Hasil untuk "Mechanical industries"

Salim Fares

A growing number of publications address the best practices to use Large Language Models (LLMs) for software engineering in recent years. However, most of this work focuses on widely-used general purpose programming languages like Python due to their widespread usage training data. The utility of LLMs for software within the industrial process automation domain, with highly-specialized languages that are typically only used in proprietary contexts, remains underexplored. This research aims to utilize and integrate LLMs in the industrial development process, solving real-life programming tasks (e.g., generating a movement routine for a robotic arm) and accelerating the development cycles of manufacturing systems.

Keno Moenck, Adrian Philip Florea, Julian Koch et al.

Autonomous vision applications in production, intralogistics, or manufacturing environments require perception capabilities beyond a small, fixed set of classes. Recent open-vocabulary methods, leveraging 2D Vision-Language Foundation Models (VLFMs), target this task but often rely on class-agnostic segmentation models pre-trained on non-industrial datasets (e.g., household scenes). In this work, we first demonstrate that such models fail to generalize, performing poorly on common industrial objects. Therefore, we propose a training-free, open-vocabulary 3D perception pipeline that overcomes this limitation. Instead of using a pre-trained model to generate instance proposals, our method simply generates masks by merging pre-computed superpoints based on their semantic features. Following, we evaluate the domain-adapted VLFM "IndustrialCLIP" on a representative 3D industrial workshop scene for open-vocabulary querying. Our qualitative results demonstrate successful segmentation of industrial objects.

Shams El-Adawy, A. R. Piña, Benjamin M. Zwickl et al.

This report builds upon the Categorization of Roles in the Quantum Industry report by providing detailed profiles for 29 distinct roles across the quantum workforce. While the earlier report established a framework of four major role categories (hardware, software, bridging, and public facing and business) and their subcategories, the current report expands on this structural framework by characterizing what professionals in each role actually do, particularly by identifying the tasks, knowledge, skills, abilities (KSAs), and experience typically required for each role. Each role profile follows a standardized structure guided by the Occupational Information Network (O*NET) framework. By presenting a fine-grained view of day-to-day work and qualification expectations, this report serves as a practical resource for educators, students, industry professionals, and policymakers aiming to understand, educate, and support the evolving quantum workforce.

V. N. Borisov, Yu. V. Zinchenko

Relevance: The article analyzes the relationship between the development of domestic mechanical engineering and relevant scientific schools within the framework of the concept of sustainable development. The functioning of domestic mechanical engineering is considered in the context of international associations.   The following methods were applied in the study: a systems approach, functional, comparative economic, and statistical analyses, as well as the authors’ methodological developments.   The scientific novelty of the article lies in the implementation of theauthors’ approach to studying mechanical engineering as an interaction between scientific schools and economic and environmental factors.   The results and conclusions of the study may be useful for decision-making within the existing economic model of the Russian Federation when forecasting, developing, and adjusting strategic programs for industry development.

K Deenadayalan, B Rahul

This paper presents a comparative study on the residual stress formation in a Nickel-based matrix by the reinforcement of two types of WC particles having two different shape factors (angular and spherical) and density. Three types of coatings were prepared: pure Nickel-based super alloy (Spherical), Nickel-based super alloy with 30 % spherical WC particles, and Nickel-based super alloy with Angular WC particles. The prepared coatings (Ni, Ni-WCS & Ni-WCA) are characterised using the X-Ray Diffraction technique for the subsequent evaluation of residual stress. Namely three techniques Sin2ψ method, William Hall method and the Direct instrumentation method based on XRD were incorporated to determine and compare the residual stresses formed in the coatings. The results exhibited that the Ni and WC shape and form factor had a significant influence on the coating residual stress.

