Adaptation Of Production Systems Research Articles

Resilient, Adaptive Industrial Self-X AI Pipeline with External AI Services: A Case Study on Electric Steelmaking

The introduction of Self-X capabilities into industrial control offers a tremendous potential in the development of resilient, adaptive production systems that enable circular economy. The Self-X capabilities, powered by Artificial Intelligence (AI), can monitor the production performance and enable timely reactions to problems or suboptimal operation. This paper presents a concept and prototype for Self-X AI in the process industry, particularly electric steelmaking with the EAF (Electric Arc Furnace). Due to complexity, EAF operation should be optimized with computational models, but these suffer from the fluctuating composition of the input materials, i.e., steel scrap. The fluctuation can be encountered with the Self-X method that monitors the performance, detecting anomalies and suggesting the re-training and re-initialization of models. These suggestions support the Human-in-the-Loop (HITL) in managing the AI models and in operating the production processes. The included Self-X capabilities are self-detection, self-evaluation, and self-repair. The prototype proves the concept, showing how the optimizing AI pipeline receives alarms from the external AI services if the performance degrades. The results of this work are encouraging and can be generalized, especially to processes that encounter drift related to the conditions, such as input materials for circular economy.

Development and Application of Digital Twin Control in Flexible Manufacturing Systems

Flexible manufacturing systems (FMS) are highly adaptable production systems capable of producing a wide range of products in varying quantities. While this flexibility caters to evolving market demands, it also introduces complex scheduling and control challenges, making it difficult to optimize productivity, quality, and energy efficiency. This paper explores the application of digital twin technology to tackle these challenges and enhance FMS optimization and control. A digital twin, constructed by integrating simulation models, data acquisition, and machine learning algorithms, was employed to replicate the behavior of a real-world FMS. This digital twin enabled real-time dynamic optimization and adaptive control of manufacturing operations, facilitating informed decision making and proactive adjustments to optimize resource utilization and process efficiency. Computational experiments were conducted to evaluate the digital twin implementation on an FMS equipped with robotic material handling, CNC machines, and automated inspection. Results demonstrated that the digital twin significantly improved FMS performance. Productivity was enhanced by 14.53% compared to conventional methods, energy consumption was reduced by 13.9%, and quality was increased by 15.8% through intelligent machine coordination. The dynamic optimization and closed-loop control capabilities of the digital twin significantly improved overall equipment effectiveness. This research highlights the transformative potential of digital twins in smart manufacturing systems, paving the way for enhanced productivity, energy efficiency, and defect reduction. The digital twin paradigm offers valuable capabilities in modeling, prediction, optimization, and control, laying the foundation for next-generation FMS.

Interconnected and resilient: A CGE analysis of AI-driven cyberattacks in global trade.

The burgeoning interconnectedness of global trade in the digital age not only presents enticing opportunities but also harbors potent vulnerabilities of artificial intelligence (AI)-driven cyberattacks. This study explores the cascading impacts of these disruptive threats on economies, supply chains, and trade, utilizing the intricate lens of Computable General Equilibrium modeling. Through meticulously designed simulation scenarios, we illuminate the potential economic ramifications of cyberattacks, with a focus on regions heavily reliant on digital technologies and interwoven supply chains. The analysis reveals significant declines in real GDP, trade prices and volumes, and trade route disruptions across regions. Notably, economies like China, the United States, the United Kingdom, and the EU, due to their deep integration in global networks, face pronounced vulnerabilities. However, amidst this bleak landscape, hope emerges in the form of cyber resilience. The study showcases the effectiveness of proactive measures like adaptable production systems, diversified trade partners, and robust cybersecurity infrastructure in mitigating the adverse impacts of cyberattacks. Incorporating cyber resilience significantly dampens the reported negative consequences, highlighting the critical role of preparedness in combating digital warfare. This study underscores the urgent need for a global paradigm shift toward cyber resilience. Collective efforts to bolster cybersecurity infrastructures, foster international cooperation in threat intelligence, and establish open and resilient trade frameworks are crucial in navigating the treacherous labyrinth of AI-driven cyberattacks. By embracing resilience strategies and fostering global collaboration, we can pave the way for a more secure and prosperous digital future, where interconnectedness becomes a tool for progress, not a vulnerability to be exploited.

