Hasil untuk "Industrial productivity"

Teng Li, Haoming Liu, A. Salvo

Leonardo José de Sousa Lima, Alexandre Santos Pimenta, Neyton de Oliveira Miranda et al.

The use of pesticides and bioinputs in agriculture is one of the most vital needs today to improve crop yields. A combination of pesticides and bioinputs, along with natural agents, is a viable solution to make agribusiness more eco-friendly. Wood vinegar (WV) is a recognized agricultural input that enhances plant growth and can act as a valuable agent for pest and disease control. The present research aimed to assess the boosting effect of blending insecticides and other bioinputs with a commercial WV, specifically SDfender, on soybean crop performance. The characteristics of WV industrial manufacturing were assessed. The chemical profile of WV was determined by gas chromatography/mass spectrometry (GC/MS). WV’s physical–chemical properties and the absence of contaminants were determined. Insecticides Galil SC and Expedition served as the standards, and Sulfite Max and Biokato served as the bioinputs. Average grain weight per plant (GWP), final stand, 1000-grain weight (TGW), and yield were determined. WV quality was acceptable, and no contaminants were detected. The WV organic fraction was composed of alcohols, furans, organic acids, phenolic compounds, and pyrans. Insecticides and bioinputs were more effective when combined with WV. No significant differences were detected among treatments for average grain weight or final stand. The TGW was highest for the combination of Galil SC, Expedition, and WV. This treatment also resulted in the highest soybean productivity (4259 kg ha−1). Adding WV to conventional insecticides and bioinputs can improve soybean crop performance, thereby increasing the use of natural products in agriculture.

Hailiang Zhao, Ziqi Wang, Daojiang Hu et al.

The convergence of artificial intelligence, cyber-physical systems, and cross-enterprise data ecosystems has propelled industrial intelligence to unprecedented scales. Yet, the absence of a unified trust foundation across data, services, and knowledge layers undermines reliability, accountability, and regulatory compliance in real-world deployments. While existing surveys address isolated aspects, such as data governance, service orchestration, and knowledge representation, none provides a holistic, cross-layer perspective on trustworthiness tailored to industrial settings. To bridge this gap, we present \textsc{Trisk} (TRusted Industrial Data-Service-Knowledge governance), a novel conceptual and taxonomic framework for trustworthy industrial intelligence. Grounded in a five-dimensional trust model (quality, security, privacy, fairness, and explainability), \textsc{Trisk} unifies 120+ representative studies along three orthogonal axes: governance scope (data, service, and knowledge), architectural paradigm (centralized, federated, or edge-embedded), and enabling technology (knowledge graphs, zero-trust policies, causal inference, etc.). We systematically analyze how trust propagates across digital layers, identify critical gaps in semantic interoperability, runtime policy enforcement, and operational/information technologies alignment, and evaluate the maturity of current industrial implementations. Finally, we articulate a forward-looking research agenda for Industry 5.0, advocating for an integrated governance fabric that embeds verifiable trust semantics into every layer of the industrial intelligence stack. This survey serves as both a foundational reference for researchers and a practical roadmap for engineers to deploy trustworthy AI in complex and multi-stakeholder environments.

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.

