So high that a consortium of research and industry, including us, has developed measures within the BMWK-funded (BMWK = Federal Ministry for Economic Affairs and Climate Protection) project E-KISS to significantly reduce energy consumption and increase productivity. The project has now concluded, and the results are in: E-KISS achieved a 29.5 percent reduction in electricity usage. The figures are impressive and show the potential of data science combined with retrofit measures.

• #digitaltwins
• #manufacturingtechnology
• #retrofit

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Steven Vettermann

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The Conditions

Machine tools play a central role in industrial manufacturing companies. Sales revenues were 229 billion euros in 2023 [1] (2022: 208 billion euros). Although there are other machining processes, machine tools are still used in industrial manufacturing. They operate with coolant lubricants, which must be available at the right time, in the right place, and in the right dosage to achieve high and consistent quality. Manufacturing with machine tools and coolant lubricants requires additional systems, some of which are legally mandated to ensure occupational safety. All these elements together form a complete system with many components, which is energy-intensive and accounts for an average of 30 to 35 percent of a manufacturing facility’s energy demand, sometimes even up to 60 percent [2]. To reduce these high numbers, a consortium of science and industry initiated the research project “E-KISS – Energy Demand-Oriented Operation of Coolant Lubricant Systems” [3]. The project pursues several goals regarding savings. First, the energy demands of the entire system are to be measured, documented, and then reduced through the use of key digital technologies such as cyber-physical production systems and digital twins. E-KISS aims to achieve a reduction in energy demand of approximately 20 to 30 percent compared to the initial situation by the end of the project.

Additionally, the coolant lubricant systems, including the exhaust system, are to be adapted while maintaining or improving process quality, which also leads to energy savings. Almost as a side effect, E-KISS results in a more environmentally friendly lifecycle for workpieces, helping companies achieve their climate protection and sustainability goals.

The project partners of E-KISS include: Technical University of Braunschweig (IWF), Robert Bosch GmbH, ONLINE Industrieelektrik und Anlagentechnik GmbH (Online IAT) – and us, Ascon Systems. The expertise is distributed among production sensor technology (IWF, Online IAT), machine application (Robert Bosch GmbH MWS – subcontract), and the development of digital models and methods (Ascon Systems, IWF).

More Transparency with Contextualized Data Throughout the Product Lifecycle

Plant operators usually have little or no transparency regarding the energy demands of individual components and systems, especially in manufacturing processes where multiple systems work together, as is the case with machining, particularly with coolant lubricants. They are used in grinding to prevent excessive wear and scrap from grinding heat. These processes consume a lot of energy. Efficiency can be improved by using intelligent controls and regulations integrated into existing systems through retrofit measures. Retrofit refers to those adjustments to existing machines and equipment that make them fit for the networked production environment through improvements and expansions, rather than complete renewal.

The research project E-KISS began with the design and setup of a cyber-physical production system. The physical reference system represents the current state and the specifics of a real grinding machine as established at the TU Braunschweig for the project. The cyber-space includes components for modeling and simulation, including sensors and our digital twin. In this environment, data from the physical system are captured, processed, and interpreted for decision-making. Initially, a measurement infrastructure with IT networking, consideration of various machining processes, and control of the overall system was established. At the start of the project, grinding trials were conducted to capture and reflect the grinding conditions and energy demands of the machine under conventional conditions.

Digital Twin: Data Changes Realities

Our focus in the research project is on the capabilities of the digital twin. It creates a complete digital model of the system with its properties, states, dependencies, and the interaction of the systems, providing a comprehensive view of the real systems. The digital twin is deeply interconnected with the individual system elements. Additionally, we, together with TU Braunschweig, undertook the data-based modeling of the system. Focusing on energy savings in coolant supply, it was particularly important to capture data on processes, tools, and workpieces and continuously record changes. We aimed to achieve transparency about the processes and the underlying data, identify control parameters, and later adjust operations on a physical level.

As the basis for E-KISS, a virtual overall model of the machine tool and the coolant lubricant system was created, where data converge in near real-time. Current measurements and system signals are visualized live via a dashboard. On this basis, we developed approaches and methods for optimizing energy consumption.

All captured data is entered into the digital file, making it available in the future and in its semantic context.

The special feature of our digital twin is that it creates a digital replica and enables bidirectional coupling with the real system. It ensures that the digital twin receives data from the system in real-time and can also send data back to the system, influencing the behavior of the entire system. And that’s precisely what E-KISS is about.

