• "Operating System" for versatile production plants

    BaSys 4.0 — Basic System Industry 4.0

As already frequently recognised, the economy is on the threshold of a fourth industrial revolution. Against the backdrop of economic challenges, particularly those in Germany, the aim of the digitisation in the manufacturing sector is to ensure that manufacturing companies can successfully adapt to the ever greater volatility of the markets, new global competition, rising version numbers and increasingly customised products up to batch size 1.

The adaptability required for the fourth industrial revolution is the key distinguishing feature of this technology. However, adaptability must not be confused with the production flexibility that is already being realised today. A flexible production plant means production lines that can be adapted in a specific area of flexibility; however, flexibility cannot be implemented efficiently. In contrast, versatile plants can be adapted to entirely new products extremely cost effectively, even if these products are not considered during the planning of the plant. The realisation of this adaptability requires new methods and technologies that enable production process to be dynamic.

Developing products and plants in parallel

Central scientific and technical approaches of BaSys 4.0
Central scientific and technical approaches of BaSys 4.0

Another aspect is the parallelisation of product and plant development. Developing in parallel is, in part, already state of the art in mass production and even the automotive industry, but the standards need to be raised to a much higher level. It must be possible to take the flexibility and versatility of "by design" into consideration on both sides.

The gradual implementation of the concepts will see Industry 4.0 increase the penetration of production processes with IT technologies. More and more people have to interact with software systems. The efficiency of order processing is (must be) further enhanced by mobile solutions in the production environment.

Optimal interoperability thanks to standardised communication

The automated communication capabilities of machines and plants, but also business partners, are a critical factor in the success of implementing Smart Factory concepts. This communication must be based on standards, both in terms of content and protocols ("All-IP"). Only in this way can a satisfactory level of interoperability be achieved.

A wide range of initiatives have been developed, not least as a result of the activities taking place around Industry 4.0. One example is ERP 2020 as carried out by the VDMA.

The focus is on the basic requirements for ERP systems and MES applications, such as connectivity, enhanced usability, support of mobile processes and also significantly improved agility of systems and business relations.

User-friendly interface

Ultimately, Industry 4.0 requires integrated software solutions (in the field of production and logistics) that provide all existing data and information in a user-friendly interface. The resulting data is visualised and used for the continuous optimisation of production, such as sequences, drift compensation etc., and for product improvement. The obvious fields of action and objectives include increasing the availability of production systems and reducing the cost of maintenance and repair work, stable production processes and consistently high product quality as well as reducing the costs associated with failure, in addition to punctual deliveries in the right quantity.

Self-learning systems and digital twins

These objectives can be achieved by measures in the field of predictive maintenance, machine data acquisition and continuous monitoring of production and quality data. Completely new approaches such as visual computing enable correlations in the data base to be identified and self-learning systems to be introduced to support decision-making or even automated initiation of necessary activities.

PSI Automotive & Industry has the task of mapping this dynamisation of production in the higher layers of production planning and control processes.

Simulations and sequencing act as "digital twins" as an image of the current plant configuration and the current and future order situation — as a timeline containing all order, plant and even product-related information. The engineering of products is not only limited to geometric and other product characteristics, but it also provides the configuration information needed to make adjustments to the plant. This simultaneous product and production engineering requires the functionality of modern-day MES or PLM systems to be expanded. Comprehensive networking of suppliers and producers Requirements for the comprehensive networking of suppliers and producers (connected world) can be derived from the demands for networking business partners in value-added networks.

Exchanging order-specific information is no longer enough — the availability of certain capabilities of a plant or an entire production system also needs to be factored in. Only by having this information is it possible to automate a technology comparison between required and available capabilities. The data models in the information layer must therefore be adapted to the necessarily systems and suppliers across the board. The variety of existing standards, such as for describing products and resources, must be applied consistently.

Event-driven production control

The expected increase in the flexibility and autonomy of future production systems is making it increasingly difficult to comply with defined processes and to describe the diversity of these processes at all. The traditional process analysis and subsequent modelling is being replaced by an event-driven production control in the short and medium term. In this case, it is less about processes described in minute detail and more on rules, possible events and alternatives. Switching configurations or modifying a product mix may then actually be the rule and not the exception. Today's order processing systems must take this into account.

Ultimately, this is about the departure from the deterministic, multi-stage planning and organisation of work content to adaptive and customisable algorithms. The adaptability of production systems increasingly requires simulation-based planning and organisation systems.

Customised products with their own identity and communication capability must be mapped in the order processing systems — be it with regard to production or the after-sales service. Depending on the application, it must be possible to monitor or even manage these IT systems in the field or within the plant itself.

Bringing users and providers together

New requirements for software solutions are expected to emerge in the industrial environment alongside the progressive implementation of Industry 4.0 concepts. It will be important for users and providers of solutions to come together and jointly develop pioneering solutions based on use cases, leaving behind the "old" world of production control with its restrictions, fixed constraints and Excel tables. To make this change possible, old paradigms and current system limits or concepts need to be disregarded and an agile environment made up of hardware, software and people to be created in the digital factory.


PSI Automotive & Industry GmbH
Karl Tröger
Business Development Manager


Collaborative project BaSys 4.0

A multitude of structural, functional and non-functional requirements have arisen from these challenges. In the same way as basic platforms used in other domains to simplify and standardise the development of complex systems, a basic platform is needed as a reference to stimulate and support the practical implementation of the fourth industrial revolution.

This "AUTOSAR for Industry 4.0" is defined based on existing technologies and necessary standards, exchange formats, basic services and interfaces that support efficient networking and conversion of production plants. The intention is to realise a service-based reference architecture that defines the limits of an Industry 4.0 system yet is flexible enough to unite the needs of different industry sectors.

Integrating an Industry 4.0 component

In addition, further profound changes to the order processing systems (ERP and MES) are expected. It is about the integration of another IT system (which was scarcely or not at all considered previously) in these software systems: the Industry 4.0 component. This "smart product" has communication skills and capabilities for data processing. It may be a product in use (in the field) or a stationary system in the production. Data is supplied continuously and must be considered by the order processing systems in a different context or the data must first be placed in a context (semantics, ontology).

These perspectives relate to plants, orders and products, and the result is order data and usage data. However, the communication capabilities of the smart products have no value if the assets are not clearly identified. As a result, all types of assets must be reflected in all possible forms in the order processing systems.

Basic System Industry 4.0

1 July, 2016 saw the launch of the German Federal Ministry of Education and Research (BMBF) funded collaborative project "Basic System Industry 4.0" (BaSys 4.0).

With 15 partners from industry and research, the project (under the coordination of the Fraunhofer IESE) has EUR 12 million in funding and runs for three years.


PSI: Standardised coupling from the sensor through to the ERP

The findings are validated by various demonstrators. PSI Automotive & Industry has the task of mapping this dynamisation of production in the higher layers of production planning and control processes. A key element of this mapping is coupling with automation technology and the resulting base system via a standardised gateway and the use of digital twins in the ERP and MES environment. The necessary extensions are primarily implemented using PSI solution architecture.

Photos (top to bottom): Thinkstock/microolga, PSI Automotive & Industry (2), Fraunhofer-Institut für Experimentelles Software Engineering IES