Abbas َAsadi, safanaz Heidari

<p style="text-align: left;"><strong>Abstract:</strong></p> <p style="text-align: left;">This research was conducted with the aim of examining the relationship among supply environment, supply chain integration, and performance considering opportunistic behaviors. This research employed a goal-oriented approach and utilized a descriptive-correlational design for its data collection procedure.</p> <p style="text-align: left;">The required data in this study were collected using a questionnaire. The statistical population was all the engineers and managers active in the manufacturing companies located in the industrial town number one of Arak. From among the statistical population of 230 individuals, a sample of 140 participants was obtained using the Cochran sampling method. They were selected through random sampling. The data were analyzed using the Partial Least Squares (PLS) technique, employing SmartPLS software for the analysis. The obtained results showed that there is a significant relationship between supply environment, supply chain integration and performance. However, the mediating role of opportunistic behaviors did not demonstrate a significant relationship, leading to the rejection of the hypothesis.</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;"><strong>Key Words:</strong> supply environment, supply chain integration, environmental performance, opportunistic behaviors</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;">&nbsp;</p> <p style="text-align: left;"><strong>1.Introduction</strong></p> <p style="text-align: left;">Waste of resources in a supply chain occurs due to the opportunistic tendencies of its members. Curbing the opportunistic tendencies of influential members who take unfair advantage of weaker organizations helps to reduce the resource consumption of weaker parties in the supply chain. Transaction costs also affect the way organizations interact with each other and cause organizations to show opportunistic behavior in order to maximize their profits. Supply chain integration is based on supply chain management concepts and considers the supply chain as an integrated system. It also focuses on sustainable performance and subsequently includes strategic and executive elements. This view of supply chain performance has led to the emergence of a supply chain management research domain called supply chain orientation. Supply chain orientation is based on the view that the organization's supply chain is an independent entity and focuses on achieving results within the supply chain that lead to better performance. So far, the relationship between supply environment, supply chain integration and performance considering opportunistic behaviors has not been considered. Is there a relationship between supply environment, supply chain integration and performance considering opportunistic behaviors or not? Identifying this relationship will provide an opportunity for future research to consider the effect of supply chain orientation on other supply chain functions and external performance outcomes. Based on this and according to the said contents, the main purpose of this research is to examine the relationship between supply environment, supply chain integration and performance by considering opportunistic behaviors.</p> <p style="text-align: left;"><strong>2.Literature Review</strong></p> <p style="text-align: left;">The findings of Nasri Rad's research (2015) showed a positive significant impact of the company's orientations on the sustainability of the supply chain. Among the dimensions of the company's orientation, two dimensions of environmental orientation and cultural orientation had a positive significant effect on sustainable purchasing and sustainable supply procedures. However, the two dimensions of social orientation and regional orientation did not have a significant effect on sustainable purchasing and sustainable supply practices. The results of the data analysis in the research conducted by Mehrabani and Hassanzadeh Farashband (2014) showed that the direction of the supply chain and the relationship management variable with the main supplier have an effect on the effectiveness of organizational purchasing. The results of the structural equation model in the research conducted by Taghizadeh Yazdi and Zulfi (2014) revealed a positive significant causal relationship between supply chain actions and competitive advantage. Also, the direct and indirect relationship between supply chain actions and sustainability was confirmed. Li and Nam (2016) showed in their research that organizational supply chain orientation has a significant effect on supply chain management and that it is also affected by management supply chain orientation. On the other hand, operational supply chain management is only affected by supply chain orientation information technology. Structural supply chain orientation also moderates the role of strategic supply chain orientation in meeting customer needs. Luzini (2015) demonstrated in his research that supply chain collaboration improves business performance; the market, performance, value and cooperation of the supply chain positively affects the financial performance; and the cooperation capabilities between companies have a positive significant impact on the company's business performance. Also, the cooperation of upstream and downstream members of the chain can support different forms of business. In their study, Esper et al. (2010) showed that the strategy and orientation of the structural supply chain can be effective in realizing the organization's goal of increasing organizational advantages. Finally, Gold et al. (2010), in their study, revealed that the strategic and structural dimensions of supply chain orientation help to improve supply chain cooperation and its combined effect is greater especially in uncertain dynamic environments.</p> <p style="text-align: left;"><strong>3.Methodology</strong></p> <p style="text-align: left;">The methodology employed in this research is grounded in applied research principles. The purpose of this research was to test theoretical concepts in real-world situations and address practical problems to improve the processes or products. The statistical population of the present study consisted of all the engineers and managers active in the manufacturing companies located in the industrial town of Arak, 140 of whom were selected as the sample of the study through available sampling. The current research has two distinct phases in the data collection and analysis. In the first phase, the data was analyzed using descriptive and inferential statistics methods. In descriptive statistics, mean, standard deviation and frequency tables are used. Then, inferential statistics are employed to explain the relationships between variables and generalize the results to the society. Cronbach's alpha test is used to determine reliability, and Lisrel software and structural equation model are used to confirm or reject each hypothesis.</p> <p style="text-align: left;"><strong>4.Result</strong></p> <p style="text-align: left;">Initially, library studies were used to review the necessary theoretical literature in the field under investigation and then, the information needed for this research was collected through a questionnaire. The statistical population of the current research was all the engineers and managers active in the manufacturing companies located in the industrial town of Arak. Form among the statistical population of 230 individuals, a sample equal to 140 participants was recruited through random sampling. To analyze the data, partial least squares technique was used, employing SmartPLS software. The obtained results showed that there is a significant relationship between supply environment, supply chain integration and performance. However, the mediating role of opportunistic behaviors was rejected. This hypothesis was composed of some sub-hypotheses.&nbsp; The results obtained for testing each of these sub-hypotheses are as follows: The results obtained from the t-statistic at the rate of 9.193 showed that there is a significant relationship between the supply environment and the integrity of the supply chain; the results obtained from the statistic t at the rate of 8.094 showed that there is a significant relationship between supply chain integration and productivity; the results obtained from the t statistic at the rate of 23.703 revealed that operational profit has a significant relationship with environmental performance; and the results obtained from the t-statistic at the rate of 1.118 rejected the mediating role of opportunistic behaviors within the work environment regarding the influence of supply chain integration on operational productivity.</p> <p style="text-align: left;"><strong>5.Discussion</strong></p> <p style="text-align: left;">In a supply chain, waste of resources arises from the opportunistic tendencies of its members. By curbing the opportunistic tendencies of influential members who exploit unfair advantages over weaker organizations helps to reduce the resource consumption of weaker parties in the supply chain. Therefore, it is suggested that industries, after adopting the appropriate supply chain strategy, in order to examine the correctness of this strategy and achieve the goals corresponding to that strategy, seek integration in the supply chain of their organization and its development. By holding training courses, managers and officials should increase the chain members' knowledge about the factors affecting the supply chain management of the project to enhance operational efficiency. This can be achieved by outlining a series of actions related to social responsibility towards the environment and employees, which may include: increased attention and investment in training employees focusing on skill development and behavioral improvement, determining rewards and welfare facilities appropriate to the performance of employees, career development and the possibility of promotion at all organizational levels, equality and job justice at all organizational levels, involving employees in decision-making, creating a cheerful, clean and safe environment for employees, and improving productivity and accordingly, performance in this environment.</p> <p style="text-align: left;">&nbsp;</p>

