Proxy Task Anomaly Detection with Asset Administration Shell Integration for Predictive Maintenance

The concept of the Digital Twin (DT) and its implementation as Asset Administration Shell (AAS) is one of the key technologies for implementing Industry 4.0. By utilizing the AAS, use cases can be implemented with high interoperability. These use cases include optimizations and improvements of physical systems, like predictive maintenance or other artificial intelligence applications. For these use cases, historical data is key. However, there exists no guidance on how to handle historical data with the AAS. Furthermore, no integrated architecture exists that enables seamless storage and retrieval of historical data using the unified AAS meta-model and interface. Thus, we bridge this gap between use case and unified implementation by presenting multiple blueprints for data storage and retrieval motivated by use cases from Industry 4.0, healthcare, and civil construction. These data storage blueprints range from a mandatory change in the AAS infrastructure to augmentations of the existing AAS concepts. Furthermore, we showcase how the data model of the AAS can be utilized for a unified retrieval of historical data. In consequence, practitioners can quickly realize use cases that require historical data by tailoring and implementing the presented blueprints. Additionally, researchers can extend the presented guidance to further use cases, possibly from other domains.

Asset Administration Shell - manufacturing processes energy optimization

Digital twins are a critical backbone technology for modern manufacturing and Industrie 4.0 (I4.0). The Asset Administration Shell (AAS) is becoming a popular foundation for modeling digital twins. Asset Administration Shells come in three successive levels of enhancement, also referred to as AAS (communication) types, though there is no common definition for these types. We conducted a systematic mapping study to find out how they are defined in the literature. As the analysis for type 2 AAS and type 3 AAS remains without direct results, we devised a novel classification schema from our findings via portfolio analysis. This schema can provide a foundation for the precise classification of AAS to guide researchers and practitioners in modeling digital twins.

Major benefit of Digital Twins lies in collaboration across value added chains based on semantic interoperability. The concept of the Asset Administration Shell (AAS) enables sharing of semantically enriched information in Industrie 4.0 application scenarios and beyond. Nevertheless, a technical infrastructure is needed that can ensure data sovereignty, i.e. integrity, confidentiality and availability of information shared across business partners in value added chains. This paper presents the current state of work on such a technical infrastructure for Asset Administration Shells (AAS). It combines three technologies: a blockchain books who changed an AAS and when, a peer-to-peer (P2P) distributed file system encrypts and stores each version of an AAS and a version-control system tracks changes to an AAS in detail. An exemplary value added chain is defined, which will be implemented in a demonstrator. This demonstrator will be used to evaluate and improve the proposed technical infrastructure for collaboration of AAS across value added chains.

Industrie 4.0 maps the digital twin as the Asset Administration Shell. To develop this digital twin, the Asset Administration Shell meta-model is used. A developer needs high-quality libraries in their programming languages to build the Asset Administration Shell in efficient and ergonomic way. The existing representations of the meta-model are inconvenient for moving from the specification to realizations in software development. This leads to many, often manual, re-implementations of the Asset Administration Shell in each programming language. We present an approach to automatically generate libraries based on the intermediate representation of the meta-model. The approach allows for practical and simple development process of Industrie 4.0 components, and scales across programming environments and future changes in the meta-model.

Industry 4.0 presents considerable challenges in data unification. The Asset Administration Shell is a key concept introduced by Reference Architecture Model Industry 4.0 to enable the storage and communication of data between assets. The current conceptualization of the Asset Administration Shell exhibits limitations when it comes to representing digital data. It lacks an effective methodology for categorizing and defining existing data as an asset and this can potentially hinder the full utilization of digital data as an integral asset within the Industry 4.0 infrastructure. This research proposes an asset model inspired from Asset Administration Shell to better represent the ever-evolving digital data as a valuable asset within the Industry 4.0 framework.

