Search

This research paper conducts a systematic review of the integration of blockchain technology with Enterprise Resource Planning (ERP) systems, a burgeoning field at the intersection of advanced technology and business management. The primary objective is to bridge the knowledge gap by synthesizing existing literature, providing insights into the current state, challenges, and potential of blockchain in enhancing ERP systems. The study follows a structured methodology involving four key stages: Literature Retrieval, Literature Screening, Biblio-metric Analysis, and Content Analysis. A comprehensive literature search in the Scopus database resulted in the identification and analysis of 250 scholarly articles, narrowed down to 66 relevant publications. The findings highlight a significant trend towards decentralized ERP solutions, driven by blockchain's promise of enhanced security, transparency, and efficiency. Key areas impacted by blockchain integration include supply chain management, accounting, security, traceability, purchasing, and process automation within ERP systems. The bibliometric analysis reveals a growing academic interest in this domain, with a focus on scalability, data security, and interoperability. However, the integration faces challenges such as technical complexity, cultural resistance, and regulatory uncertainties. The study concludes that while blockchain presents transformative opportunities for ERP systems, realizing this potential requires overcoming substantial technical and organizational hurdles. Future research should concentrate on developing scalable, interoperable blockchain solutions, tailored to specific industry needs and compliant with regulatory standards, thereby facilitating widespread adoption and maximizing the benefits of blockchain in ERP systems. [ABSTRACT FROM AUTHOR]

This study explores the application of the BPM lifecycle to optimize the market analysis process within the market intelligence department of a major energy company. The semi-structured, virtual nature of the process necessitated careful adaptation of BPM methodology, starting with process discovery through data collection, modeling, and validation. Qualitative analysis, including value-added and root-cause analysis, revealed inefficiencies. The redesign strategy focused on selective automation using Python 3.10 scripts and Power BI dashboards, incorporating techniques such as linear programming and forecasting to improve process efficiency and quality while maintaining flexibility. Post-implementation, monitoring through a questionnaire showed positive results, though ongoing interviews were recommended for sustained performance evaluation. This study highlights the value of BPM methodology in enhancing decision-critical processes and offers a model for adaptable, value-driven process improvements in complex organizational environments. [ABSTRACT FROM AUTHOR]

With the digital transformation of the construction industry, the need to improve construction business process collaboration and automation is increasing. However, as construction projects usually involve many stakeholders with complex relationships and insufficient mutual trust, the existing technologies cannot fulfill the requirements of the construction industry. This paper explores the integration of blockchain, smart contracts, and process automation technologies into construction business processes, shedding light on both managerial and technical challenges. The study introduces a comprehensive technical framework meticulously designed to align with the intricate nature of construction practices while focusing on the resolution of legal complexities associated with smart contract applications and the facilitation of process collaboration and automation. The framework comprises three core modules: (1) action definition and extension to process models, (2) standardized mapping for automatic smart contract generation, and (3) smart contract visualization for reliable process collaboration and automation. This multifaceted approach caters to the specific needs of construction management, standardization, interoperability, and visualization. The framework's practicality is further evaluated through real-world testing within a construction payment case, effectively showcasing its efficacy and applicability in tangible business scenarios. While this paper represents a significant step forward in addressing construction business process collaboration and automation challenges, it acknowledges the necessity for ongoing research and development to refine and expand these innovative solutions to meet the evolving demands of construction management. Practical Applications: Currently, there is a significant escalation in the severity of disputes within the construction industry. The adoption of blockchain technology allows for the redistribution of trust within a construction project, shifting reliance from individuals to the system itself for better collaboration and fewer disputes. Although blockchain can help foster a more secure and transparent environment, at the process level, an efficient workflow engine is needed to activate processes in this environment. Therefore, this study proposed an approach to generating smart contract codes based on construction business processes in a standardized way and further visually executing these codes for the processes with historical transactions stored in blockchain. This approach can reduce the effort of smart contract programming and improve the standardization and credibility of smart contract generation. It can also streamline the procedure from construction business process design to final execution via predefined and visual modules. Meanwhile, the generation prototype is open sourced to provide transparency and further enhance the approach. To indicate practical implications in the real world, this study provided a case of construction payment, but the solution is not limited to the payment scenario. [ABSTRACT FROM AUTHOR]