Emine Karaçayır

Amaç: Bu çalışmanın amacı, Türkiye’de 2005-2023 yılları arasında Borsa İstanbul BIST Temettü Endeksi’nde faaliyetlerine devam eden şirketlerin finansal esnekliğinin yatırım verimliliği üzerindeki etkisini araştırmaktır.Yöntem: Borsa İstanbul Temettü Endeksi’nde faaliyet gösteren 89 şirketin 2005-2023 dönemi verileri kullanılarak panel veri analizi gerçekleştirilmiştir. Bağımlı değişkenin gecikmeli değerlerinin bulunması nedeniyle dinamik panel veri modeli kullanılmış ve Genelleştirilmiş Momentler Metodu (GMM) modeli tercih edilmiştir. Finansal esnekliği ölçmek için kullanılan yedek borç kapasitesi yönteminde üç yıl aralıksız finansal esnekliğe sahip olan şirketlere bir sonraki dönem için finansal esnekliğe sahip olması durumunda “1” değerinin verildiği, tersi durumda ise “0” değerinin verildiği kukla değişkeni oluşturulmuş, bu değişken aynı zamanda finansal esneklik değişkeni olarak kullanılmıştır. Bulgular: Şirketlerin, yatırımlarını yedek borç kapasitelerini kullanarak artırabildiği ve bu sayede yatırımlarını daha etkin bir şekilde yönetebildiği görülmüştür. Aynı zamanda finansal esnekliği yüksek olan şirketlerin yatırımlarını artırarak daha verimli sonuçlar elde ettiği tespit edilmiştir.Özgünlük: Genel olarak finansal esneklik ve firma performansı arasındaki ilişki ve finansal esnekliğin; varlık yapısı, sermaye yapısı ve kar dağıtım politikaları ile olan ilişki araştırılmıştır. Bu çalışmada finansal esnekliğin yatırım verimliliği üzerine etkiyi araştırılmıştır.