I. O. Bakare

Natural rubber (NR) is an important export commodity in Nigeria with versatile applications in many industries. Its latex or lump forms are regarded as the farm gate while the ribbed smoked sheet (RSS) is the raw materials feeding the rubber industry and both are very essential in the productions process. Consequently the objective of this paper is to investigate the Evaluation of physicochemical properties, drying process and drying conditions of natural rubber (NR) latex and Ribbed Smoked Sheets (RSS) obtained from Benin City, Nigeria using appropriate standard procedures. Data obtained show that the constituents of Hevea (NR) latex are dry rubber content (%) 35.60; Lipids (%) 1.08; Protéines (%) 1.23; Carbohydrates (%) 1.40; Minerals (%) 0.47; Water (%) 60.22; Sspecific gravity (28 °C) 0.931± 0.003; Total solid content (TSC) (%) 43.20 ± 1.03; Mechanical stability M.S.T (%) 650 ± 1.06; Volatile fatty acids VFA (%) 0.18 ±0.07; Nitrogen Content (%) 0.55 ± 0.03, while the property of the ribbed smoked sheets (RSS) were Dirt % (wt) 0.15; Ash % (wt) 0.11; Volatile matter % (wt) 0.38; Wallace plasticity Po (47), PRI (74) and lightly brown in colour. The results obtained showed that processing NR into RSS not only served as a preservative, which improved the storage durability, but also imparted flavour, aroma, and attractive colour to the cured sheets. This study sheds more light on the processing, storage conditions, durability, and efficient production of high-value-added RSS developed from natural rubber latex.

S.M. Voloshko, B.M. Mordyuk, and M.O. Vasylyev

The growing demand for parts offering a high strength-to-weight ratio drives the need for lightweight materials for the aerospace and automotive industries. In this regard, the presented article aims to review the production aspects of a new class of lightweight materials with a high specific strength. The aluminium/carbon nanotubes (Al/СNTs) composites are among such materials. The present review characterises the following modern methods for producing such composites: friction stir processing, powder rolling process, powder extrusion process, high-pressure torsion, infiltration into the preform, pressureless sintering in vacuum, modified stir casting technique, spark plasma sintering, and laser additive manufacturing. The results of experimental studies of the mechanical characteristics of the Al/СNTs composites obtained by different methods and observations of the nanostructure formation depending on the СNTs content are presented. The strengthening mechanisms of the Al/СNTs systems are also considered.

Subhankar Chakraborty, Santanu Sharma, Rupam Goswami

In the world of electric vehicles energy recovery is a major concern for improving the mileage. One way of doing this can be recovery of road vibrations through regenerative damping. In this article, we propose a comparative analysis of 2 different types of regenerative dampers. One is Ball-screw damper and the other is Dual clutch rack and pinion damper on the basis of 2 characteristics. Firstly, analysis of impulse response to study the stability and filtration capability. Secondly, power optimization has been done to analyse the energy recovery and dissipation along with riding comfortability for different operational frequencies. The main identification parameter is the internal impedance of energy harvesting circuit. Mathematical analysis followed by simulation suggests that, in case of Dual clutch rack and pinion damper the average bandwidth to impedance ratio is 3.41 hertz-Ω−1 whereas for Ball-screw dampers is 0.22 hertz-Ω−1. This makes Dual clutch rack and pinion damper a good energy harvester at wider frequency ranges. However, magnitude of energy recovery is higher for Ball-screw damper dampers. The results obtained in this work would motivate other researchers to improve the functionality of both the dampers to enhance the dynamic stability and energy recovery of the vehicle.

Tom Maus, Nico Zengeler, Tobias Glasmachers

We present a novel reinforcement learning (RL) environment designed to both optimize industrial sorting systems and study agent behavior in evolving spaces. In simulating material flow within a sorting process our environment follows the idea of a digital twin, with operational parameters like belt speed and occupancy level. To reflect real-world challenges, we integrate common upgrades to industrial setups, like new sensors or advanced machinery. It thus includes two variants: a basic version focusing on discrete belt speed adjustments and an advanced version introducing multiple sorting modes and enhanced material composition observations. We detail the observation spaces, state update mechanisms, and reward functions for both environments. We further evaluate the efficiency of common RL algorithms like Proximal Policy Optimization (PPO), Deep-Q-Networks (DQN), and Advantage Actor Critic (A2C) in comparison to a classical rule-based agent (RBA). This framework not only aids in optimizing industrial processes but also provides a foundation for studying agent behavior and transferability in evolving environments, offering insights into model performance and practical implications for real-world RL applications.

