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“The factory of the future will be data-driven – or it will no longer be competitive”

Published: · Last updated: · 15 min reading time

What characterizes the factory of the future? How can smart manufacturing succeed? What should be in the digital toolbox for the shop floor? A conversation with Dr. Ullrich Ochs, co-managing director of FORCAM GmbH and ENISCO by FORCAM GmbH. He holds a doctorate in physics and is responsible for technology and development.

The factory of the future – what does it look like, what characterizes it?

Dr. Ullrich Ochs: The factory of the future will be largely digital, i.e. data-driven. It is characterized by digital networking of parts, products and processes. The key term here is Industrial Internet of Things (IIoT). In this context, IIoT, digitization and data management are not an end in themselves but represent a large and growing toolbox of software solutions with which manufacturing companies can achieve specific goals faster and easier. The ultimate goal of every company is to secure its competitiveness. To do this, it must be able to operate efficiently and cost-consciously, act flexibly and produce sustainably. Only digitally networked manufacturing can optimally support precisely these goals – profitability, resilience and sustainability.

Why is this only possible digitally?

Because today’s markets demand one thing above all: speed with consistent quality and reliable delivery. In addition, customers want product ranges that offer a greater number of variants and innovations as often as possible. Product life cycles are shortening accordingly. These market requirements necessitate ever faster adaptation of production processes, i.e. adaptation to the cardiovascular system of the manufacturing industry. A company’s factory or factory network must be able to operate with corresponding flexibility. This flexibility in complex, often global production processes can only be achieved through digital technologies. Only through digital technologies can competitive production be organized today – efficient, sustainable, flexible and open to innovation.

What does this mean for factory IT service providers like ENISCO and FORCAM?

For factory IT service providers like our group, this means that they must deliver solutions for digital shop floor management with the greatest possible measurable customer benefits – in terms of transparency, in terms of efficiency, in terms of flexibility.

Ideally, digital shop floor management represents a closed problem-solving loop. In it, fault messages on machines are automatically triggered in real-time or by employees, controlled by key figures. Employees are supported in analyzing and solving malfunctions. Finally, the success of each measure can be verified on the basis of objective metrics – this makes it possible to optimize processes on an ongoing basis.

The digital toolbox for this must be ‘best-in-class’ so that companies can take advantage of as many of the desired possibilities of the Internet as possible.

What belongs in a ‘best-in-class’ toolbox?

Companies want speed through flexibility. Flexible production means that processes and workflows can be adapted smoothly without having to reprogram the software. This flexibility requires three tools to be orchestrated together: Connectivity, digital twin and interoperability.

Connectivity is the master key to data-driven production with real-time analytics. Leverageable electronic data only exists when the wide variety of machines and sensors, i.e., the shopfloor, are connected and networked with the corporate planning of the top-floor, from which the orders come. All signals are recorded, harmonized, and processed in such a way that they are available as information in further systems such as a Manufacturing Execution System – MES.

With digital twins, i.e. digital images of machine or production states on the computer, users can analyze virtually and optimize in real terms. This makes resource efficiency possible at all levels – from material and media consumption at the individual machine to unit cost and total cost optimization at the controlling level of the company.
And thirdly, interoperability, the seamless interaction of all IT systems. This requires a free flow of data, which is made possible by open interfaces such as an Open API or standards such as OPC/UA and MQTT.

A concrete example please …

There is a good example in the automotive sector: A supplier group wants to have CO2-neutral production by 2035. The subsidiaries are responsible for the implementation. One of our customers is one of these subsidiaries. The factory team there has digitally connected the most important machines to achieve greater energy efficiency.

To do this, the team uses software to correlate the performance data of the machines with their energy data so that they can use the most energy effficient machines for each order. Energy consumption has thus been reduced by more than 20 percent in recent years, while processes have remained the same and production volumes have increased.

What does all this mean for the factory IT of the future?

The factory IT of the future has a uniform data source for all applications. A central platform brings together signals from all internal and external sources, regardless of transmission paths and protocols. The signals are harmonized and brought into a consistent semantic data model. This represents the single source of the truth, the unified data center that feeds all existing and future IT solutions with the information they need.

This makes real-time evaluations possible at all levels for all functions –

  • Performance analyses of individual machines for the workers,
  • Dashboards with historical and current overviews for shift and production managers,
  • Predictive maintenance through artificial intelligence and machine learning for maintenance managers,
  • Energy and resource consumption for ESG managers,
  • Unit cost trends for controllers,
  • Workflow, service and quality analytics for CRM and SCM managers

FORCAM and ENISCO are pioneers in data-driven manufacturing solutions and digital shop floor management. Today, the market has many providers, both large and small. What makes our group of companies different?