The so-called digital transformation of the construction industry is essential to overcoming long-standing global productivity stagnation. This transformation aims to adopt the latest technological developments and methodologies to improve construction productivity while supporting data-informed decision-making. However, the construction sector has fallen short of meeting the fast-growing population's demands for sustainable quality infrastructure at the required pace as it has not yet taken full advantage of these advancements. Despite broad experience in managing projects, when it comes to modeling, monitoring, and re-engineering processes, the construction industry has fallen behind several other industries. To overcome these challenges, efficient construction processes and operational strategies are essential to keeping organizations competitive and meeting market demands. In this regard, even though several studies on process modeling and management in construction exist, research on construction process improvement and automation through data-driven process mining remains understudied. Moreover, the literature lacks a comprehensive review of process-oriented studies with practical industry insights. To fill these gaps, this paper aims to provide an exhaustive analysis of process mining, modeling, and management as reported by the most current state of the literature in the architecture, engineering, construction/facility management (AEC/FM) domain coupled with a current industry perspective. As a result, the authors: (1) propose a conceptual process classification framework that considers the broad spectrum of process-oriented studies in the existing literature; (2) identify construction processes commonly present across a project's life cycle; (3) design and conduct structured interviews with subject matter experts to validate identified processes and get industry insights about them; (4) spot major literature gaps describing future research opportunities; and (5) develop a business process model canvas template that supports construction organizations in improving their corporate memory and pursuing construction productivity growth by better managing, monitoring, and automating construction processes. [ABSTRACT FROM AUTHOR]

The automotive industry is one of the most demanding sectors of all manufacturing industries due to its competitiveness. It is necessary to innovate through the implementation of automated and robotic equipment, leading to cycle time and labor cost reduction. This work aims to design semi-automatic equipment to assemble cabling connectors used in the automotive sector, replacing a manual process currently taking place in an automotive components company. In the proposed equipment, the operator places a connector in the equipment, and the components (pins and seals) are automatically inserted. A vision sensor with artificial intelligence then confirms the correct application. The equipment operation defined as Finite Element Method (FEM) was applied for structural verification; the materials and fabrication processes were detailed; the associated costs were calculated, and the equipment subsets were validated. The design was successfully accomplished, and the imposed requirements were fulfilled, with significant advantages over the current process, providing new knowledge on how semi-automatic systems can be deployed to enhance the productivity and quality of manufacturing processes. The design principles and insights gained from this work can be applied to other automation challenges, particularly where manual processes need to be replaced by more efficient semi-automatic or automatic systems. The modularity of the overall solution and the design concepts of the component inserter, component feeder, and assembly process allow for its use in different assembly scenarios beyond the automotive sector, such as electronics or aerospace, providing a contribution to increased competitiveness and survival in the global market. [ABSTRACT FROM AUTHOR]

The purpose of the article is to study the opportunities of innovative development of the Russian oil and gas complex amid current challenges. The subject of the article is modern features of functioning of the Russian oil and gas sector. As a methodology, it is necessary to high-light the analysis of Internet resources and articles relevant to the research topic, statistical data, their synthesis and generalisation. Among the main results of the work we will indicate structuring sanctions in terms of the direction of impact on innovation activities, identifying opportunities and prospects for innovative development of companies in the oil and gas sector in the current conditions. The results obtained can be applied as part of assessing the prospects with consideration to the modern situation and in the educational process. The directions for further research on a given topic include studying the operating features of companies of various sizes during their activities as well as identifying the most effective technological designs that can be used in the industry, including domestic ones. We have made the following main conclusions. Firstly, the impact of the sanctions is aimed largely at the technological development of oil and gas companies. Secondly, the prohibitive measures have stimulated the use and implementation of domestic innovations. Thirdly, the application of new decisions makes it possible to optimise the processes of the technological development, including those that until recently were determined to be unprofitable. Fourthly, innovations help to increase the number of organisations in the oil and gas sector by involving small-sized companies whose activities cover a minor segment that is not attractive to large corporations.