Yangfan Cao, Wei Chong Choo, Bolaji Tunde Matemilola

The recent rise in deep learning and natural language processing (NLP) applications has notably improved productivity across different fields. This research aims to refine Value-at-Risk (VaR) model accuracy by leveraging text mining and deep learning. It first uses NLP to analyze online news sentiments, integrating these as variables to boost stock market risk forecasts and assess their effect on VaR accuracy. Additionally, the study combines predictions from four unique Generalized AutoRegressive Conditional Heteroskedasticity (GARCH)-type models into advanced Long Short-Term Memory (LSTM) and Convolutional Neural Network (CNN)-LSTM models to see if this boosts VaR precision. It also explores how textual data impacts VaR predictions over short and longer periods, using 7 and 20-day rolling windows. The analysis, using S&P500 (SPY), Dow Jones Industrial Average (DJI), and Nasdaq Composite (IXIC) data from 2012 to 2023 alongside news headlines, tests these approaches. The results confirm that incorporating textual information into the VaR model enhances its forecasting accuracy, highlighting the benefits of applying deep learning techniques in this process.

Yindu Su, Huike Zou, Lin Sun et al.

Product Attribute Value Identification (PAVI) involves identifying attribute values from product profiles, a key task for improving product search, recommendation, and business analytics on e-commerce platforms. However, existing PAVI methods face critical challenges, such as inferring implicit values, handling out-of-distribution (OOD) values, and producing normalized outputs. To address these limitations, we introduce Taxonomy-Aware Contrastive Learning Retrieval (TACLR), the first retrieval-based method for PAVI. TACLR formulates PAVI as an information retrieval task by encoding product profiles and candidate values into embeddings and retrieving values based on their similarity. It leverages contrastive training with taxonomy-aware hard negative sampling and employs adaptive inference with dynamic thresholds. TACLR offers three key advantages: (1) it effectively handles implicit and OOD values while producing normalized outputs; (2) it scales to thousands of categories, tens of thousands of attributes, and millions of values; and (3) it supports efficient inference for high-load industrial deployment. Extensive experiments on proprietary and public datasets validate the effectiveness and efficiency of TACLR. Further, it has been successfully deployed on the real-world e-commerce platform Xianyu, processing millions of product listings daily with frequently updated, large-scale attribute taxonomies. We release the code to facilitate reproducibility and future research at https://github.com/SuYindu/TACLR.

Chaoran Zhang, Chenhao Zhang, Zhaobo Xu et al.

The combination of embodied intelligence and robots has great prospects and is becoming increasingly common. In order to work more efficiently, accurately, reliably, and safely in industrial scenarios, robots should have at least general knowledge, working-environment knowledge, and operating-object knowledge. These pose significant challenges to existing embodied intelligent robotics (EIR) techniques. Thus, this paper first briefly reviews the history of industrial robotics and analyzes the limitations of mainstream EIR frameworks. Then, a new knowledge-driven technical framework of embodied intelligent industrial robotics (EIIR) is proposed for various industrial environments. It has five modules: a world model, a high-level task planner, a low-level skill controller, a simulator, and a physical system. The development of techniques related to each module are also thoroughly reviewed, and recent progress regarding their adaption to industrial applications are discussed. A case study of real-world assembly system is given to demonstrate the newly proposed EIIR framework's applicability and potentiality. Finally, the key challenges that EIIR encounters in industrial scenarios are summarized and future research directions are suggested. The authors believe that EIIR technology is shaping the next generation of industrial robotics and EIIR-based industrial systems supply a new technological paradigm for intelligent manufacturing. It is expected that this review could serve as a valuable reference for scholars and engineers that are interested in industrial embodied intelligence. Together, scholars can use this research to drive their rapid advancement and application of EIIR techniques. The authors would continue to track and contribute new studies in the project page https://github.com/jackyzengl/EIIR

Muhammad Junaid Asif, Abdul Rehman, Asim Mehmood et al.

