Knowledge-Data Driven for Cyber-Physical Production Systems in the Aerospace Industry: Current Issues and Emergent Technologies

Rapid technology advances and increasing digitalization bring new opportunities but also put new challenges to modern production systems. Industrial agent concepts and technologies can be used to address the needs of modern Cyber-Physical Production Systems (CPPS). To do so, their interplay, especially in industrial settings, needs to be better understood and assessed. Key directions for investigations that are relevant for industrial agent based CPPS are analyzed in this work, mainly the design patterns, interfaces between agents and CPPS, metrics to evaluate the quality of agent based CPPS, and distributed intelligence implemented in or by agents. Although efforts exist both in agent and CPPS domains, their amalgamation still has several aspects that are under-investigated, especially when considering large-scale systems of CPPS, and the proposed four directions discussed in this work, seem promising to address several of the key underlying challenges.

Traditional manufacturing and production systems are in the throes of a digital transformation. By blending the real and virtual production worlds, it is now possible to connect all parts of the production process: devices, products, processes, systems and people, in an informational ecosystem. This paper examines the underpinning issues that characterise the challenges for transforming traditional manufacturing to a Cyber Physical Production System. Such a transformation constitutes a major endeavour for requirements engineers who need to identify, specify and analyse the effects that a multitude of assets need to be transformed towards a network of collaborating devices, information sources, and human actors. The paper reports on the e-CORE approach which is a systematic, analytical and traceable approach to Requirements Engineering and demonstrates its utility using an industrial-size application. It also considers the effect of Cyber Physical Production Systems on future approaches to requirements in dealing with the dynamic nature of such systems.

The role of Industrial Resources in Reconfigurable Aerospace Production Systems: A Preliminary Literature Review

The heterogeneity of the components of a Cyber-Physical Production System in addition to the high decentralization and autonomy required in Industry 4.0, introduces new levels of engineering complexity and dynamism that classical reductionists approaches are not able to solve. Within this context, novel solutions that rely on complexity sciences seem to be a good alternative to cope with these underline challenges. In this context, this paper presents a conceptual framework of complexity theory, self-organization and emergence and its subsequent relation to cyber manufacturing systems. Such analysis shows very promising ideas in the further development of complex, robust, adaptive and at least partial autonomous manufacturing systems.

In concert with advances in information and communication technology and their application to manufacturing environments, physical entities in factories are acquiring more intelligence via integration with cyber systems. This integration brings about Cyber-Physical Production Systems and leads to smart manufacturing, the next generation manufacturing paradigm. In the new paradigm, high levels of agility, flexibility, and real-time control make it possible to keep the system running efficiently and self-organized. At the same time, however, it becomes difficult in a self-organized and decentralized system to capture the system's status, evaluate the system's performance, and predict the system's future events. In this article, we suggest improvements to smart manufacturing systems where the intelligence from smart entities could be fully utilized without losing system control. To achieve this goal, a solution for integrating schedule-driven production (push systems) and event-driven production (pull systems) is proposed to optimize both material flow and information flow for manufacturing operations. For each entity in a smart manufacturing system, details of decision making are encapsulated and its status is exposed. The status-based decisions filter out unimportant information and make smart manufacturing systems loosely-coupled and predictable. A simulation case study based on Devices Profile for Web Services [1] is used to illustrate the effectiveness of such an approach. The case study suggests that status-based decisions could be applied to smart manufacturing and that they can be part of an approach that balances the self-organized control with overall performance. Therefore, we can make full use of intelligent entities in lower levels of a factory while keeping the entire system under control.

Industry 4.0 introduces new production paradigms like Cyber Physical Production System (CPPS) which should be efficient, self-organized and resilient. The emergence of CPPS evolves the roles of humans and should enhance the manufacturing system efficiency and the decision making process. In this paper, we are studying the human’s new roles to ensure resilience of industrial Cyber Physical System (CPS). We are proposing a new human-centred decision-making architecture taking into consideration the strategic, the tactical and the operational levels.

Cyber-physical systems (CPS) in supply chain management: from foundations to practical implementation

Implementation and Evaluation of 5G-enabled sensors for Machine Tools

Online monitoring and collaborative scheduling method for wheelset cyber-physical production system: A wheelset manufacturing system case study from a Chinese high-speed train enterprise

Digital equivalence is the main objective of Digital Twin (DT)s, and simulation is an integral part. DTs reach beyond traditional simulation with the help of real-time synchronization through Industrial Internet of Things (IIoT) technologies. Simulation supports off-line experimentations and planning, while DTs offer synchronous execution and modification. DTs help to understand “what may happen”. Also, they present “what is happening” and its management methodologies. In this paper, we present building aspects and an integration approach for a Digital Twin based Discrete-Event Simulation model. Our approach utilizes a data-driven agent-based simulation within a DT framework. It presents an integration layer that provides two essential features: reconfiguration and state initialization. It gives simulation models configurability and integrity that are required for operating within a DT. Our proposed approach is presented through a use case of a semiconductor manufacturing system. The proposed integration layer extends the usability of current Discrete-Event Simulation (DES) for a DT within a Cyber-Physical Production System.