29.5 Percent Electricity Savings

For the calculations on whether and how efficiency improved, a two-shift operation with 4,160 operating hours per year was taken as the basis, with 27 percent for direct processing, 28 percent for setup time, and 45 percent for idle time. The underlying electricity price is 0.2446 euros per kilowatt-hour.

Optimizations included direct energy savings by shutting down machines during downtime and idle times, process adjustments through introduced sensor technology, and the full integration of the digital twin, including intelligent adjustment of the identified control parameters.

Under these conditions, the energy savings amount to 29.5 percent, which corresponds to 13,590 kilowatt-hours and 3,324 euros per year per machine.

From Model Environment to Practice: After the tests proved the success of the research project, the consortium implemented an identical prototype in a real environment in the final step of the project. Specifically, the contents were transferred to an SME in the metal processing sector and connected to a milling machine there. The differences from the research environment lay in the physical implementation and the specific requirements of the system. The results were reproducible, underscoring the findings obtained in the model environment, albeit with different data.

Conclusion

The research project shows that data science leads to insights into actual energy consumption as well as material usage. Combined with retrofit measures – including more and better sensors and individual workpiece components – the data help companies use resources more efficiently, protect the environment, and save costs. The research can be easily and straightforwardly transferred into practice.

[1] Turnover in the German mechanical engineering sector by selected sectors in 2022 and 2023 https://de.statista.com/statistik/daten/studie/173637/umfrage/branchenumsatz-des-maschinenbaus-in-deutschland-nach-sektoren/

[2] Li, W., Zein, A., Kara, S., Herrmann, C., 2011. An Investigation into Fixed Energy Consumption of Machine Tools, in Glocalized solutions for sustainability in manufacturing: Proceedings of the 18th CIRP International Conference on Life Cycle Engineering, Technische Universität Braunschweig, Braunschweig, Germany, May 2nd – 4th, 2011, Springer, Berlin, Heidelberg, p. 268.

[3] Förderkennzeichen: 03EN2037A, B, D, E

Reading tips:

Elisabeth Zettl et. al.: Ökologische und ökonomische Bewertung des Ressourcenaufwandes: Industrie-4.0-Retrofit-Maßnahmen an Werkzeugmaschinen (VDI, 2022)

Christopher Rogall et. al.: Systematic Development of Sustainability-Oriented Cyber-Physical Production Systems (MDPI, 2022)

Christopher Rogall et. al.: Application of sustainability-oriented cyber physical production systems to grinding processes (Procedia CIRP, 2023)

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Jun 20, 2024

How and why software-defined manufacturing is changing the industry

The future of production lies in digital, automated processes. This is the only way for companies to become flexible and less affected by spontaneous market developments and skilled labor shortage. Software-defined manufacturing (SDM) is the name of the evolution that underlies this change in production conditions. What sets this apart from conventional methods is the fact that software and software-supported technologies are at the very center of manufacturing processes.

• #industry40
• #manufacturing
• #SDM
• #SoftwareDefiniedManufacturing

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Steven Vettermann

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SDM promises a more efficient production method and a substantial enhancement in the adaptability of production lines. Innovations and new business models can also be advanced more rapidly in a software-centric production environment.

The basics of Software-defined Manufacturing (SDM)

In traditional manufacturing, machines and systems are central and controlled by hardware, specifically the PLC. Software-defined manufacturing shifts this concept by controlling hardware, including the PLC, through dynamic software systems or platforms. This approach optimizes the hardware and the entire production chain. A key advantage is the ability for companies to respond to market changes almost in real time, as adjustments to new requirements, designs, and production processes can be made via software updates rather than physical modifications. SDM incorporates essential digital technologies such as the Internet of Things (IoT), cloud computing, and artificial intelligence (AI).
SDM platforms facilitate real-time monitoring and adjustment of production processes, leading to reduced downtime, improved quality, lower error rates, and increased production capacity. They enable flexible retooling of production lines, which is especially advantageous for industries with high product variability. This approach accelerates production times, enhances production flexibility, and lowers operating costs through optimized production and increased productivity.

The role of IT-OT-Convergence

The convergence of information technology (IT) and operational technology (OT) plays a central role in software-defined manufacturing. This convergence leads to a seamless integration of data and control flows between administrative and production-related areas of a company, creating a bridge between the office and production. By integrating IT and OT systems, production data can be registered and analyzed in real time. This increases transparency and assists in making precise and well-founded decisions. Convergence enables companies to anticipate problems in production before they occur or, if they do, to react quickly and resolve them before they lead to major disruptions. IT-OT convergence encourages the development of predictive maintenance strategies, which in turn increases uptime and reduces unplanned downtime. In addition, IT-OT convergence can achieve efficiency gains and cost savings by eliminating redundant systems and processes. The integration of IT and OT is a decisive step towards a fully networked and intelligent production environment that forms the foundation for the factory of the future.