This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technology based on wireless communication. We proposed a system based on NRF transceivers to establish a strong Wireless Sensor Network (WSN), enabling transfer of real-time data from multiple sensors to a central setup that is driven by ARDUINO microcontrollers. Different key parameters, crucial for industrial setup such as temperature, humidity, soil moisture and fire detection, are monitored and displayed on an LCD screen, enabling factory administration to oversee the industrial operations remotely over the internet. Our proposed system bypasses the need for physical presence for monitoring by addressing the shortcomings of conventional wired communication systems. Other than monitoring, there is an additional feature to remotely control these parameters by controlling the speed of DC motors through online commands. Given the rising incidence of industrial fires over the worldwide between 2020 and 2024 due to an array of hazards, this system with dual functionality boosts the overall operational efficiency and safety. This overall integration of IoT and Wireless Sensor Network (WSN) reduces the potential risks linked with physical monitoring, providing rapid responses in emergency scenarios, including the activation of firefighting equipment. The results show that innovations in wireless communication perform an integral part in industrial process automation and safety, paving the way to more intelligent and responsive operating environments. Overall, this study highlights the potential for change of IoT-enabled systems to revolutionize monitoring and control in a variety of industrial applications, resulting in increased productivity and safety.

Rhea Aqueel, Asma Maqbool, Kauser Abdulla Malik

The field of genetic engineering and molecular breeding utilizes maize immature embryos for transformation studies. However, there are hinderances such as the unavailability of immature embryos throughout the year and their low transformation frequencies which make them unsuitable for use at a commercial level. Among cereals, maize has prime importance due to its productivity, industrial products, animal feed and fodder. Regeneration capability in maize transformation studies varies due to differences in genetic makeup and explant source. In this study, we evaluate mature embryos as explants for in vitro plant regeneration. Six varieties including 3 hybrid lines (Pioneer 3025, SG 2002 and Neelam) and 3 inbred lines (NCML 107, CML 161 and FBF 3368) were screened for Agrobacterium mediated transformation amenability using mature maize embryos. The two inbred lines NCML 107 and CML 161 performed best showing 100% callus induction frequency, 93.33% and 86.66% transient GUS expression, and 43.75% and 13.3% regeneration frequency, respectively. Using split seed as an explant, better regeneration was observed in NCML 107 (14.86%) and CML 161 (7.5%) as compared to mature embryos, NCML 107 (10%) and CML 161 (2%). Here we report successful plant regeneration (regeneration medium supplemented with Kinetin + BAP) using split seeds as an explant. Our results demonstrate the capability of two elite maize inbred lines (NCML 107 & CML 161) for their amenability to Agrobacterium mediated transformation and better tissue culture response; hence can be selected in maize transformation studies for improving crop varieties for enhanced nutritional content and better adaptation.

Gabriele Valvano, Antonino Agostino, Giovanni De Magistris et al.

Training supervised deep neural networks that perform defect detection and segmentation requires large-scale fully-annotated datasets, which can be hard or even impossible to obtain in industrial environments. Generative AI offers opportunities to enlarge small industrial datasets artificially, thus enabling the usage of state-of-the-art supervised approaches in the industry. Unfortunately, also good generative models need a lot of data to train, while industrial datasets are often tiny. Here, we propose a new approach for reusing general-purpose pre-trained generative models on industrial data, ultimately allowing the generation of self-labelled defective images. First, we let the model learn the new concept, entailing the novel data distribution. Then, we force it to learn to condition the generative process, producing industrial images that satisfy well-defined topological characteristics and show defects with a given geometry and location. To highlight the advantage of our approach, we use the synthetic dataset to optimise a crack segmentor for a real industrial use case. When the available data is small, we observe considerable performance increase under several metrics, showing the method's potential in production environments.

Rafal Noga, Xaver Paulig, Lukas Schmidt et al.

