With digitalization in technical companies, the number of systems in which production-related information is created is increasing. The amounts of data are also becoming larger and more heterogeneous. Today, data is generated in a wide variety of systems: M-CAD, electrical and electronic CAD software, as well as product-relevant digital information in office documents, in the ERP system, in the CRM or support system.

Managing this data is complex because it has to be considered across the entire life cycle of a product. As part of integrative collaboration between all departments, it is also important that not everyone only works with their own data. However, the manual transfer of information from one system to the next is a constant source of error.

The term digitalization is often interpreted too briefly in this context.

Disruptive innovation

Revolution or overwhelmed by competitors?

Being just as innovative as a start-up at full speed while business operations are ongoing: German medium-sized companies in the technological environment still have difficulty with this balancing act. Refining technologies and pushing them to the top of the world – no one can easily beat German engineers when it comes to this. What is currently happening as part of digitalization is more than just technological development. It is a revolution in which many established companies have already been overwhelmed by a competitor who was still unknown until yesterday – keyword disruptive innovation.

Disruptive innovation does not come primarily through technological differentiation, but rather through the business model. It is precisely this characteristic that poses a particular challenge for digitalization in German medium-sized businesses, in mechanical engineering, in plant engineering or other industries. As an established company, you cannot simply throw away what you already have and devote yourself to new ideas without worry and with all your might. Rather, you have to take a two-pronged approach in order to secure innovative things economically: continue to use the existing model and transfer it at the same time.

But how can you be disruptive with yourself and at full speed? How can you explore new directions, unencumbered by existing obligations, with the utmost dynamism and the same enthusiasm as a start-up in Silicon Valley?
The most important factors in designing new business models are timing and management. It is not the “early bird” that catches the worm, but the one who is correctly positioned when the “early majority” of customers arrive, that is, the largest group of buyers who demand the new product or service.

PLM and Industry 4.0

Why PLM is the prerequisite for intelligent products

Viewed from the perspective of PDM/PLM systems, the basis for process control in Industry 4.0-oriented production is the complete management of product data.

“The efficient and effective management of this digital product model from development through sales, production and commissioning to customer use and ensuring the services associated with the product” – this has been referred to as the product life cycle since the beginning of the new millennium. Management or PLM. And increasingly, PLM includes not only the mechanical geometry data models, but also the logic of the electrical and electronic systems and the programs of the embedded software.

This management of product data is the basic requirement for modern, “intelligent” and networked products to fulfill their function and be successful on the global market. It is the basic requirement that production can then be organized in a “more intelligent” network. It is the basic requirement for Industry 4.0.” (Hechenberger theses of the Sendler Circle)

What is a digital business process?

In practice, you often find processes that only appear to be digital. However, a true digital business process is only characterized by the fact that operable information is available that can be further processed.

Today you have to look closely to distinguish false from genuine digital business processes. Just because there is no longer any paper does not mean that the information is digital. Rather, it is just “electronified”. The scanned invoice that a supplier emails to its customer is a typical example. The billing information contained therein is not digitally operable. But you need real digital information for a real digital business process.

To do this – in the case of the invoice – the image data must first be read out using optical character recognition, header and position data recognized and, ideally, compared with an underlying order in the ERP system. If the order and invoice values ​​match, a workflow is used that forwards the invoice data to financial accounting for payment – the classic dark booking without human intervention and a prime example of a true digital business process. This therefore characterizes: digitally operable information that is processed by machines and systems that are connected to each other for this purpose.
What applies to invoices in a commercial environment can be transferred to design and development, ie the information available in a Product Lifecycle Management System (PLM). In this case it concerns all data and processes that are related to product management. A change request for a product as a PDF created in the PLM software is not yet operable, in other words digitally processable information. Rather, the relevant information in the request “Change the following part in this way” must be available separately and linked to the associated component in the PLM system . Only then can connections be established. The mere fact that the individual change items are listed in the application does not allow for a completely digital assignment. And it’s not just the information about the change that has to be available digitally and linked to the change documentation. But also the task that arises from it.