Agriculture is being transformed through automation and robotics to improve efficiency and reduce production costs. However, this transformation poses risks of job loss, particularly for low-skilled workers, as automation decreases the need for human labor. To adapt, the workforce must acquire new qualifications to collaborate with automated systems or shift to roles that leverage their unique human abilities. In this study, 15 agricultural occupations were methodically mapped in a cognitive/manual versus routine/non-routine two-dimensional space. Subsequently, each occupation's susceptibility to robotization was assessed based on the readiness level of existing technologies that can automate specific tasks and the relative importance of these tasks in the occupation's execution. The qualifications required for occupations less impacted by robotization were summarized, detailing the specific knowledge, skills, and work styles required to effectively integrate the emerging technologies. It was deduced that occupations involving primary manual routine tasks exhibited the highest susceptibility rate, whereas occupations with non-routine tasks showed lower susceptibility. To thrive in this evolving landscape, a strategic combination of STEM (science, technology, engineering, and mathematics) skills with essential management, soft skills, and interdisciplinary competences is imperative. Finally, this research stresses the importance of strategic preparation by policymakers and educational systems to cultivate key competencies, including digital literacy, that foster resilience, inclusivity, and sustainability in the sector. [ABSTRACT FROM AUTHOR]

The methodology for production of biologics is going through a paradigm shift from batch‐wise operation to continuous production. Lot of efforts are focused on integration, intensification, and continuous operation for decreased foot‐print, material, equipment, and increased productivity and product quality. These integrated continuous processes with on‐line analytics become complex processes, which requires automation, monitoring, and control of the operation, even unmanned or remote, which means bioprocesses with high level of automation or even autonomous capabilities. The development of these digital solutions becomes an important part of the process development and needs to be assessed early in the development chain. This work discusses a platform that allows fast development, advanced studies, and validation of digital solutions for integrated continuous downstream processes. It uses an open, flexible, and extendable real‐time supervisory controller, called Orbit, developed in Python. Orbit makes it possible to communicate with a set of different physical setups and on the same time perform real‐time execution. Integrated continuous processing often implies parallel operation of several setups and network of Orbit controllers makes it possible to synchronize complex process system. Data handling, storage, and analysis are important properties for handling heterogeneous and asynchronous data generated in complex downstream systems. Digital twin applications, such as advanced model‐based and plant‐wide monitoring and control, are exemplified using computational extensions in Orbit, exploiting data and models. Examples of novel digital solutions in integrated downstream processes are automatic operation parameter optimization, Kalman filter monitoring, and model‐based batch‐to‐batch control. [ABSTRACT FROM AUTHOR]

The article discusses emerging technologies in information systems project management. Project management is a modern discipline that began to take shape from 1900 and has evolved and adapted to the needs of society and business. Emerging technologies such as artificial intelligence, blockchain, augmented and virtual reality, and process automation are transforming the way information systems projects are managed. These technologies can be used to analyze large amounts of data, ensure data integrity and security, visualize a project's design and perform virtual testing, and automate tasks to reduce project time and cost. It is important for companies to be aware of these technologies and use them effectively to improve the efficiency and profitability of their projects. [ABSTRACT FROM AUTHOR]