Design of a Flexible Skill-Based Process Control System Considering Process-Relevant Properties

The Industry 4.0 research initiative strives to facilitate globally interconnected, flexible, and highly adaptable production systems. The use of skill-based control mechanisms such as OPC UA skills offers the prospect of a straightforward and flexible interchange, as well as the seamless integration of individual participants and processes through standardized interfaces. Furthermore, by enhancing these skills with evaluation parameters pertinent to the processes, such as CO2 equivalents or the duration of specific skill executions, a foundation is laid for creating a customizable and adaptable composition of processes based on specific production process needs. In this article, the OPC UA skill concept is expanded with process-relevant properties, and a structured procedure for the introduction of skill-based process control is presented. The developed concept was implemented and tested on an industrial use case of glass pane completion. The aim of this publication is to demonstrate the potential of skill-based process control that has an integrated assessment of skills.

Definition and Description of Matrix Production Systems

The industry’s use of adaptable production systems, such as matrix production, is increasing. However, these systems vary in their specific details. The lack of a unified definition, delimitation, and description hinders comparability and the transfer of lessons learned between different systems. This paper aims to propose a comprehensive definition of matrix production and differentiation between different implementation forms.To achieve this, the paper first examines existing approaches to define and describe production systems and their manifestations. Various frameworks and models have been proposed in the literature, but they often focus on specific aspects of production systems, neglecting the complexity of matrix production. The paper identifies common elements and challenges in defining and describing production systems by analyzing these approaches.A second investigation analyzes various existing descriptions of matrix production from the scientific literature. While some definitions focus on the organizational structure, others emphasize operational aspects. By synthesizing these definitions, the paper proposes a comprehensive definition of matrix production encompassing both dimensions.Furthermore, the paper includes cases of industrial implementations as a third investigation. These cases provide insights into the practical application of matrix production systems across different industries. The paper identifies common characteristics, challenges, and benefits associated with matrix production by analyzing these implementation examples.Finally, all three investigations are combined to create a unified definition and a complementary descriptive model. The proposed framework provides a systematic approach to define and describe matrix production systems. It allows for a better understanding and comparison of different implementations, facilitates the transfer of lessons learned, and promotes the exchange of best practices.This framework will enable researchers and practitioners to optimize matrix production systems, ultimately leading to improved efficiency and competitiveness in the industry.

Industrial collaborative environments integrating AI, Big Data and Robotics for smart manufacturing

In recent years, global events have posed significant challenges to manufacturing firms’ business models, necessitating adaptable production systems that integrate human and automated resources seamlessly. Fortunately, technological advancements over the past decade have facilitated flexible production solutions. This paper introduces the approach of the CONVERGING EU project for collaborative smart manufacturing systems aiming at increasing flexibility, efficiency, and operators’ satisfaction. The proposed approach is structured into three technical pillars: perception, adaptation, collaboration, enhanced by modules for fostering user experience. Perception involves identifying and recognizing features of parts, resources, and surroundings to infer and analyse their status, and formulate action plans. Automated adaptations through hardware and control system modifications allow for executing formulated plans while complying with user characteristics and needs. Collaboration focuses on the software and hardware interfaces to ensure safe and seamless interaction with collaborative robotic solutions. Training, ergonomics tracking, and adaptable interfaces are also proposed to pave the way toward social industrial environments. This approach is applied to four industrial scenarios from different manufacturing sectors: automotive, white goods, aeronautics and additive manufacturing. The design of systems incorporating AI and robotics is presented together with the expected impact including safer, more intuitive, and trustful human-robot interaction, but also more inclusive industrial environments.