Hyperconvergence in manufacturing

Hyperconvergence extends the idea of convergence by unifying storage, computing and network operations in a single, organized system architecture. This enables companies to simplify and centrally manage their IT landscape, reducing administrative burden while increasing the flexibility and responsiveness of production systems. It eliminates data silos and decouples interlinked control units.

Hyperconvergence enables quick reactions to changes in production by dynamically reallocating resources as required. This is particularly beneficial in environments with frequently changing production requirements, as companies can react faster and more efficiently to new market demands. Thanks to the high modularity of the systems, they can easily be adapted to changing production conditions.

In manufacturing companies, hyperconverged systems can reduce IT footprints while increasing performance and capacity. The centralized management of resources through a hyperconverged infrastructure improves responsiveness to demands from the production process. It facilitates the implementation of advanced analytics that help optimize the entire manufacturing process.

Use Case: SDM at the Stuttgart machine factory

At the Stuttgart machine factory of the ISW (Institute for Control Technology of Machine Tools and Production Equipment), we have successfully applied the capabilities of SDM in practice. Machine and AGV (Automated Guided Vehicle) process orchestration is conducted independently of the manufacturer using digital twins. High-performance, parallel communication between digital twins, machines, and IT systems is facilitated via standard protocols such as OPC UA and REST. Products, processes, and resources are interconnected and can be adjusted flexibly. Interactions are recorded as discrete events to ensure full transparency and flexibility. Contextual data recording provides an excellent foundation for AI-based optimizations. Real-time process monitoring is achieved through NVIDIA Omniverse visualization. Ascon Systems is thus delivering a comprehensive and powerful industrial metaverse application within SDM4FZI.

The use case proves that software-defined manufacturing can lead to even more advantages. The process can be changed online and visualized remotely and in real time. The 3D platform NVIDIA Omniverse is used for visualization in this use case. Additionally, employees on site can receive all necessary system status and maintenance information on their tablets, rendering terminals and paperwork obsolete. This makes it possible to demonstrate the advantages of software-defined manufacturing itself, as well as the potential for refitting brownfield environments.

Ascon Systems SDM4FZI demonstrator with 3D

This and other use cases illustrate the many possible uses and applications of software-defined manufacturing. They are described in detail on the project website https://www.sdm4fzi.de.

Basis for the software-defined factory – the factory of the future

Technologies like SDM enable the “factory of the future,” characterized by highly automated and flexible production facilities that leverage digital control to swiftly respond to market changes and individual customer needs. Robotics, advanced automation, AI, and machine learning are key to enhancing efficiency and reducing errors. In these factories, all systems and machines are interconnected and centrally monitored and controlled, allowing for continuous process optimization and quick adaptation to new requirements. Sensors and networked devices collect and analyze data in real time to improve production and quality. These factories are more efficient and sustainable, optimizing material and energy use. Additionally, they offer a safer and more ergonomic work environment, as robots handle many hazardous or repetitive tasks. The factory of the future signifies a major shift in manufacturing through the integration of SDM and other advanced technologies.

A research consortium comprising experts from science and industry, including our participation, is currently exploring the potential of software-defined manufacturing in the automotive and supplier sectors through the publicly funded project “SDM4FZI – Software-defined Manufacturing for the Automotive and Supplier Industry“. The project is set to conclude at the end of 2024, initial results were showcased at the Stuttgart Innovation Days on September 17th and 18th, 2024.

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Jun 11, 2024

Will industrial production be more successful in the future without PLCs?

In today’s fast-paced industry, the ability to seamlessly adapt to new technologies and market demands is becoming increasingly critical for success. Manufacturers who want to lead the global competition need to establish seamless data flows within their production processes. This approach enables more efficient and flexible production that can respond quickly to changes and manufacture customized products efficiently. If a flexible infrastructure is crucial, then anything that is rigid, costly and time-consuming must be eliminated. And PLCs are increasingly being cited in this context. Why does the use of a PLC, whether physical or virtual, hinder progress in production?