Imran Riaz Hasrat, Eun-Young Kang, Christian Uldal Graulund

Safety and reliability are crucial in industrial drive systems, where hazardous failures can have severe consequences. Detecting and mitigating dangerous faults on time is challenging due to the stochastic and unpredictable nature of fault occurrences, which can lead to limited diagnostic efficiency and compromise safety. This paper optimizes the safety and diagnostic performance of a real-world industrial Basic Drive Module(BDM) using Uppaal Stratego. We model the functional safety architecture of the BDM with timed automata and formally verify its key functional and safety requirements through model checking to eliminate unwanted behaviors. Considering the formally verified correct model as a baseline, we leverage the reinforcement learning facility in Uppaal Stratego to optimize the safe failure fraction to the 90 % threshold, improving fault detection ability. The promising results highlight strong potential for broader safety applications in industrial automation.

Arun Achuthankutty, Rohith Saravanan, Hariesh Nagarajan et al.

Industries operating in extreme conditions demand materials with exceptional strength, fatigue resistance, corrosion resistance, and formability. While AA5052 alloy is widely used in such industries due to its high fatigue strength and corrosion resistance, its strength frequently falls short of stringent standards. For AA5052 alloy, this study explores the combined use of solutionizing and cryo-rolling, followed by annealing, to improve strength. Although several alloys have been reported to undergo solution treatment before cryo-rolling, this study focuses on how post-processing via annealing can lessen the formability constraints usually connected to conventional cryo-rolling. The study sheds light on the ways that solutionizing, cryo-rolling, and annealing interact to affect the alloy’s mechanical characteristics. Microstructure analysis shows that solutionizing improves the grain structure by reducing dynamic recovery, promoting dislocation density, and facilitating precipitate formation. Sheets subjected to solutionizing + cryo-rolling and partially annealed at 250 °C produce optimal results. Interestingly, formability is decreased when cryo-rolling alone is used instead of cold rolling, whereas formability is successfully increased when solutionizing is used. Comparing solutionized + cryo-rolled sheets that are partially annealed at 250 °C to cold-rolled sheets that are annealed at the same temperature, the former show notable quantitative improvements: a notable 17% increase in ultimate strength, a 10% boost in yield strength, and a noteworthy 13% enhancement in microhardness. Formability has improved with the solutionized + cryo-rolled specimens by annealing. This proposed approach led to noticeable gains in formability, hardness, and strength, which would significantly improve material performance for industrial applications.

Xiaoquan Lu, Kaijie Fang, Yuqi Zhou et al.

Abstract Based on the building thermodynamics model and the physical heat/cold conversion model of an air-conditioning system, this paper proposes a double-layer energy optimization model for a cement factory’s office building air-conditioning systems considering dynamic ambient temperature and the entire unit equipment. First, taking the envelope structure, outdoor air, and internal heat sources as the main subjects and considering the heat exchange between human skin and the envelope structure, a building thermal balance model and a refined calculation model of comfort were established. Secondly, the ground source heat pump is considered. A physical model of the operation of the air-conditioning system is set for the equipment, such as heat pumps, circulating water pumps, and variable frequency fans. Then, a two-layer comprehensive optimization model of the cement factory office building air-conditioning system was given based on system power consumption and comfort. The upper model dynamically adjusts the indoor set temperature to obtain the cooling load of the air-conditioning system; the lower model allocates the load rate based on the heat pump unit's performance to optimize the system's overall energy consumption. Finally, a typical case of a double-story model of a cement factory office building using the GA algorithm was compared and verified, showing the effectiveness of the proposed model.

Tian-Shu Liu, Peng Chen, Feng Qiu et al.

Lightweight aluminum (Al) alloys have been widely used in frontier fields like aerospace and automotive industries, which attracts great interest in additive manufacturing (AM) to process high-value Al parts. As a mainstream AM technique, laser-directed energy deposition (LDED) shows good scalability to meet the requirements for large-format component manufacturing and repair. However, LDED Al alloys are highly challenging due to their inherent poor printability (e.g. low laser absorption, high oxidation sensitivity and cracking tendency). To further promote the development of LDED high-performance Al alloys, this review offers a deep understanding of the challenges and strategies to improve printability in LDED Al alloys. The porosity, cracking, distortion, inclusions, element evaporation and resultant inferior mechanical properties (worse than laser powder bed fusion) are the key challenges in LDED Al alloys. Processing parameter optimizations, in-situ alloy design, reinforcing particle addition and field assistance are the efficient approaches to improving the printability and performance of LDED Al alloys. The underlying correlations between processes, alloy innovation, characteristic microstructures, and achievable performances in LDED Al alloys are discussed. The benchmark mechanical properties and primary strengthening mechanism of LDED Al alloys are summarized. This review aims to provide a critical and in-depth evaluation of current progress in LDED Al alloys. Future opportunities and perspectives in LDED high-performance Al alloys are also outlined.