Legal regulation of economic security of Ukraine under the establishment of Industry 4.0

Problem setting. The conditions of the modern digital era impose new requirements on the efficiency of national enterprises. Industry 4.0 involves digitization and automation of production processes and management at enterprises of the real sector of the economy to increase labor productivity, reduce costs, flexibility and adaptability of production systems, and the effectiveness of cooperation in the value creation chain. At the same time, with the possibilities of Industry 4.0 technologies, there are threats to economic security, which requires the development of a strategic vision and legal regulation of security in the digital economy. Analysis of recent researches and publications. The analysis of scientific publications of domestic scientists on the topic of the study showed that there are two opposite groups of works. The first group of researchers analyzes the risks and threats of Industry 4.0 for the economy; however, the authors do not provide recommendations for ensuring economic security in the digital economy. The second group of scientific publications is devoted to general issues of ensuring the economic security of Ukraine, in particular in the legal sphere. However, they hardly pay attention to threats from digitalization. Purpose of research is the development of theoretical provisions and practical recommendations regarding the improvement of regulatory and legal regulation of ensuring the economic security of Ukraine in the conditions of the formation of Industry 4.0. Article’s main body. The work examines the essence of Industry 4.0, the possibilities and advantages of introducing digital technologies into management and production processes, the risks of digitalization and threats to the economic security of Ukraine, the feasibility of improving the legal regulation of economic security in the conditions of the introduction of digital technologies is substantiated. During the analysis of legal acts, the lack of a strategic vision of ensuring economic security against the threats of digitalization, an insufficient list of security indicators for assessing the consequences of digital transformations, and the threat of Ukraine’s financial and technological dependence on developed countries were revealed. The basic principles of the formation of state policy in the field of economic security are substantiated: the rule of law, the priority of protecting economic sovereignty, the correlation and comparability of national and international legislation, adequacy, expediency, meaningfulness, rationality, timeliness and effectiveness of regulatory measures, mutually beneficial conditions of international cooperation, equality of opportunities for residents and nonresidents, stimulation of the domestic economy, sequence of opening of the national economic system for the EU economic system, priority of protection of strategic sectors of the economy, recognition of the jurisdiction of international judicial and arbitration bodies. It is proposed to improve legal regulation in terms of expanding the principles of state policy formation in the field of economic security, revising the methodology for calculating the level of economic security of Ukraine, regulating the provisions on the development and implementation of the Strategy of Economic Security of Ukraine, establishing threats from digitalization and determining the corresponding tasks to overcome them in each sphere of economic security. Conclusions and prospects for development. The implementation of Industry 4.0 is associated with significant threats to national economic security, which requires the development and implementation of a state policy to ensure security in the field of the digital economy. The developed recommendations for improving legal regulation will allow to more effectively ensure economic security in Ukraine. Further directions of research consist in the development and scientific substantiation of measures to ensure economic security in conditions of digitalization, improvement of legal support for their effective implementation.

Bienestar animal y sistemas de producción en el siglo XXI

Animal welfare has been gaining prominence on the world stage in recent years. This highlight the need to adapt production systems. The term animal welfare is a growing concept in the global context and has undergone important changes in its definition, evaluation and interpretation in the last century. The science of animal welfare recognizes the importance of the five freedoms as a way of conceptualizing welfare and the need for a reinterpretation of how to assess and interpret the status of welfare, especially for production animals. This reinterpretation culminated in the development of the Five Domains model, a model designed to assess animal welfare in a more complete, systematic and comprehensive way. The model has four physical / functional domains, evaluated through the definition of indicators. The assessments enabled the incorporation of many protocols for analyzing welfare, aimed at animal production systems, in which the general state of welfare reflects its status, which can be defined as a scale, being positive, neutral or negative. The objective of this bibliographic review is to highlight the evolution of animal welfare science considering the five domains as the main criteria to be used to define the welfare status of production animals.