This article deals with project management in information systems, whose relevance lies in the vital importance of these systems in modern companies. Information systems are essential for decision making and data management in today's interconnected world. Project management, on the other hand, coordinates elements such as scope, resources, costs, schedules and risks to achieve defined objectives. The systems development life cycle (SDLC) structures the process, encompassing phases such as scope definition, planning, execution, monitoring and closure. These phases are integrated with risk management, which identifies, evaluates and mitigates threats and opportunities. Mitigation strategies act before adversity, while contingency planning prepares for the unforeseen. That is why risk management is integrated throughout the project life cycle to anticipate and address challenges. The combination of both aspects is critical in a constantly evolving technology environment. In addition, organizational culture and communication play a critical role. A culture of awareness and accountability, transparency in communication and active stakeholder participation are essential. Training and continuous adaptation allow learning from past experiences and improving practices. [ABSTRACT FROM AUTHOR]

Due to its high complexity and the varied assembly processes, hybrid assembly systems characterized by human–robot collaboration (HRC) are meaningful. Suitable use cases must be identified efficiently to ensure cost-effectiveness and successful deployment in the respective assembly systems. This paper presents a method for evaluating the potential of HRC to derive automation suitability based on existing or to-be-collected time data. This should enable a quick and favorable statement to be made about processes, for efficient application in potential analyses. The method is based on the Methods–Time–Measurement Basic System (MTM-1) procedure, widely used in the industry. This ensures good adaptability in an industrial context. It extends existing models and examines how much assembly activities and processes can be optimized by efficiently allocating between humans and robots. In the process model, the assembly processes are subdivided and analyzed with the help of the specified MTM motion time system. The suitability of the individual activities and sub-processes for automation are evaluated based on criteria derived from existing methods. Two four-field matrices were used to interpret and classify the analysis results. The process is assessed using an example product from electrolyzer production, which is currently mainly assembled by hand. To achieve high statement reliability, further work is required to classify the results comprehensively.

Purpose: The paper aims to present implementation of RPA (Robotic Process Automation) into the BPM (Business Process Management) Lifecycle to systematize the application of robotic solutions in process management. Design/methodology/approach: By exploring BPM lifecycle principles and components, RPA methods, and the APQC® framework, an integrated BPM-RPA model was developed. The components of the BPM-RPA model were defined along with the necessary documentation. Findings: The proposed model presents a systematic approach to RPA implementation by integrating it into the business process management model. A case study was conducted in a large network organization, and the results are presented. Research limitations/implications: The model was designed for large network organizations and their branches and functional directorates. Practical implications: The BPM-RPA model can be adapted to various supportive/back-office processes and applied across multiple industries. Originality/value: This paper emphasizes the importance of linking RPA with the foundational process management model within an organization. [ABSTRACT FROM AUTHOR]

An analysis of the operation of the piercing mill revealed the need to upgrade the mechatronic rolls positioning system and to introduce an intelligent system to improve the quality of rolled products. The main problem is the formation of defects at the ends of the shells during rolling on a piercing mill. The excess material must be cut off and recycled because more raw materials than required are used for rolling one billet. To eliminate this problem, it is necessary to change the preload of the workpiece during rolling, thereby forming a profile that reduces the undesirable changes at the ends of rolled pipes. The mill currently has foreign equipment which is difficult to purchase. Such difficulties may lead to downtime. Moreover, the unit operates only in manual or semi-automatic mode. The possibility of replacing equipment with domestic analogs is considered. A visualization and control program has been developed. To determine the position of the workpiece in the mill and change the preload of the shell in automatic mode, a neural-network control system has been developed. [ABSTRACT FROM AUTHOR]

Global pandemics, military conflicts, and natural disasters are crescively disrupting increasingly complex supply chains. But neither the social science of economics or decision science of supply chain management were sufficient to anticipate, much less mitigate the depth, breadth, or duration of the disruptions and damage wrought by COVID-19 or Russia's invasion of Ukraine. Economics is the study of production, distribution, and consumption of goods and services, and creation and transfer of wealth. Supply chain management is the management of a network of organizations, internal and external, by which an organization pursues its own goals and objectives. Process focus is integral to supply chain management, as operations management is the management of an organization's processes to pursue its goals and objectives. Adherence to processes is necessary for organizations to consistently reach their goals and objectives. When organizations execute consistently, they can leverage that quality for lower costs, greater volume, higher prices, or additional stakeholder goodwill. By combining these concepts, supply chain economics can be framed as the systematic study of the production, distribution, and consumption of goods, services, and capital by networks of organizations, internal and external, with which any given organization pursues its goals and objectives. [ABSTRACT FROM AUTHOR]