• #efficiency
• #industry40
• #PLC

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Steven Vettermann

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The main obstacle to the use of PLCs is that the factory of tomorrow will achieve flexibility through seamless integration capabilities – and a PLC is not built to achieve this.

Three shortcomings characterize traditional PLC systems:

1. Incompatibility with modern technologies
   Many traditional PLCs are not able to seamlessly integrate with newer technologies such as AI co-pilots, cloud computing and big data analytics and fully support communication standards. However, these technologies are crucial for the realization of smart and connected production environments required for modern manufacturing processes.
2. Lack of scalability and flexibility
   Manufacturers often face the challenge that traditional PLCs are limited in their capacity and functionality. Adding or modifying functionality can be expensive and complicated, limiting adaptability to changing production requirements. In addition, it is difficult to quickly reprogram PLCs to adapt to different products and processes.
3. Technical and operational limitations
   PLC programming and maintenance requires specialized knowledge and can lead to significant operational disruptions if key personnel are not available. In addition, communication capabilities are limited by proprietary or outdated protocols, which hinders the flow of information and integration into modern production environments.

Economic benefits of replacing the PLC

If the PLC is replaced and hyper-convergent IT solutions are integrated instead, there are two significant economic benefits:

Cost savings

In August 2022, the consulting firm McKinsey found that 8% of the companies surveyed in the automotive industry plan to invest more than 500 million US Dollars in automation over the next five years¹. This investment must be worthwhile. Ascon Systems found that a medium-sized car manufacturer spends an average of six million euros per year and plant on automation solutions (purchase, replacement, maintenance, modifications, etc.). On each line, there are PLCs that take care of controlling the machines themselves and others that control the process (sometimes you find a mix of responsibilities on a PLC, but that is neglected here). Depending on the use case a different share for controlling the machine and/or the process is needed. For some, perhaps only 5% is needed for process control, for more complex scenarios maybe 50%.

So let’s assume that, on average, 30% is needed for process control and 70% for machine control. Let us now say that the first step is to replace only the PLC that controls the process (the 30%). Let us also presume that controlling the process via modern IT costs 25% less than controlling the process via PLC. Based on these figures, the conservatively estimated savings from replacing the PLC with IT are on average:

• Process control only = € 450,000 per year and system
• 100% replacement = €1,500,000 per year and system

Of course, one can find arguments why this is not realistic. However, the need to be more flexible, reaching the next level of automation and saving money should be motivation enough to do it.

Improved productivity and agility

Switching to modern IT-based solutions enables higher productivity through improved levels of automation and more efficient production processes. It also increases flexibility in production, which significantly improves the ability to respond to market demands and manufacture customized products in smaller batch sizes.

The progressive integration of modern technologies into the production environment is not only a way to increase efficiency and reduce costs, but is increasingly becoming a necessity in order to remain competitive on a global scale. Companies that become more flexible and adaptive in this way will be better positioned to respond to future challenges and benefit from the opportunities that arise.

Conclusion

If you want to remain competitive in the future, respond to the increasing shortage of skilled labor and further reduce costs, you need to think strongly about whether to stick with the old PLC-centric automation technologies or replace traditional OT with flexible IT technologies. This saves costs and at the same time creates the opportunity to incorporate AI co-pilots and data analytics directly into the manufacturing process. And all this at production costs in Germany, which is then competitive on an international level.

Find out more about how Ascon Qube can open a world of manufacturing without PLCs.

1. McKinsey Study: Unlocking the industrial potential of robotics and automation ︎

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Apr 22, 2024

The Evolution of PLCs: What Will the New Normal Be?

Machine control technology has been constantly advancing for the last 100 years. Starting with purely mechanical control, then electrical and electronic, and now software-based and much-discussed virtual control. What is the current situation? What else is missing for the disruptive innovation, standardization, and resilient manufacturing everyone is clamoring for?

• #AI
• #automation
• #industry40
• #PLC
• #techsimplified
• #virtualPLC

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Steven Vettermann

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Manufacturing and processing facilities still used hardwired relay-based control systems well into the 1960s. These were functional, but not flexible. Modifications and maintenance were time-consuming and resource-intensive. In the automotive industry, this type of infrastructure was a severe limitation.

That all changed when engineers developed the first programmable logic controller (PLC) in 1969 – a pioneering innovation that revolutionized the field of automation. The introduction of PLCs made it possible to implement and, if necessary, modify control logic using software. The PLC made it much simpler to program, modify, and expand control logic. For the first time, manufacturers were able to adapt readily to changing production conditions.