Global meta-analysis: Sparse tree cover increases grass biomass in dry pastures

Agricultural and ecological droughts, extreme heat and aridity have high impacts on livestock and pasture systems worldwide. Finding ways to adapt production systems and increase biomass under these new conditions is urgently needed. The availability of tree shade in these pastures could potentially ameliorate the impacts of warm weather. Yet, the effects of tree cover on the productivity of livestock rangelands are hotly debated. We performed a global meta-analysis to evaluate the effects of tree cover on grass biomass during contrasting seasons within the same system and along environmental gradients in tropical and temperate productive systems. We also assessed the levels of canopy density at which tree cover effects are observable. We observed that trees facilitate grass biomass during dry seasons, especially in the tropics and dry regions. These positive effects are more likely to occur at intermediate levels of evapotranspiration and irradiance. Our findings suggest that integrating trees in pastures might increase resilience of current livestock production systems to drier and warmer conditions.

New Data Structures for a Flexible Order Management

Turbulent markets pose increasing challenges for manufacturing companies. Disruptions such as customer order changes, machine breakdowns, or delivery failures require constant adjustments in operations. The efficient and effective handling of these disruptions is essential to achieve the required customer satisfaction. More adaptable production systems like the Fluid Manufacturing System (FLMS) promise to meet the changed requirements. A correspondingly adaptable order management system is needed. However, today’s order management structures are too rigid. Within this paper, the challenges of production planning and control with regard to adaptable production systems are derived. Then, today’s data structures in order management are presented and, based on this, a new flexible data structure for order management is developed.

Co-Operative Learning and Resilience to COVID-19 in a Small-Sized South African Enterprise

Constraints imposed by the shrinking resources and the climate change dynamics necessitate a behavioral change to increase knowledge exchange and optimize resource utilization. Existing entrepreneurship and innovation practices are therefore undergoing transformation to adapt production systems to the post-COVID-19 reality of increased risks of calamities within a context of shrinking resources. This paper uses a knowledge-centered crisis management framework to examine how enhanced knowledge sharing through co-operative learning can be applied to induce higher innovation performance and more efficient resource utilization structures during crises comparable to the current pandemic. Using the collaborative learning experiences of a small enterprise producing ecological fertilizers, this study was able to link crisis resilience enhancement to increased knowledge exchange between business entities connected through the agro-ecological value chain. New insights generated through the co-learning process were found to constitute a key input for strengthening the required capability endowments that enable the organization and its partners to weather the COVID-19 crisis and lay the foundation for the sustainability of post-COVID-19 operations.

Synthesis of Adaptive Systems in an Unstable Environment

Purpose: the article is devoted to the ways to create adaptive production systems, taking into account the experience of the economies that have successfully emerged from the terminal crisis. One of the tasks is to improve the adaptability of the production system or, at the best, of the socio-economic system as a whole, in a now situation of uncertainty and unpredictable social, technological, structural, economic dynamics.Methods: an approach is based on the provisions of systemic economic theory, specifically on the representation of the socio-economic system in the form of a tetrad, comprising several key subsystems (sectors) that exchange resources (powers) that they possess.Results: noticeable contemporary conditions and the characteristics of the global socio-economic system are identified as a terminal crisis, which is determined by the depth and breadth to cover the regions, countries, industries with serious changes of a new quality in the functioning of economic objects at the different hierarchy levels. Such a crisis, in contrast to a structural crisis, affects all social groups, spheres of subject affairs and actors relations. The paper argues the quite relevant issue of how to make a systemic transition to a new model and paradigm of the economy. With this purpose, we have identified three groups of factors on which a model of the economy in a post-pandemic world can be based at least. Theoretical grounds and practical conclusions are given in order to carry out system assembly (synthesis) of a production system based on the model of the tetrad.Conclusions and Relevance: it is shown that the synthesis of all types of systems – socio-economic, industrial, innovation system – should be carried out on the basis on systemic economic paradigm, taking into account both the new current phenomena and peculiarities on the different economic levels. According to the author conclusion, some of the principles, proposed to organize and manage the corporate systems by Deming, can be used to increase adaptive ability of the production systems at least at the micro level of the Russian economy, which will inevitably be being transformed in a post-pandemic world.