Currently, factory automation systems need to cope with very different challenges, such as technological advances happening very fast, global and competitive market or product customization. These challenges lead to a new generation of automation systems based on the so-called Cyber-Physical Production Systems (CPPS) globally connected to form a flexible System of Cyber-Physical Production Systems (SoCPPS). CPPSs require acquisition of production system data and smart data processing to extract information to improve the overall system performance. To achieve that it is needed to bridge the gap between the control systems and higher layers. This paper discusses an approach to use the IEC 61499 function block concept to exchange data between plant floor and higher layers using an industrial standard like OPC UA. The OPC UA server offers subscription mechanisms, making possible the integration of several resources residing at plant floor. As it runs on embedded devices, the proposal makes possible to acquire plant information at low cost, enabling at the same time, a component-based design for enterprise plant floor control with independence of the hardware platform used.

A Machine Vision-based Cyber-Physical Production System for Energy Efficiency and Enhanced Teaching-Learning Using a Learning Factory

The way aircraft are manufactured plays a crucial role in shaping efficiency, costs, and overall quality in the aerospace industry. This study delves into the key principles, methodologies, and technological advancements that define modern aircraft manufacturing system design. It examines both traditional and emerging approaches, such as assembly line optimization, automation, digital twin technology, and Industry 4.0 applications. Additionally, it explores how lean manufacturing, Just-In-Time (JIT) production, and additive manufacturing (3D printing) are helping to improve efficiency and reduce waste. Beyond the technical aspects, this research also highlights some of the major challenges in aircraft manufacturing, including complex supply chains, material selection, precision engineering, and regulatory compliance. By analysing case studies from leading aerospace manufacturers, the study uncovers best practices and the latest trends shaping the industry. Through real-world examples, it provides insights into how companies refine their production processes to meet growing demands for safety, sustainability, and cost-effectiveness. This research adds to the existing body of knowledge by offering an in-depth look at how aircraft manufacturing is evolving. The findings can serve as a valuable resource for aerospace manufacturers, engineers, and policymakers looking to make informed decisions about improving production efficiency, reducing costs, and enhancing aircraft performance. Ultimately, this paper highlights the importance of integrating advanced technologies and lean methodologies to build a more sustainable and efficient future for aircraft manufacturing.

Link, J. S., Yemane, D., Shannon, L. J., Coll, M., Shin, Y-J., Hill, L., and Borges, M. F. 2010. Relating marine ecosystem indicators to fishing and environmental drivers: an elucidation of contrasting responses. – ICES Journal of Marine Science, 67: 787–795. The usefulness of indicators in detecting ecosystem change depends on three main criteria: the availability of data to estimate the indicator (measurability), the ability to detect change in an ecosystem (sensitivity), and the ability to link the said change in an indicator as a response to a known intervention or pressure (specificity). Here, we specifically examine the third aspect of indicator change, with an emphasis on multiple methods to explore the “relativity” of major ecosystem drivers. We use a suite of multivariate methods to explore the relationships between a pre-established set of fisheries-orientated ecosystem status indicators and the key drivers for those ecosystems (particularly emphasizing proxy indicators for fishing and the environment). The results show the relative importance among fishing and environmental factors, which differed notably across the major types of ecosystems. Yet, they also demonstrated common patterns in which most ecosystems, and indicators of ecosystem dynamics are largely driven by fisheries (landings) or human (human development index) factors, and secondarily by environmental drivers (e.g. AMO, PDO, SST). How one might utilize this empirical evidence in future efforts for ecosystem approaches to fisheries is discussed, highlighting the need to manage fisheries in the context of environmental and other human (e.g. economic) drivers.

It is a known fact that aerospace industry requires very strict requirements in terms of weight, material properties, and product lifetime performance. Therefore, composite materials are key candidates to satisfy these stringent requirements. Thermoplastic composites have become more competitive in the fields of aerospace, defense, energy, electronics, and automotive industries compared to thermoset composites, due to their ease of formability, short production cycles, and recyclability. Considering the benefits of thermoplastic composite materials, more thermoplastic parts will be produced in near future in aerospace industry. This study highlights the most recent advancements in thermoplastic composite technology. The latest advances in thermoplastic composite technology are highlighted by reviewing material technologies and production methods. Conclusion of this study, it has been observed that the use of thermoplastics in the aerospace industry is increasing day by day, owing to the advantages they offer compared to traditional materials. Especially in critical and trending areas such as stamp forming, press consolidation, Automatic Fiber Placement (AFP), and welding methods, research and development activities are intensifying. Furthermore, this study provides insights into the direction of current investments in thermoplastic technology and discusses how these investments are likely to shape future applications within the aerospace industry.