Over the decades, technological advancements, particularly in microelectronics, information technology, and communications have considerably enhanced the capabilities of PLCs. What were once very simple devices serving primarily as a replacement for relay logic have become complex control systems with integrated diagnostics, network connectivity, and the ability to process data in real-time. This evolution runs parallel to the development of technology in general. It also, however, shows how the increasing integration of production and information technologies in the form of software has built the foundation for industry 4.0 and the smart factory.

The virtual PLC: not the end, but rather the beginning

The last decade has seen increasing virtualization of systems and hardware. The transformation started with the introduction of the soft PLC. This was a marked departure from what was usually a direct connection between control software and its corresponding hardware. By implementing an additional software layer residing between the hardware and the operating system, a soft PLC enables the abstraction of physical devices. This makes it possible to deploy components such as hardware, software, storage, and networking equipment as virtual resources so multiple users can access them simultaneously. Virtualization also plays an increasingly important role on the level of the control systems. The introduction of the soft PLC has done away with the rigid coupling of hardware and control software, moving the control software up to the application layer of a PC operating system. This considerably enhances interoperability. And depending on the operating system in use, a soft PLC will still retain direct access to hardware.

The next step towards complete virtualization of automation hardware was accomplished by the virtual PLC. In contrast to software-based control systems (soft PLCs), a virtual PLC is completely abstracted. This abstraction and corresponding virtualization of the hardware is implemented using containers¹ or hypervisors², just as it is with other IT applications. The virtual PLC doesn’t care which device you run it on. You don’t install a virtual PLC on a computer, but rather in a container. Which computer that container is deployed on³ is irrelevant for the virtual PLC. But only so long as the container or hypervisor can provide as many interfaces to the hardware as the PLC requires. Except for latency considerations, it doesn’t really matter whether the PLC runs in the cloud, on the edge, or in a data center.

One of most frequently cited advantages of virtual PLCs over conventional automation control systems like soft PLCs is that a virtual PLC reduces the cost and time involved in procurement, wiring, maintenance, rolling out applications, and device administration. This saves resources across the board and prevents bottlenecks. All new technologies have aspects that warrant consideration, of course. IT security and safety are two key topics in this context (see IEC 61508: Functional Safety of Electrical/Electronic/Programmable Electronic Safety-related Systems).

Let’s take a deeper look under the hood

The same functionality with less hardware, but more virtual. Software, cloud-ready. It sounds appealing — and this does truly look like progress. But this is fundamentally the same technology. It requires the same highly sought-after professionals to implement, the same tools and testing, and it comes with the same problems. It also introduces new factors to consider, such as managing the need for experts from a different background (IT vs. OT experts, for instance).

And there are more facets that should not be ignored:

• Which hardware requirements does the virtual PLC have with respect to the server that it will be running on?
• And how will this virtual PLC perform?

Because sometimes all you get is a clone of a physical PLC emulated with software that has just as much (or little) memory and supports interface standards just as poorly (or well) as its physical counterpart. You might experience the situation where a PLC requires enormous quantities of memory on the server it’s deployed on.

These are all things you have to ask the virtual PLC manufacturer or software vendor. Because in most cases it’s not just a single PLC, but rather a project with a larger scope. And suddenly what was once a little computer in the corner of the factory is now a complete data center that requires its own administration and maintenance etc. The same applies to questions about mechanisms for centralized deployment (versus point-to-point) or rolling out patches including the testing this requires.

The logical next step

The advantages of virtualization with respect to flexibility, costs, dealing with bottlenecks, and resiliency are undeniable. But when you talk about PLCs, one topic always comes up: cycle time. This includes real-time performance, in other words, the guaranteed ability to deliver results within a determined timeframe. PLCs — whether soft PLCs or virtual PLCs — read inputs, execute logic sequentially, and update outputs on a scan cycle. Each cycle, this repeats. And if you think about the basic premise of automation, which is all about carrying out discrete steps repeatedly, it makes sense.

But the demands placed on factories have changed dramatically in recent years. Yes, you still need the capabilities a PLC offers, especially when it comes to real-time requirements. But the manufacturing processes that are now being automated have become more complex and varied. Control software needs to keep pace with these developments.

What’s more important now are things like orchestrating the interactions of the various machines and programs, enabling interactions with AI-based services, and ensuring greater transparency in and with other enterprise systems. We’re talking about high-performance, highly parallel processing of big data with very complex interrelationships.