Dialogue Enhanced Extended Reality: Interactive System for the Operator 4.0

The nature of industrial manufacturing processes and the continuous need to adapt production systems to new demands require tools to support workers during transitions to new processes. At the early stage of transitions, human error rate is often high and the impact in quality and production loss can be significant. Over the past years, eXtended Reality (XR) technologies (such as virtual, augmented, immersive, and mixed reality) have become a popular approach to enhance operators’ capabilities in the Industry 4.0 paradigm. The purpose of this research is to explore the usability of dialogue-based XR enhancement to ease the cognitive burden associated with manufacturing tasks, through the augmentation of linked multi-modal information available to support operators. The proposed Interactive XR architecture, using the Spoken Dialogue Systems’ modular and user-centred architecture as a basis, was tested in two use case scenarios: the maintenance of a robotic gripper and as a shop-floor assistant for electric panel assembly. In both cases, we have confirmed a high user acceptance rate with an efficient knowledge communication and distribution even for operators without prior experience or with cognitive impairments, therefore demonstrating the suitability of the solution for assisting human workers in industrial manufacturing processes. The results endorse an initial validation of the Interactive XR architecture to achieve a multi-device and user-friendly experience to solve industrial processes, which is flexible enough to encompass multiple tasks.

Biomimicry and the Problem of Praxis

Biomimicry can serve as a design template for an ecological civilisation by showing how cyclical, no-waste, mutually adaptive production systems designed ‘after nature’ could render human industry fully ‘sustainable’. However, unless the modes of praxis involved in such a reformed industrial base are also redesigned, the value orientation fostered by the new order would remain anthropocentric. Biomimicry would accordingly result in an eco-modernist-type scenario in which society was ‘decoupled’ from nature, with dystopian consequences for the larger community of life. Drawing on Indigenous modalities, I explore ways in which modern industrial systems could include participatory modes of praxis that would emanate in genuinely bio-inclusive forms of consciousness and hence lay the ethical foundations for an ecological civilisation.

A Function-Behaviour-Structure design methodology for adaptive production systems

Adaptive production systems are a key trend in modern advanced manufacturing. This stems from the requirement for the system to respond to disruption, either in the form of product changes or changes to other operational parameters. The design and reconfiguration of these systems are therefore a unique challenge for the community. One approach to systems design is based on functional and behavioural modelling, drawn from the field of design theory. Existing approaches suffer from lack of focus on the adaptive properties of the system. While traditional production systems design focusses on the physical system structure and associated processes, new approaches based on functional and behavioural models are particularly suited to addressing the challenges of disruptive production environments resulting from Industry 4.0 and similar trends. We therefore present a Function-Behaviour-Structure (FBS) methodology for Evolvable Assembly Systems (EAS), a class of self-adaptive reconfigurable production systems, comprising an ontology model and design process. The ontology model provides definitions for Function, Structure, and Behaviour of an adaptive production system. This model is used as the input to a functional modelling design process for EAS-like systems, where the design process must be integrated into the system control behaviour. The framework is illustrated with an example taken from a real EAS instantiation using industrial hardware.

