This article introduces OPRA (Observation-Prompt-Response-Action) and its multi-agent extension, COPRA (Collaborative OPRA), as frameworks offering alternatives to traditional agent architectures in intelligent manufacturing systems. Designed for adaptive decision-making in dynamic environments, OPRA enables agents to request external knowledge—such as insights from large language models—to bridge gaps in understanding and guide optimal actions in real-time. When predefined rules or operational guidelines are absent, especially in contexts marked by uncertainty, complexity, or novelty, the OPRA framework empowers agents to query external knowledge systems (e.g., ChatGPT), supporting decisions that traditional algorithms or static rules cannot adequately address. COPRA extends this approach to multi-agent scenarios, where agents collaboratively share insights from prompt-driven responses to achieve coordinated, efficient actions. These frameworks offer enhanced flexibility and responsiveness, which are critical for complex, partially observable manufacturing tasks. By integrating real-time knowledge, they reduce the need for extensive training data and improve operational resilience, making them a promising approach to sustainable manufacturing. Our study highlights the added value OPRA provides over traditional agent architectures, particularly in its ability to adapt on-the-fly through knowledge-driven prompts and reduce complexity by relying on external expertise. Motivational scenarios are discussed to demonstrate OPRA’s potential in critical areas such as predictive maintenance.
Sustainable development in mountainous and hilly regions is a critical component of global sustainability efforts. These regions are facing numerous challenges, including ecological fragility, labor migration, and resource scarcity and imbalance. Addressing these issues is imperative for sustainable development; this study identifies two primary conditions necessary for sustainable development in mountainous regions: achieving human and nature’s sustainable development, which provides reliable material support and social support for achieving the same in the mountainous and hilly regions. The flower-viewing economy, derived from transforming China’s mountain agriculture, is an efficient new format for mountainous and hilly regions. To verify these primary conditions, this study constructed a flower-viewing economy from three dimensions: material support, subject relationship, and expectation, using the peach blossom festival in Tingzi Village, Taihe Town of Chongqing City, as an example. Here, we explained that a sustainable development model focused on benefiting farmers is an endogenous, farmer-centered pathway to sustainable development, highly relevant to promoting sustainable development in developing countries’ mountain villages.
Artificial Intelligence (AI) and Machine Learning (ML) are transforming manufacturing processes, offering unprecedented opportunities to enhance sustainability and environmental stewardship. This comprehensive review analyzes the transformative impact of AI technologies on sustainable manufacturing, focusing on critical applications, including energy optimization, predictive maintenance, waste reduction, and circular economy implementation. Through systematic analysis of current research and industry practices, the study examines both the opportunities and challenges in deploying AI-driven solutions for sustainable manufacturing. The findings provide strategic insights for researchers, industry practitioners, and policymakers working towards intelligent and sustainable manufacturing systems while elucidating emerging trends and future directions in this rapidly evolving field.
The growing demand for sustainable materials in the automotive industry has prompted research into natural fiber-reinforced composites. To reduce carbon footprints and enhance product sustainability, the sectors increasingly focus on renewable and biodegradable materials. Composites made from natural fibers, such as coir and hemp, offer a promising solution for creating lightweight, high-performance components with a reduced environmental impact.In this study, an experimental investigation was conducted to examine the impact of single and hybrid and treated and untreated fibers, on the properties of epoxy-based composites. Untreated hemp fiber with treated Coir fiber was used for the research. The composites were fabricated through the open mould hand lay-up technique. Samples were prepared by randomly dispersing the fibers in the epoxy matrix before pouring them into the respective moulds prepared according to ASTM standards. Tensile, impact, and hardness tests were conducted on the cured samples to determine their mechanical properties, while a scanning electron microscope was used to evaluate the fractured surface. Water absorption tendencies were also determined. The results showed that the sample denoted as 5CF wt.% had the best property combination with tensile strength (32.4 MPa), tensile modulus (11.9 GPa), flexural strength (167.0 MPa), and impact strength (46.8 kJ/mm2). It was discovered that hemp fiber-based composites were not enhanced properly due to lack of fiber surface modifications. Though optimum results were obtained from treated coir fiber-based single/distinct composite, untreated hemp fiber was discovered to aid some flexural modulus and hardness properties in the hybrid composite based on the best results obtained in its distinct-based composite. Therefore, untreated hemp fiber can be used in hybrid form with treated coir fiber where one of the fibers is scarce or when fiber surface medication is difficult to achieve. Thus, the results showed that 5CH-based composites are the most suitable composition for automotive components development where high-mechanical properties are essential.
Recently, onboard sensing and support devices have been used for the well-being of humans, animals, birds, plants and, more generally, biodiversity. The performance of these tools is closely linked to their electromagnetic environment, mainly artificially created by humans. Therefore, the presence of electromagnetic radiation linked to human activities near such tools constitutes a threat. The intelligent and sustainable manufacturing of these tools, which makes it possible to face such a threat, can be achieved through their design and optimization. This commentary aims to highlight the interaction of artificial electromagnetic radiation with onboard health tools involving living tissues in urban biodiversity (One Health concept) and the intelligent and sustainable construction and protection (Responsible Attitude concept) of these tools. The manuscript presents an overview of onboard devices, possible effects of electromagnetic radiation, durable construction and shielding, and analysis of electromagnetic compatibility integrity control. The main outcome of this contribution regarding sustainably designed onboard devices is that numerical analysis tools of electromagnetic fields could efficiently verify their integrity and the behavior of their necessary smart shields. These different themes are associated with examples of literature.