How can PLCs, which are not designed for a scenario like this at all, possibly be the right choice here? Modern IT solutions offer much more efficient options. The point is not to drive the PLC out of the factory and into the data center or the cloud, regardless of whether it’s physical or virtual. The goal is to use PLCs in a way that makes sense and in combination with IT functionality to give today’s manufacturers the ability to meet the demands of tomorrow.

The logical next step is to separate the two control tasks – hardware and process – which today are both programmed into the PLC. The PLC continues to control the hardware (e.g. robots, machines). But the processes (such as the sequence logic) are controlled by more efficient methods.

A look at modern production control

The IEC 61499 automation standard (Standard for Distributed Automation) has helped to make terms such as object-oriented, discrete event processing, and service-oriented architecture more commonplace in automation circles. But in daily operations, people still think inside the confines of what PLCs are capable of.

The easiest way right now, for instance, to tell a welding robot how to execute a spot weld, is to use a PLC. But is it necessary to use the same means to tell the robot at which location this process should take place? Because this is where things get tricky. Products change. Or maybe the company wants to produce different product variants on a single production line. The same applies to process control. Why would you make someone program a PLC to handle the logic or orchestration of multiple robots? Are there other solutions that could accomplish this at least as well? Ones that might even be more flexible and make it easier to implement changes, so that the declining number of PLC experts can spend their time on more important tasks?

Here as well, abstraction is our friend: The answer is decoupling product/process from hardware control.

Just like a virtual PLC has no need to know where the machine it’s running on is located, a welding robot only needs to know how to perform its spot weld. The product/process-specific parameter of “where” is provided from outside. Welding, fastening, clamping, and transporting items become abstract activities decoupled from the machine performing them, making these capabilities easier to utilize. The robot doesn’t need to know anything about the company-specific communications standards (which until now also needed to be programmed into the PLC).

In modern production control, capabilities are orchestrated, not individual machines. This gives companies new options and a high degree of flexibility and independence, also with regard to PLC programmers. And then there’s the contribution toward standardization: Vendors no longer need to program the in-house standards of their respective customers into individual PLCs. They just deliver a “thing with the ability to weld.” The production process is represented with full visibility in the IT layer above it. In IT, you call this type of approach hyperconverged infrastructure (HCI).

The evolution of the PLC runs parallel to the development of automation solutions. Rigid models are being questioned; the future lies in IT-OT convergence and hardware virtualization. Enabling disruptive innovation and fulfilling the demands of resilient production requires more than just virtualizing PLCs. There is currently no other technology that’s better at telling a machine what to do than a PLC. But when it comes to the flexibility of sequencing control, integrating with IT systems and AI, and providing intuitive user interfaces, solutions based on hyperconverged infrastructure are superior.

Ascon Qube

Ascon Qube lets you implement hyperconvergent infrastructures. It’s a vendor-neutral platform for the complete planning, optimization, and control of manufacturing processes using digital twins. This high-performance technology gives you more flexible production processes, creates transparency, and enables the easy integration of AI-based copilots.

Further explanations and definitions:

1. https://en.wikipedia.org/wiki/OS-level_virtualization ︎
2. https://en.wikipedia.org/wiki/Hypervisor ︎
3. https://en.wikipedia.org/wiki/Software_deployment ︎

Want to know more?

Ascon Systems – Digital Shadow

Hyperconvergence in manufacturing: increasing efficiency through IT innovation

The industrial metaverse: what to know about key technologies, correlations, and benefits

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Mar 27, 2024

#CircularEconomy: The crucial role of digital twins from Ascon Systems in battery recycling

Batteries play a crucial role in the future of electric mobility. Their ecological footprint has however been the subject of criticism and the full potential of the value chain is yet to be realized. But all that is changing now. An interdisciplinary consortium comprising industrial and research organizations is exploring as part of the research project ZIRKEL how automation solutions can contribute to battery disassembly and provide the best option for recycling the contained raw materials. In this project our digital twins are of significant importance.

• #batteryrecycling
• #circulareconomy
• #electricvehicles
• #emobility
• #ewaste
• #productlifecycle
• #recycling

Author

Steven Vettermann

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The increasing prevalence of electric vehicles and the batteries they require has raised important questions about the product lifecycle. Most electric vehicles use lithium-ion batteries. Producing and disposing of such batteries takes a considerable toll on the environment. This includes everything from acquiring the raw materials to energy consumption during production and disposal. Recycling these valuable raw materials is a priority from both an ecological and economic perspective because this will help stabilize value chains and contribute to the availability of raw materials. Yet battery recycling presents us with many challenges. The construction of battery packs varies widely, and the composition of the individual batteries involves a mix of different materials. Disassembling the battery systems is time intensive and expensive. Currently, this process is mostly a manual one. The solution to these problems is automation. 