If a digital business process is to be created in the PLM environment, it is not enough to send a task by email and attach the components in question as an attachment. Rather, the task must be assigned in the PLM software via a task file and each document is only available once. The change process in the PLM system then controls all product data and documents associated with the change, accompanied by the task file. A PLM system as a product data backbone is the prerequisite for such a change process, because it is directly related to product data that is created throughout the company. This is the only way to manage the change consistently from the complaint through change management to development or to create a digital information twin from a machine and life history file at the push of a button .

These two scenarios demonstrate what constitutes a true digital process. A company only operates end-to-end digitalization when it makes information from CAD, ERP and PLM digitally available and ensures that it can be used immediately by other systems. Information must therefore be able to be used in its digital form without human interaction and to trigger actions and downstream processes. This is then referred to as digital “impact management”. In order to properly operate digitalization in technical companies, you need a corresponding digital platform . A product data backbone represents such an information basis.

A company must create the necessary IT technical requirements for this. There are three areas that are essential for digitalization : the ERP system (with SCM, business intelligence and maintenance) for linking production, finance, sales and service, the office systems including intranet, portal and CRM system as well the PLM software for product development and management – ​​the Product Data Backbone .

Systems Engineering

The bridge between business models, product development and product management

The development of increasingly sophisticated mechatronic systems requires close collaboration between specialists from all disciplines involved. When designing a new product or fundamentally redesigning it, it often cannot and should not be recognized at the beginning exactly which function is being implemented using which technology. Rather, it is first important to describe the functionality of a product very precisely. This allows everyone involved in development, manufacturing and marketing to see what needs to be done. This is the job of systems engineering.

Systems engineering is the first phase of product lifecycle management. It also accompanies all subsequent phases in the PLM process. Systems engineering and product lifecycle management must therefore be closely related to each other. System-oriented design, detached from the form of implementation in mechanics, electrical systems or software, will become enormously important in the future and represents a central point of an Industry 4.0 strategy.

Products now have to be defined more closely by the business model. To do this, it is important to ensure a bridge between development in the respective departments and the business model. This bridge is systems engineering, which is to be applied as a higher-level concept. In the future, the proportion of software and electronics in products will increase and with it the market pressure to offer such product components. The shift in value proposition shares becomes the driver of systems engineering methods. Through their use, product cycles are shortened and the entire development is characterized by greater dynamics over the entire life cycle of the product.

Digital information twin

The tandem of digital twin and digital information twin

Machines and systems are becoming increasingly complex in their structure; The product share of electronics and software compared to pure mechanics is constantly increasing in view of digitalization and Industry 4.0. If the product information of all components of a system over its entire life cycle is brought together in a product and document lifecycle management system (PDM/PLM software), a digital information twin of the system delivered to the customer is created.

Computer-aided models of objects on which virtual simulations can be carried out have been making a name for themselves for some time under the heading of digital twins. Digitalization is discussed in mechanical engineering and plant engineering as a concept in connection with Industry 4.0. As an image of a process, a product and a service, the digital twin connects the real and the virtual world. Sensors installed on a real object transmit their data to the digital twin, which processes and evaluates it. Monitoring systems makes it easier to anticipate errors and prevent problems before they occur.

In everyday business life, complete digital twins of this type have not yet grown beyond their initial stage due to the technical requirements associated with them. Currently, individual parts of the system are monitored remotely, for example to ensure predictive maintenance. The technical basis for a digital twin is a consistent digital platform that links product-relevant documents and information and makes them available throughout the entire product life cycle.

Machine and life history files as a form of the digital twin

What is easier to implement instead of a completely digital image is a “digital information twin”. This is a life history file of a product/system. It is based on the technical structure of all elements of the system and combines all related information that is relevant for product development and product management in a central location. Product data and documents flow together in the life cycle file over the entire life cycle of the system. This information about a product is brought together customer-related or project-specific and represents the delivered machine as a digital information twin.

For example, in order to be able to assess recurring faults in a system in terms of product quality, it must be clearly documented what each individual machine looks like at the customer’s. Which pump and motor were installed? What changes has this engine already undergone? Which software version is in the drive control? Where is the corresponding description? Based on the complete digital documentation, which can be accessed at the push of a button, the conclusions drawn from malfunctions can be better assessed. The manufacturer can also automatically create documentation, map original requirements or analyze the impact of change requests.