Skysails Power GmbH is the leading manufacturer of light and efficient power kites that harness the wind's untapped supplies at high altitudes, aiming at profoundly altering wind energy's impact in achieving the global energy transition. Novel, variable trim kites have been developed that allow to modulate the aerodynamic coefficients of the airborne system, significantly improving the overall system efficiency. The flight control of variable trim kites is much more complex than that of previous kite generations and its mastering is a challenge and one of the keys to a successful operation. Numerical optimization is applied to find a set of flight trajectories in order to maximize the energy production while satisfying several constraints on the system operating in a wide range of conditions. This industry abstract provides a general introduction of the trajectory optimization problem with variable trim kites. We also briefly introduce the state-of-the-art optimization setup. This is followed by demonstration of high-quality example results of the optimization. Finally, we discuss the results and their applications.

Zainab Alwaisi, Simone Soderi, Rocco De Nicola

Internet of Everything (IoE) is a newly emerging trend, especially in homes. Marketing forces toward smart homes are also accelerating the spread of IoE devices in households. An obvious risk of the rapid adoption of these smart devices is that many lack controls for protecting the privacy and security of end users from attacks designed to disrupt lives and incur financial losses. Today the smart home is a system for managing the basic life support processes of both small systems, e.g., commercial, office premises, apartments, cottages, and largely automated complexes, e.g., commercial and industrial complexes. One of the critical tasks to be solved by the concept of a modern smart home is the problem of preventing the usage of IoE resources. Recently, there has been a rapid increase in attacks on consumer IoE devices. Memory corruption vulnerabilities constitute a significant class of vulnerabilities in software security through which attackers can gain control of an entire system. Numerous memory corruption vulnerabilities have been found in IoE firmware already deployed in the consumer market. This paper aims to analyze and explain the resource usage attack and create a low-cost simulation environment to aid in the dynamic analysis of the attack. Further, we perform controlled resource usage attacks while measuring resource consumption on resource-constrained victims' IoE devices, such as CPU and memory utilization. We also build a lightweight algorithm to detect memory usage attacks in the IoE environment. The result shows high efficiency in detecting and mitigating memory usage attacks by detecting when the intruder starts and stops the attack.

Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy et al.

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamlessly integrates real-world systems with their virtual counterparts, bridging the physical and digital realms. In this article, we present a comprehensive survey of the emerging DT-enabled services and applications across industries, beginning with an overview of DT fundamentals and its components to a discussion of key enabling technologies for DT. Different from literature works, we investigate and analyze the capabilities of DT across a wide range of industrial services, including data sharing, data offloading, integrated sensing and communication, content caching, resource allocation, wireless networking, and metaverse. In particular, we present an in-depth technical discussion of the roles of DT in industrial applications across various domains, including manufacturing, healthcare, transportation, energy, agriculture, space, oil and gas, as well as robotics. Throughout the technical analysis, we delve into real-time data communications between physical and virtual platforms to enable industrial DT networking. Subsequently, we extensively explore and analyze a wide range of major privacy and security issues in DT-based industry. Taxonomy tables and the key research findings from the survey are also given, emphasizing important insights into the significance of DT in industries. Finally, we point out future research directions to spur further research in this promising area.

Marco Bortolini

Palamarenko Yana V. , Chikov Illia A.

The issue of recycling waste from the main production is experiencing growing relevance and importance in the context of sustainable development and environmental protection. In today’s world, where environmental issues and conservation of natural resources are becoming extremely important, manufacturers and consumers are faced with the need to find new innovative approaches to waste management and reducing the negative impact of industrial processes on the environment. Therefore, the use of biogas plants is one of the promising solutions in this direction. These plants play an important role in reducing greenhouse gas emissions, using agricultural waste, improving the production cycle, and contributing to more sustainable and environmentally friendly production processes. This article reveals the importance of biogas plants as an innovative solution for addressing the issues of organic waste recycling along with creating more sustainable production. The article discusses the topical issue of assessing the efficiency of biogas plants, based on both domestic and foreign experience. The analysis of the efficiency of biogas plants is carried out on the basis of a comparison of domestic and international experience. Thus, the authors determine that in order to ensure a comprehensive assessment of the efficiency of biogas plants, it is necessary to thoroughly analyze technical parameters, technological solutions, economic aspects, and environmental indicators. The proposed multi-criteria approach will allow to obtain an exhaustive and objective assessment of the functioning of biogas plants, taking into account most of the key aspects of their efficiency. This will make it possible to determine the optimal areas for improving these plants in order to achieve the highest possible level of productivity and consistency of their operation. Further on, this approach will contribute to making sound managerial decisions and thus achieving a common goal in the modern energy paradigm. The authors propose to assess the efficiency of biogas plants by building a model based on fuzzy logic methods. This approach allows to take into account the ambiguity and uncertainty of incoming information, which gives the possibility to agree on different criteria and parameters, taking into account their unpredictability and dependence on many factors. The results of this model help in choosing the optimal biogas plant that meets the conditions and requirements of today.