The factory operators lack 3GPP network knowledge and there is a requirement for industrial 5G networks to enable zero-touch automation which will translate factory business expectations to technical expectations. Integrating the intent-based operations is a key approach to implement intelligent network management system which can automatically verify, deploy, configure and optimize itself to meet the targets and goals. However, there is still a need for human intervention (e.g., factory operators) to place the intents. In this paper, we propose a solution based on Asset Administration Shell (AAS) to implement digital twins of the 5G network and 5G-capable factory devices. The proposed solution approach implements necessary submodels in AAS instances, so that the factory devices can place their own intents with minimized manual intervention. This framework is implemented and demonstrated with an automation system in conjunction with a 5G emulation environment.

Dynamic simulation models are widely utilized to evaluate complex technical components and systems like electric drives or machines. They can support the development process of a production machine by avoiding an inadequate layout of components or an erroneous control design. However, the effort for building them is often too high for this purpose (lot size one). An automated model generation can be utilized to overcome the gap between efforts and advantages of dynamic simulations. This contribution presents an approach for simplifying the dynamic model generation of production machines by using the so-called Asset Administration Shell defined by the initiative Platform Industrie 4.0. The Asset Administration Shell was developed to aggregate all data necessary for maintaining the product across its life cycle. This includes component data and models as well as structural information about a machine. The generation process is performed by using the common FMI standard and a two-step procedure which allows the linkage of different simulation tools. The model generation is demonstrated by an example layout of a machine's internal direct current grid.

Small batch sizes and individualized products are managed with the concept of Cyber-Physical Production Systems (CPPS), enabling flexibility through interchangeable constellations, but increases complexity, especially when dealing with dependencies between decentralized subsystems. To increase the resilience and self-healing capabilities, greater automation of fault detection and diagnosis (FDD) is a key factor. It is a challenge to gather knowledge about faults, as these rarely occur compared to normal behavior. The flexibility in skill-based production systems makes this situation even more difficult. To overcome this challenge, data and knowledge about faults and their context from several Cyber-Physical Production Modules is used, which leads to federated knowledge databases. The knowledge databases are modeled in the Capability-Skill-Service-Fault-Symptom model (CSSFS model). To achieve the goal of high availability, resilience and autonomy of CPPS, automated decision-making for FDD using CSSFS applications is required. Therefore, automatic communication between FDD components is necessary. Therefore, focus of this paper is on the development of a communication scheme, which models participants using Asset Administration Shells and the I4.0 Language to model their interactions to enable automated communication and makes distributed knowledge accessible. To ensure decentralized control of these services, functionalities from several factory levels are encapsulated by Multi-Agent Systems (MAS) that follow a holonic structure.

Plug-and-Produce based on Standardized Industrie 4.0 Asset Administration Shells – Use Cases, Architecture, Prototype, and Standardization Gaps

Due to their flexible functionality and variable system design, convertible production environments exhibit a high degree of complexity. The complexity arises, among other things, from the heterogeneity of the components used, their scalability, their interaction within the systems, and the cross-system communication. Software solutions in the environment of automation systems, among others, have a great influence on the flexibility and complexity of the system. For their use, the cross-system description of plants with their components including the associated capabilities and a preferably standardized coordination of resources is desirable. One possibility of description is offered by the Asset Administration Shell (AAS) as a digital representative of resources. For the synchronization of plants and their segments, control components are suitable in the environment of AAS. In current industrial environments, solutions with PackML are established at the level of industrial controllers. They offer a possibility of functional interoperability and synchronization of plant segments. In the paper, the addition of the PackML approach to synchronization at the control level and the provision of the relevant information at the AAS level is shown.