Lithium batteries pave way for rapidly reducing greenhouse gas emissions. Still there are concerns associated with battery sustainability, such as the supply of key battery materials like cobalt, nickel and carbon emissions related to their manufacture. While LiMn2O4 spinel is a common cathode material for Li-ion batteries that remove Co and Ni, studies on over-stoichiometric variants and their behavior across a broad potential range may be limited. Research in this area could provide valuable insights into the performance, stability and electrochemical characteristics of such cathodes, offering potential benefits for the development and optimization of Li-ion battery technologies. This study investigates the electrochemical behavior of Li-rich Li1+yMn2−yO4−δ (LMO, y ≈ 0.03, δ ≈ 0.01) spinel as a cathode in Li-ion batteries, focusing on the phenomenon of extra capacity under the extended operating voltage 1.5–4.8 V vs. Li+/Li. The nanostructured LMO sample synthesized by sol-gel method and calcined at 900 °C is characterized by X-ray diffraction, scanning and transmission electron microscopy and surface area measurements. The Li-rich spinel electrode delivers a specific discharge capacity of 172 mAh g−1 at 1st cycle. It retains 123 mAh g−1 at the 100th cycle (71.5% capacity retention) at current density of 100 mA g−1 current density (i.e., ~0.7 C rate). An excellent stability is obtained in the 1.5–4.8 V potential window, with a discharge capacity of 77 mAh g−1 after 500 cycles at the same current density, owing to the reduction of the Jahn-Teller effect by Li doping. These results contrast with the specific capacity of 85 mAh g−1 (1st cycle) and the capacity retention of 54.3% after 100 cycles, obtained when the cell operates in the narrow potential range of 3.0–4.5 V.
Technological innovations, education, business and society change quickly and often unpredictably. The fusion of artificial intelligence (AI), machine learning, augmented reality (AR), virtual reality (VR) and augmented reality (XR) opens a new era in which work, production, communication and thought processes are massively transformed. In this context, the challenge arises: How can small and medium-sized enterprises (SMEs) adapt to this accelerated change? This study highlights a path forward and introduces the concept of “SME 5.0” or “Hybrid SME” or “SME of Tomorrow” as a comprehensive solution to address the complexities of the digital age. In this integrated exploration of the X.0 Wave Theory and SME 5.0 Concept, the framework for human civilization’s evolution and technological shifts converges with a practical roadmap for small and medium-sized enterprises (SMEs) navigating the dynamic digital landscape. Acknowledging transformative waves in technology, economics, and societal structures within the X.0 Wave Theory, the study accentuates the ongoing nature of these shifts. It advocates for a long-term perspective, urging policymakers and industry leaders to consider potential future scenarios to devise strategies fostering innovation, competitiveness, and privacy safeguards. Simultaneously, the study introduces SME 5.0 as a holistic solution for SMEs, aligning with the transformative success envisioned by the X.0 Wave Theory. Proposing the Seven Pillars of Sustainability (7PS) framework tailored to SMEs, the concept emphasizes digitalization and sustainable technology. The title, “Harmonizing the X.0 Wave Theory and SME 5.0 Concept”, encapsulates the synergy between theoretical underpinnings and practical solutions. The subtitle, “Fostering Sustainable Collaboration, 7PS Engineering, and Overcoming Legal Challenges in the Digital Age”, provides a glimpse into the study’s focus on practical implications, sustainability, engineering, and legal considerations for SMEs in the rapidly evolving digital era.
This manuscript describes the research path when extending a maturity model. The initial model—ManuMaturity—was for manufacturing companies aiming beyond Industry 4.0. The extended OSME model covers data sharing within a supply chain, an open innovation ecosystem and sustainable manufacturing. The OSME maturity model has five maturity levels: traditional factory, modern factory, agile factory, agile cognitive factory and agile cognitive industry and seven dimensions (such as infrastructure, data, customer, business model, employee, sustainability and processes). The tool was experimented with in manufacturing companies on two occasions: with a set of manufacturing companies and a group of companies. In both cases, feedback was gathered from the respondents. The article follows the maturity assessment development phases such as scope, design, populate, test, deploy and maintain, and reports the software implementation of the maturity tool. With the help of the developed maturity model and the tool, it was possible to make assessments in case companies, where the tool and its results were commented mostly positively. The tool can be applied in various ways. For example, a group of people can jointly submit their common understanding and have a thorough discussion or a group of company representatives submit their responses and the variation is discussed afterwards.
Vitrimers are crosslinked polymers containing dynamic covalent linkages. Because of their crosslinked structure, they are stable as thermosets at their service temperatures. At high enough temperatures, dynamic exchange reactions occur and rearrange the polymer network, thus vitrimers become malleable and reprocessable like thermoplastics. The dynamic covalent bonds can also undergo dissociative cleavage reactions under specific conditions, so vitrimers are inherently degradable. To achieve a sustainable future, various biomass resources have been used as raw materials in vitrimer preparation. This review summarizes recent developments in biobased vitrimers and highlights their preparation methods. The limitations of current biobased vitrimers are also discussed.
This paper gives a comprehensive review of scientific interests and current methodologies of artificial intelligence applied to advanced material design and discovery by taking into account multiple sustainable design criteria such as functionalities, costs, environmental impacts, and recyclability. The main research activities include predicting material properties, compositions, and structures with data mining, new material discovery, hybrid modeling approaches combining AI techniques and classical computational formulations based on physical and chemical laws, and multicriteria optimization of materials. Based on this review, a short analysis is provided on the perspectives of this research area in the future, aiming at creating an everything connected material life cycle with real-time traceability systems