It’s true: The increasing focus on digitalization in production is leading to more companies focusing on this topic area and launching products on the market. However, the digitization of the shop floor did not just start recently, and we at FORCAM and ENISCO have been active in this field for around 25 years. Together, our experts bring many decades of experience in digital manufacturing control and digital shop floor management. This know-how can be found in our software products as well as in our consulting services. Our teams not only understand IT, but also OT – operational technology.

This many years of practical experience distinguishes us from many market competitors: We are the experts even for complex shop floor requirements, i.e. of productions with many different product variants. With our solutions and our consulting, we contribute to the flexibility that the factory of the future needs.

MES versus IIoT: FORCAM and ENISCO belong to the market of MES providers. At the same time, the industrial IoT is considered the concept of the future. How do MES and IIoT fit together?

MES and IIoT systems can complement each other very effectively. After all, both solution worlds have a common goal: to help companies produce more efficiently in manufacturing. Both solution worlds are about collecting and processing data and drawing analyses and conclusions from it.

The VDMA has published a white paper on this subject, to which we were able to contribute. It summarizes that MES remains the ‘single point of truth’ across the entire value chain on the shop floor. Both the ERP (Enterprise Resource Planning) planning level on the one hand and the automation level with IIoT solutions on the other can be integrated in a modern MES system.

So MES and IIoT systems fulfill different functions?

Yes, IIoT systems provide a view of real-time technical data from individual machines, plants or processes. Technical data such as temperatures, speeds, consumption, etc. are recorded. Modern MES, on the other hand, provide a 360-degree view of all relevant data, processes and connected systems. And this across all locations.

MES record technical data in such a way that they can also be used at a higher business management level. For example, they put the production data from the machine level in context with the respective order. In this way, the MES data also enable important conclusions to be drawn at the ERP planning level, for example on energy and resource efficiency.

Even in the MES world, the concept of a central data platform prevails today. Why?

In the vast majority of companies, the world of discrete manufacturing is highly complex and geared to individual parameters. A modern IT architecture in manufacturing therefore requires above all the ability to integrate new solutions seamlessly like Lego building blocks. An existing architecture at the customer’s site should be supplemented, not jeopardized. Platform concepts can best solve this requirement.

Our MES platform concept for discrete manufacturing is integrative and open to interfaces, modularly expandable and suitable for all manufacturing types. McKinsey has defined three factory types according to the number of product variants manufactured. Our solutions support both made-to-order and single-item production with the most variants as well as customized mass production or large-scale production with less product variance. For this reason, our customers also come from a wide range of manufacturers – from automotive and aerospace to mechanical and plant engineering, medical technology, industrial components and warehouse logistics.

Keyword connectivity: How important is the competence of machine connectivity still in times of web-based tools and new standards like low- and no-code solutions?

Connectivity plays a central role: If no data is provided, no data can be processed – neither with classic methods nor with modern, more flexible approaches such as low- or no-code.

A distinction must be made here: Modern machines simplify communication because they work with established standards such as OPC/UA. However, many manufacturing companies also have machines that either do not provide any network communication at all or can only communicate with proprietary protocols of the machine manufacturer. Since these machines often have to run for decades and will not be replaced by modern machines any time soon, a concept for the comprehensive digitization of production is needed in order to be able to integrate such existing machines into a smart factory. With our Edge solution, we offer an approach that can integrate existing machines into the world of digitization in addition to modern machines with OPC-UA.

Keyword Digital Twin, the virtual image of a production on the computer: What exactly is behind this?

The digital twin is an approach to virtually represent a real, i.e. physically structured production in a model in the computer. The complete production structure with its various hierarchical levels, from the plant to the hall to the subplants and lines down to the individual machine, is mapped in a model. This means that at each level of the hierarchy there are model elements, each of which has a counterpart in the physical world.

The production data are each assigned to a model element of the digital twin. This structures the data and gives it meaning. For example, the information “Production running” for a machine says something about the status of the individual machine, but for a production line it says something about a group of machines that work together in the line to manufacture the products.

The digital twin is thus the heart of the digital factory?

I would say it is the heart of continuous improvement in the factory of the future. Yet the digital twin is basically nothing new. As early as the 1990s, software was developed that worked closely with machines to solve a problem in the real world. For example, logistics software has an image of the warehouse in its database and can thus tell at any time which pallet is in which location in the high-bay warehouse. Or a SCADA system has information about the existing devices, sensors and actuators in the master data and can thus log faults with reference to the source and display the devices in a graphical representation, visualizing the status using suitable colors.

What do FORCAM and ENISCO offer in terms of digital twins?

Our products also map the aspects of physical production plants in order to be able to display, evaluate and use the data according to its significance. We deliver two things in particular: firstly, a Digital Machine Twin, which maps the performance states of a machine or plant for a factory team, and secondly, a Digital Production Twin, in which the orders from the ERP level are included and allow higher-level analyses.