Zhang Dong, Zou Qing, Zheng Yu et al.

Abstract The focus of this study is to optimize the exploration of biomass-driven multi-energy systems, which include combined heat, power, and gas generation. The objective is to enhance the thermal, environmental, and economic performance indicators of the system. The optimization objectives encompass the quantities of internal combustion engines and air source heat pumps, as well as the dimensions of tanks utilized for anaerobic fermentation. A mathematical model was developed to optimize multiple objectives for combined heat, power, and gas generation systems by employing multi-objective intelligent optimization algorithms. The validation and analysis were conducted using rural residences in Lanzhou, Gansu Province, China, as a case study. The sensitivity analysis of biomass gasification combined heat and power systems was conducted from both technical and cost perspectives, examining the dynamic impact characteristics on the outcomes of multi-objective optimization. The findings indicate that the annual energy-saving rate of the optimized combined generation system decreased from 3.62% to -6.78%, while the growth in carbon emissions reduction rate increased from 76.05 to 81.38%, and the annual cost-saving rate grew from 0.97 to 14.96%. The power generation efficiency of the cogeneration station and hydraulic retention time were found to have a significant impact on the multi-objective optimization results of the combined generation system among the technical parameters. The unit cost of anaerobic fermentation tanks had a more significant impact on the multi-objective optimization results in terms of cost parameters, compared to the price of biogas residue.

Yoel R. Cortés‐Peña, William Woodruff, Shivali Banerjee et al.

Abstract Oilcane—an oil‐accumulating crop engineered from sugarcane—and microbial oil have the potential to improve renewable oil production and help meet the expected demand for bioderived oleochemicals and fuels. To assess the potential synergies of processing both plant and microbial oils, the economic and environmental implications of integrating microbial oil production at oilcane and sugarcane biorefineries were characterized. Due to decreased crop yields that lead to higher simulated feedstock prices and lower biorefinery capacities, current oilcane prototypes result in higher costs and carbon intensities than microbial oil from sugarcane. To inform oilcane feedstock development, we calculated the required biomass yields (as a function of oil content) for oilcane to achieve financial parity with sugarcane. At 10 dw% oil, oilcane can sustain up to 30% less yield than sugarcane and still be more profitable in all simulated scenarios. Assuming continued improvements in microbial oil production from cane juice, achieving this target results in a minimum biodiesel selling price of 1.34 [0.90, 1.85] USD∙L−1 (presented as median [5th, 95th] percentiles), a carbon intensity of 0.51 [0.47, 0.55] kg CO2e L−1, and a total biodiesel yield of 2140 [1870, 2410] L ha−1 year−1. Compared to biofuel production from soybean, this outcome is equivalent to 3.0–3.9 as much biofuel per hectare of land and a 57%–63% reduction in carbon intensity. While only 20% of simulated scenarios fell within the market price range of biodiesel (0.45–1.11 USD∙L−1), if the oilcane biomass yield would improve to 25.6 DMT∙ha−1∙y−1 (an equivalent yield to sugarcane) 87% of evaluated scenarios would have a minimum biodiesel selling price within or below the market price range.

Binh Thi Thanh Dang, Wang Yawei, Abdul Jabbar Abdullah

Purpose – The study attempts to examine the impact of the US-China trade war on Vietnamese exports to the United States, which has consistently served as a key market for Vietnamese goods and services in recent decades. The heterogeneous effects of the trade war on different export sectors are also evaluated. Design/methodology/approach – The secondary data on Vietnamese exports to the US at a 6-digit level is collected from UN Comtrade. Besides, the difference-in-differences (DiD) method is employed to analyze the impact of the trade war on exports from Vietnam to the United States. Findings – The findings revealed a 14% increase in total Vietnamese exports to the United States due to the trade war. Examining heterogeneous effects, certain industries, such as plastics, iron or steel articles, textiles and garments, and machinery and mechanical appliances, experience significant benefits. However, the study did not identify statistically significant effects on other sectors, such as electrical machinery products, agricultural and forestry, and furniture. Originality/value – The paper is one among limited studies considering the causal effects of the trade war on a developing country, accounting for the heterogeneous effects on different export sectors.