Tianyu Zhang, Gang Wang, Chuanyu Xue et al.

With the introduction of Cyber-Physical Systems (CPS) and Internet of Things (IoT) technologies, the automation industry is undergoing significant changes, particularly in improving production efficiency and reducing maintenance costs. Industrial automation applications often need to transmit time- and safety-critical data to closely monitor and control industrial processes. Several Ethernet-based fieldbus solutions, such as PROFINET IRT, EtherNet/IP, and EtherCAT, are widely used to ensure real-time communications in industrial automation systems. These solutions, however, commonly incorporate additional mechanisms to provide latency guarantees, making their interoperability a grand challenge. The IEEE 802.1 Time Sensitive Networking (TSN) task group was formed to enhance and optimize IEEE 802.1 network standards, particularly for Ethernet-based networks. These solutions can be evolved and adapted for cross-industry scenarios, such as large-scale distributed industrial plants requiring multiple industrial entities to work collaboratively. This paper provides a comprehensive review of current advances in TSN standards for industrial automation. It presents the state-of-the-art IEEE TSN standards and discusses the opportunities and challenges of integrating TSN into the automation industry. Some promising research directions are also highlighted for applying TSN technologies to industrial automation applications.

Ankush Meshram, Markus Karch, Christian Haas et al.

Since 2010, multiple cyber incidents on industrial infrastructure, such as Stuxnet and CrashOverride, have exposed the vulnerability of Industrial Control Systems (ICS) to cyber threats. The industrial systems are commissioned for longer duration amounting to decades, often resulting in non-compliance to technological advancements in industrial cybersecurity mechanisms. The unavailability of network infrastructure information makes designing the security policies or configuring the cybersecurity countermeasures such as Network Intrusion Detection Systems (NIDS) challenging. An empirical solution is to self-learn the network infrastructure information of an industrial system from its monitored network traffic to make the network transparent for downstream analyses tasks such as anomaly detection. In this work, a Python-based industrial communication paradigm-aware framework, named PROFINET Operations Enumeration and Tracking (POET), that enumerates different industrial operations executed in a deterministic order of a PROFINET-based industrial system is reported. The operation-driving industrial network protocol frames are dissected for enumeration of the operations. For the requirements of capturing the transitions between industrial operations triggered by the communication events, the Finite State Machines (FSM) are modelled to enumerate the PROFINET operations of the device, connection and system. POET extracts the network information from network traffic to instantiate appropriate FSM models (Device, Connection or System) and track the industrial operations. It successfully detects and reports the anomalies triggered by a network attack in a miniaturized PROFINET-based industrial system, executed through valid network protocol exchanges and resulting in invalid PROFINET operation transition for the device.

Preethi, T. M. Mohamed Usman, Rajesh Banu Jeyakumar et al.

Abstract Biohydrogen production from industrial wastewater has been a focus of interest in recent years. The in depth knowledge in lab scale parameters and emerging strategies are needed to be investigated in order to implement the biohydrogen production process at large scale. The operating parameters have great influence on biohydrogen productivity. With the aim to gain major insight into biohydrogen production process, this review summarizes recent updates on dark fermentation, inoculum pretreatment methods, operating parameters (hydraulic retention time, organic loading rate, pH, temperature, volatile fatty acids, bioreactor configuration, nutrient availability, partial pressure etc.). The challenges and limitations associated with the biohydrogen production are lack of biohydrogen producers, biomass washout and accumulation of metabolites are discussed in detail. The advancement strategies to overcome these limitations are also briefly discussed.