That’s what the ZIRKEL* project initiated by Germany’s Federal Ministry of Education and Research (BMBF) aims to achieve. ZIRKEL is examining every stage of the product life cycle of a battery pack and seeks to strengthen the circular economy through innovation, production technologies, and process routes to make recycling more efficient. The partners participating in the project include, in addition to the BMBF, Liebherr-Verzahntechnik, Arxum GmbH, DMG Mori, Institut für Partikeltechnik at TU Braunschweig, Fraunhofer-Institut für Schicht- und Oberflächentechnik, Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik, Synergeticon — and us.

Battery recycling in the circular economy

The biggest challenges in battery recycling include the varied composition of the components, many of which are bolted or glued in place. This makes it difficult to disassemble the battery packs, which in many cases are also damaged. ZIRKEL is trying to sustainably increase productivity and the economic feasibility of disassembling, breaking down, and sorting battery systems and electric motors. In pursuit of these objectives, the research is identifying the most ecological and economical recycling options for each product while completely monitoring material cycles and optimizing the recycling rate using near-real-time analytics from the surroundings, planning, factory, and product.

We are contributing our expertise with digital twins to the project. During the battery manufacturing process, digital twins link physical production environments to virtual models.  This allows us to collect and store a comprehensive range of data from laboratory equipment. Our contribution also involves providing methods for data visualization and processing. The digital twins allow for careful analysis, definition, and modeling of data interfaces for connected machines and AI platforms. The contextualized data is then used by Synergeticon for AI analysis and by Arxum using blockchain technology to enable the traceability of recycled components for the new EU battery passport. 

During the disassembly and recycling process, the digital twins can enable adaptation to different battery types and conditions, thereby increasing the efficiency of processes within the circular economy. This technology contributes to flexibility and, crucially, can increase efficiency and reduce costs. Digital twins make a vital contribution to closing the loop on material cycles and promoting a sustainable circular economy for all types of electric transportation. 

* The ZIRKEL project is conducting research and developing production technology for the circular economy of highly integrated electric vehicle components such as battery systems and electric motors. Grant project code: 02J21E044

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Mar 6, 2024

Ascon Systems implements first demonstrator for the research project “Plant 4.0”

Berlin is where Mercedes-Benz puts new technologies to the test. The ones that pass are destined for production facilities all over the world. Ascon Systems is here, too, with solutions for data orchestration and automation using digital twins. The initial demonstrator has put the capabilities of these technologies on display.

• #automotive
• #innovation
• #plant4.0
• #resilientproduction
• #solutionpartner

Author

Steven Vettermann

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The financial success of manufacturers increasingly depends on how capable they are of reacting faster to changes in markets and technologies. That’s not possible without shorter product life cycles. 12 companies have now joined forces to research the ideal conditions for creating tomorrow’s flexible manufacturing solutions. The project title is “From conventional production plant to resilient competence plant through Industry 4.0 (Plant 4.0)” and it is funded by BMWK, Germany’s Federal Ministry for Economic Affairs and Climate Action.*

Together with EKS InTec, Ascon Systems is implementing Work Package 2 on digital twins. The goal is to plan, commission, and operate production facilities using digital twins while also enabling changes, thus facilitating the resilience that modern manufacturing demands. The project team is generating the scenarios and specifications this requires and subsequently testing functionality. The latter is taking place at the Mercedes-Benz Digital Factory Campus (MBDFC) at the company’s Berlin-Marienfelde location. This is where the company tests new technologies with the goal of rolling them out to future production facilities all over the world. This can involve technologies for entire production lines, individual workstations, or cells. It can also apply to special assembly equipment such as automatic screwdriving systems or IT infrastructure components that operate as IIoT (industrial internet of things) devices.

The participants have adopted a very agile approach for the project and collected insights from applying the technology. Even though the project didn’t kick off until 2023, Ascon Systems has already completed its first demonstrator.

The test system setup includes up to eight automated guided vehicles (AGVs) that transport vehicle bodies along a predetermined route. The bodies travel to multiple manual and automated workstations in a specific sequence. With the help of lift tables, the auto bodies are raised to different heights to ensure good ergonomics for the people working at the station.