However, I want to point out one shortcoming in the world of Digital Twins: There are very many different models. This is because each manufacturer of shop floor software maps the aspects of physical production necessary for the functionality of its software in its proprietary computer model. This means that each manufacturer has its own digital twin, and the digital twins of different manufacturers are usually not compatible with each other.

This is precisely the problem addressed by cross-manufacturer initiatives such as the Industrial Digital Twin Association, whose goal is a common data model for the digital twin. The IDTA, in turn, cooperates with the Open Industry 40 Alliance, of which we are also a member.

So is interoperability just a concept in the distant future?

No, interoperability is available. Our approach is to offer the greatest possible interoperability and modularity of IT solutions on one platform, through a variety of interface solutions – from plug-ins for connecting all internationally common factory machines to OPC/UA, MQTT and KAFKA to Open API and SAP adapters.

Further away, in my estimation, is an international standard, the IIoT master key, so to speak. However, if there were a standard to which all providers and users adhered, then interoperability across industries and companies would be achieved.

Is artificial intelligence – AI – the new magic wand that is revolutionizing production?

AI apps are very helpful in recognizing patterns. For example, certain simple diligence tasks can be handled much better with AI than before. Examples are the automated recognition of good or bad parts or incorrect finishes such as painting errors. But I don’t yet see a revolution like the overall control of a manufacturing operation by AI. That would probably only work in factories that are empty of people.

So humans need to change, not AI need to get better?

As a rule, broad acceptance must first be established for AI solutions. Otherwise, there will always be discussions about what makes sense. People are used to optimizing specific things in their areas, such as workplaces or certain processes. Only an AI can grasp the complexity of an entire production process.

The key point, however, is that an AI has to be trained. This can happen in two ways: Either the AI learns on the computer in simulations, or the AI learns directly in reality. The latter, however, would lead to a great deal of chaos in a production process – after all, an AI must also first make one or two wrong decisions in order to learn a correct decision. Considering that every factory has its own individual circumstances, I think that the time when AI systems in reality control manufacturing processes in their entirety and thus revolutionize them is still a long way off.

Which MES solutions fulfill core requirements and should definitely be used by companies?

A digital transformation in the factory should be organized as an evolutionary process in partial steps, if possible. In each sub-step, the aim is first to empower employees, then to gather experience and optimize it in pilot projects, and then to roll it out.

Companies can be guided by four important functions that MES apps must fulfill:

  • first, transparency – made possible by connectivity with machine and shop floor data collection.
  • second, process and quality assurance through visualization, analysis and reporting – this is enabled by MES for overall equipment effectiveness OEE, energy monitoring and traceability,
  • third, planning – with detailed planning and digital planning board,
  • fourth, control – with document management and ticket system.

We offer all these apps on a modular basis. In addition, our specialty is the E-MES solution. This is a complete production control system with which we support customers in making manufacturing and logistics processes more intelligent, efficient, and flexible. For example, they use E-MES to control entire paint shops or high-bay warehouses.

Production is also one element in an entire supply chain. What must MES be able to do in terms of supply chain management?

The logistics transfer to warehousing or delivery takes place on the shop floor. This is where, for example, modern blockchain technologies come into play, i.e. the forgery-proof transfer of products from production to the subsequent areas of the supply chain. An MES platform solution should be open to cooperate with IT systems outside of the actual production.

From code to customer: How important is the topic of user interface today, i.e. the greatest possible user friendliness and satisfaction?

In the century of the cell phone, user-friendliness is also a top priority on the shop floor. After all, it’s all about the lasting empowerment of factory teams. User interfaces should be as self-explanatory, user-friendly and simple as possible. Suitable user interfaces must be easy to configure, either because an MES offers this itself, or through low-code solutions that are easy to integrate. The choice is large today.

On-premise, edge, cloud – what do enterprises really need?

This is a highly sensitive topic. After all, it’s about building and maintaining a highly available IT infrastructure. The options for providing data are many and varied. The cloud certainly offers many advantages in terms of scaling, service and security, with established providers offering a variety of options including public, private and hosted private cloud, for example.

At the same time, in my view, it is becoming apparent that an increasing number of companies prefer factory or near-factory data storage for some tasks, i.e. on-premise or at the edge. The main reason is that any cloud deployment ultimately relies on the Internet, unless the infrastructure is installed on the factory floor itself. With the Internet, however, disruptions can always occur – for example, due to the famous excavator outside the factory gate. Production and IT managers should therefore always analyze exactly which applications should run on-premise and which in the cloud.

In this respect, the future is likely to lie in hybrid deployment scenarios, i.e. in individual combinations of on-premise, edge, public and private cloud strategies. This is understandable. After all, it is the IT architecture and data provision that determine success or failure on the market today.

With our open MES platform approach, we are also well prepared for hybrid deployment scenarios.