Within the context of Industry 4.0, future production systems are expected to support mass customization up to lot size one. In order to realize the individual production processes, a changeable and consistent integration of assets from different manufacturers is required. Therefore, the concept of I4.0 components was developed. Every I4.0 component provides a so-called asset administration shell, i.e. a standardized virtual representation of its capabilities. This paper focuses on real-time I4.0 components that require a deterministic communication with bounded low-latency in-between. In contrast to non-real-time I4.0 components, Ethernet (IEEE 802.3) is enhanced by the new real-time communication technology Time-Sensitive Networking (TSN, IEEE 802.1). The basic configuration of TSN connections within the asset administration shell was already addressed by previous work. In this work, we present the configuration of application layer protocols using the example of OPC UA Publish/Subscribe (PubSub). More precisely, we outline the underlying concept and define additional submodels for the asset administration shell of real-time I4.0 components. Finally, we discuss the advantages of the presented approach in terms of changeability.

Gaining value out of data provided in industrial application in a standardized Industrie 4.0 compliant way is a challenging and time-extensive task. Not only does the data need to be integrated into a data platform, it also needs to be described and integrated in an appropriate way, that allows a standardized processing for its value-added services. One way to achieve this, lies in the use of OPC UA and the asset administration shell. Together they can implement an Industrie 4.0 Component as the standardized service for tailored data integration and usage. Data in OPC UA is available in different levels of abstraction, both in terms of the data and its description. Rarely is the asset administration shell (AAS) considered in this context. This paper will introduce a first approach to harmonize OPC UA and the AAS in an I4.0 compliant Aggregation Server. The server is able to aggregate information models based on the current meta model mapping of the AAS, regardless of whether the base servers implement this or not. Moreover the aggregated server can route OPC UA services down to the base servers and is managing itself in case of discovery and information aggregation. This approach can be used as the standalone interface for data integration in respective data platforms.

Energy management systems are an important tool for increasing the energy efficiency of buildings. However, the widespread availability of such systems is offset by the complexity and high costs of implementation, as well as a lack of data. These obstacles can be addressed by using standardized digital twins of technical components. In combination with homogeneous semantics and standardized interfaces as uniform access points to information, the implementation of an energy management system can be simplified. However, given the large number of different manufacturers of the technical components, an agreement on a common semantic standard of the information elements seems unlikely. Studies show that methods from the field of natural language processing can be used to process heterogeneous semantics. An agreement on a common vocabulary is no longer necessary. Instead, different semantics can be used and matched to a target vocabulary. The implementation of such a matching service reduces the configuration effort for the implementation of an energy management system. Providing an Industrie 4.0 interface that contains the semantic matching service within the components allows the interaction between them and an energy management system. A prerequisite for automated interaction is the availability of information in a uniform structure in the form of an information model. This paper presents the design of an Industrie 4.0 asset administration shell and initial submodels for an energy management system. Additionally, an Industrie 4.0 interface for the semantic matching service is implemented in a prototypical application of an energy management system. This implementation demonstrates how the configuration effort of such a system can be reduced by semantic matching.

The wiring harness is one of the most expensive components of the automobile. It is still a custom-made product despite the high-volume production in the automotive industry. However, various trends, such as increasing fragility of supply chains and functional safety demands for autonomous driving are demanding the automation of the value creation processes. But in mass customisation, automation needs the digitalisation of all information flows. Machines and processes must be able to automatically gather all required information. In the wiring harness industry, much of the information has been geared toward processing by humans and has hardly been digitised at all. One of the foundations for Industry 4.0-oriented automation is ergo the existence of complete digital information of each wiring harness. A digital twin of the wiring harness is required. The Asset Administration Shell (AAS) is the technical concept for transparently interoperating with the digital twin. The project “Asset Administration Shell for the Wiring Harness” or in German (Verwaltungsschale für den Leitungssatz - VWS4LS) creates the first complete digital description of the wiring harness based on the AAS. As a result, all actors in the value network can access complete and consistent data (“single point of truth”), enrich it, and control its application through authorisations. To achieve this goal, a consortium from all levels of the value network was assembled for VWS4LS starting with the OEM, through the suppliers at the various levels of the value chain, and to the software suppliers and machine manufacturers. This publication presents the project and its initial results.