Ascon Systems has modelled the process and information flows using digital twins. The data generated by each trip of the AGV regarding its position and operating status are collected alongside their respective contexts and stored. Evaluations and analyses appear on a dashboard. Operators can individually adjust the height of the AGV’s lift table for each station using the corresponding digital twin. Changes to the process or parameters can be implemented on-site or remotely. With these initial steps now implemented, all the experience that has been gathered can be used to implement the Plant 4.0 living lab.

The next step will involve Ascon Systems coupling the digital-twin-controlled demonstrator with the car manufacturer’s own digital ecosystem MO360. Remote, live-synced visualization and interaction then become possible, demonstrating the options and opportunities to increase both manufacturing flexibility and user friendliness through end-to-end digitalization.

* The project funding from the Federal Ministry for Economic Affairs and Climate Action is detailed in the grant guideline “Digitalization of Vehicle Manufacturers and Automotive Suppliers” as part of the funding framework “Investing in the Future for Vehicle Manufacturers and Automotive Suppliers” with the support of project sponsor VDI Technologiezentrum GmbH. The project’s funding code for Ascon Systems is 13IK022G.

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Our work with NVIDIA has entered a new phase. We joined the NVIDIA Inception program in August 2023. Now, NVIDIA has granted us the title of Solution Advisor: Consultant within its partner network.

For companies seeking to explore the economic and operational benefits of the industrial metaverse, this means several things. With our support, they can now take full advantage of everything the industrial metaverse has to offer while identifying and implementing breakthrough innovations. Imagine what it would be like if you could simply “scan in” an entire factory. What if you had everything you need for efficient brownfield planning including AI-powered tools. And you and your team could monitor, reconfigure, and control your factory —from anywhere in the world. All while linking real-time information from your shop floor to your ERP, an AI tool, or your maintenance processes, so you could reach a completely new level of transparency across your operations. And what if your staff had all the information available on a production machine right on their tablets, and could interact with the equipment from their device without needing experts for re-tooling or maintenance? This is what we help you achieve at your production facilities.

Achieve big goals faster and more cost efficiently

If you could express the industrial metaverse as a formula, it might look something like this: Industrial Metaverse = Task Automation + Transparency + Intuitive Operation. All you need is an idea of which goals you would like to achieve, or which processes you would like to (or must) change to maintain your competitive edge. Often, it’s not exactly clear what is realistic or possible. We give you the right methodology together with examples from your own industry of what has already been accomplished and what is being planned while guiding you past the hurdles and challenges that arise. You’ll discover how innovative technologies can reveal unforeseen opportunities at your factories and how to set the right goals and attain them.

Regarding execution, an agile approach has proven the most efficient. It’s important to first gather experience in projects with a manageable scope, quantify the benefits, and adjust as necessary for optimal results before rolling the solution out across the company and among suppliers. When a company implements digitalization and automation, it always means change. And any change process needs to be carefully planned, implemented, and supported.

Our team possesses state-of-the-art knowledge about process automation, OT, and IT, and crucially, how to facilitate and implement change. This way, your company gets the required support for everything from planning through execution for both production modernization and new plant construction. For an example, read about our case study for BMW in Dingolfing here.

Setting a course for the industrial metaverse

Everyone seems to have their own definition of the industrial metaverse. While some think of it as 3D visualizations or simulations, others take a broader view and define the industrial metaverse as a space in which the real, physical asset of your factory also exists as a virtual one in the form of a digital twin that is connected to its bricks-and-mortar counterpart. And both views are valid. Because the industrial metaverse is just a catch-all phrase that encompasses all of these possibilities. The most important thing to understand is that different technologies work together to provide data consistency and transparency in a manner that has never been possible before. Decisions on the real shop floor affect the digital twin, and vice versa. Disruptive innovations can be implemented without code.

The industrial metaverse allows you to capitalize on many new opportunities and secure a competitive advantage over your competition. We offer you support from the initial steps up to and including integration into the NVIDIA Omniverse. We would be delighted to hear about your specific needs.

For customers who are already working with us and NVIDIA, our new status as Solution Advisor: Consultant means that you now have even more ways to use technologies from the Omniverse, NVIDIA’s own metaverse platform. We give you direct access to innovations from the NVIDIA network, NVIDIA experts, the collective expertise of all the partner companies in the NVIDIA network around the globe, and we combine it all with our systematic approach and comprehensive knowledge of automation and IT.

Suggested Read: The Factory of the Future in the Industrial Metaverse: Utopia or Opportunity?

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