Multi-criteria evolutionary algorithm optimization for horticulture crop management

Climate variability requires adaptive production systems in agriculture often resulting in significant irreversible investments. Cultivar replacement programs in horticulture orchards that substitute older varieties for more heat- and drought-resilient varieties have enterprise values that are highly sensitive to the timing of such investments. Farm-level replacement programs are subject to multiple constraints around debt serviceability, operating costs, the replacement cycle and the rate of degradation of the existing orchard. The maximization of enterprise value subject to multiple constraints can be reduced to a multi-objective optimization problem. Over long horizons this optimization process generates a very-large solution space. Using a multi-objective evolutionary algorithm we examine uncertainties around climatic effects and the timing of investments for horticultural operations and derive the optimal times to adapt using cultivar replacement techniques. We find that the investment decision using traditional valuation methods is suboptimal and can result in poor decisions, potentially undermining adaptation efforts. We further show that opposing economic and climatic conditions can adversely impact enterprise value based on mistiming the investment decision. Application of the genetic algorithm solver is demonstrated using a vector-based geographic information system to a farm where individual portions of an orchard are subject to varying rates of production, degradation and age.

The Assist-By-X system: Calibration and application of a modular production equipment for visual assistance

Shorter production lifecycles, new challenges due to the advancing globalization, and increasing demand for individualized products are only some of the general conditions that internationally operating manufacturing companies have to face. Therefore, adaptable production systems are required which can be changed to the current requirements of the production process. In this article, a modular visual assistance system is presented which can be integrated in different production systems and environments. For a successful integration of the assistance system a calibration is indispensable, thus a calibration method for one component of the assistance system is discussed in detail. In order to control the system, a visual data flow programming tool is used in combination with MQTT as a standard communication protocol. By doing so, the programming effort of the system is reduced and new components can easily be added to the system by creating new flows.

Reconfiguration of production systems using optimization and material flow simulation

Current market developments, such as intensifying volatility and rising demand for individualized products, require highly flexible and adaptable production systems. Reconfigurable production systems enable manufacturing companies to meet these market developments due to the ability of short-term scalability of capacities and order-specific adjustments of production resources for preserving high delivery performance and utilization rate. The vast complexity of such systems raises the demand for decision support systems. Therefore, this paper presents an innovative approach combining optimization and material flow simulation for developing and selecting optimized reconfiguration scenarios. A prototypical application is presented to demonstrate the feasibility of the approach.

SMART CPPS ARCHITECTURE INTEGRATED IN THE USE OF IEC-61499, WITH A HIGHLY ADAPTABLE FUNCTIONS BLOCK IN 4.0 INDUSTRY

Currently, human beings are experiencing what has been named as the Fourth Industrial Revolution (Industry 4.0) in terms of automation and control systems of cyber-physical production environments. These systems do not only allow access to many innovative features, which are based on network connections, but also, they provide access to Internet of Things (IoT) world. It is in this context, IoT changes the way to link new technologies in order to obtain more efficient, intelligent, flexible and adaptable production systems. Thus, manufacturing systems have to be independent from the product itself that the companies wish to commercialize. Cyber-Physical Production Systems (CPPS) have several advantages like granular communications. On the other hand, common electric bandwidth for all users regardless of data speeds. As well, compatibility in connection with free or guided space communication links and the major intensity modulation compatibility. IEC standard 61499 is generally based on a generic architecture with specific software requirements and development rules that allows portability and device configuration.

Overseas Experience of Introducing Advanced Technologies of Production System Upgrading

Today's enterprise in order to be competitive needs not only to use high technologies, put out science-intensive products and have the R & D department with high innovation potential. To response in good time and adequately to challenges called 'digital economy' the company will be able only if it possesses a flexible adaptive production system providing synergy to all divisions, all employees of the enterprise. This system should continuously upgrade not to lose its relevance. The article deals with methodology of '20 keys' as an integrator of well-known approaches to enhancing the organization work. Its specific features and advantages were identified, as well as concrete results of introducing this methodology by overseas companies, in particular, the American company 'Windfall Products' specializing in production of powder metal components. The system of five-level appraisal of the organization formulated in the company is introduced in the article. Key stages of reforming conducted in the company, concrete processes and steps being in line with each of the stages are described there. Benefits of the program of '20 keys' for realizing modern tools and approaches to business enhancement are also included in the article.