Sotiris Michaelides, Stefan Lenz, Thomas Vogt et al.

The industrial landscape is undergoing a significant transformation, moving away from traditional wired fieldbus networks to cutting-edge 5G mobile networks. This transition, extending from local applications to company-wide use and spanning multiple factories, is driven by the promise of low-latency communication and seamless connectivity for various devices in industrial settings. However, besides these tremendous benefits, the integration of 5G as the communication infrastructure in industrial networks introduces a new set of risks and threats to the security of industrial systems. The inherent complexity of 5G systems poses unique challenges for ensuring a secure integration, surpassing those encountered with any technology previously utilized in industrial networks. Most importantly, the distinct characteristics of industrial networks, such as real-time operation, required safety guarantees, and high availability requirements, further complicate this task. As the industrial transition from wired to wireless networks is a relatively new concept, a lack of guidance and recommendations on securely integrating 5G renders many industrial systems vulnerable and exposed to threats associated with 5G. To address this situation, in this paper, we summarize the state-of-the-art and derive a set of recommendations for the secure integration of 5G into industrial networks based on a thorough analysis of the research landscape. Furthermore, we identify opportunities to utilize 5G to enhance security and indicate remaining challenges, identifying future academic directions.

Francesco Sanfedino, Paolo Iannelli, Daniel Alazard et al.

To overcome the innovation gap of the Guidance, Navigation and Control (GNC) design process between research and industrial practice a benchmark of industrial relevance has been developed and is presented. This initiative is driven as well by the necessity to train future GNC engineers and the GNC space community on a set of identified complex problems. It allows to demonstrate the relevance of state-of-the-art modeling, control and analysis algorithms for future industrial adoption. The modeling philosophy for robust control synthesis, analysis including the control architecture that enables the simulation of the mission, i.e. the acquisition of a high pointing space mission, are provided.

Srinjoy Mitra, Jean-Pierre Raskin

This paper discusses the importance of reflective and socially conscious education in engineering schools, particularly within the EE/CS sector. While most engineering disciplines have historically aligned themselves with the demands of the technology industry, the lack of critical examination of industry practices and their impact on justice, equality, and sustainability is self-evident. Today, the for-profit engineering/technology companies, some of which are among the largest in the world, also shape the narrative of engineering education and research in universities. As engineering graduates form the largest cohorts within STEM disciplines in Western countries, they become future professionals who will work, lead, or even establish companies in this industry. Unfortunately, the curriculum within engineering education often lacks a deep understanding of social realities, an essential component of a comprehensive university education. Here we establish this unusual connection with the industry that has driven engineering higher education for several decades and its obvious negative impacts to society. We analyse this nexus and highlight the need for engineering schools to hold a more critical viewpoint. Given the wealth and power of modern technology companies, particularly in the ICT domain, questioning their techno-solutionism narrative is essential within the institutes of higher education.

Jiayi He, Jiao Chen, Qianmiao Liu et al.

The Industrial Internet of Things (IIoT) integrates interconnected sensors and devices to support industrial applications, but its dynamic environments pose challenges related to data drift. Considering the limited resources and the need to effectively adapt models to new data distributions, this paper introduces a Continual Learning (CL) approach, i.e., Distillation-based Self-Guidance (DSG), to address challenges presented by industrial streaming data via a novel generative replay mechanism. DSG utilizes knowledge distillation to transfer knowledge from the previous diffusion-based generator to the updated one, improving both the stability of the generator and the quality of reproduced data, thereby enhancing the mitigation of catastrophic forgetting. Experimental results on CWRU, DSA, and WISDM datasets demonstrate the effectiveness of DSG. DSG outperforms the state-of-the-art baseline in accuracy, demonstrating improvements ranging from 2.9% to 5.0% on key datasets, showcasing its potential for practical industrial applications.