Curating and integrating data from sources are bottlenecks to procuring robust training datasets for artificial intelligence (AI) models in healthcare. While numerous applications can process discrete types of clinical data, it is still time-consuming to integrate heterogenous data types. Therefore, there exists a need for more efficient retrieval and storage of curated patient data from dissimilar sources, such as biobanks, health records, and sensors. We describe a customizable, modular data retrieval application (RIL-workflow), which integrates clinical notes, images, and prescription data, and show its feasibility applied to research at our institution. It uses the workflow automation platform Camunda (Camunda Services GmbH, Berlin, Germany) to collect internal data from Fast Healthcare Interoperability Resources (FHIR) and Digital Imaging and Communications in Medicine (DICOM) sources. Using the web-based graphical user interface (GUI), the workflow runs tasks to completion according to visual representation, retrieving and storing results for patients meeting study inclusion criteria while segregating errors for human review. We showcase RIL-workflow with its library of ready-to-use modules, enabling researchers to specify human input or automation at fixed steps. We validated our workflow by demonstrating its capability to aggregate, curate, and handle errors related to data from multiple sources to generate a multimodal database for clinical AI research. Further, we solicited user feedback to highlight the pros and cons associated with RIL-workflow. The source code is available at github.com/magnooj/RIL-workflow. [ABSTRACT FROM AUTHOR]

Technology is needed in the process of collecting data, information, and activities to reduce the use of paper or paperless. According to OJK, a Financing Institution is a business entity that carries out financing activities in the form of providing funds or capital goods. Some of the benefits of IT strategy Making a roadmap for IT development and development related to infrastructure, application systems, services, and information security. With the data and information that can be collected, can be managed and used in decision-making through an analysis that can be used in looking at the policies and strategic decisions of the organization. With the IT strategy, companies can have strategies in securing data and system management in the organization, in particular, it can be used to segment the market and determine business focus to increase added value that can be provided to consumers or debtors. From making a checklist using the websites of 26 finance companies, it can be seen that the company's strategy in digitalization and information technology such as having applications, ISO 270001 standards, using marketing and payment channels as well as the use of financing glorification forms and financing applications shows that multifinance companies have begun to move to digitalization. If a multi-finance company has an aggressive vision for asset development and digital presence, digital channels are enhanced to increase the number of potential new customers entering through digital channels and of course by improving and maintaining data quality by using third-party data and increasing payment channel cooperation to ensure more choice of debtor payments. With a moderate vision, the use of third-party data to improve credit quality to improve or improve the quality of the asset portfolio of multifinance companies. [ABSTRACT FROM AUTHOR]

This paper explores the multifaceted realm of artificial intelligence (AI) implementation in financial services, providing insights into its potential, challenges and best practices. Highlighting the emergence of generative AI (GenAI) as a transformative tool, the paper underscores its significant impact on productivity and revenue generation within investment banks and capital markets. Addressing inherent risks of AI adoption, the paper stresses the importance of robust governance frameworks to mitigate operational, reputational and compliance risks. Specific attention is given to the phenomenon of GenAI hallucinations and the imperative for deterministic AI models to ensure data integrity and regulatory compliance. The paper outlines four key pillars of AI's applications in financial services: predictive AI, anomaly detection AI, classification AI and GenAI. Examples highlight AI's role in risk management, fraud prevention, customer experience enhancement and internal process optimisation, underscoring its transformative potential across the industry. The paper also covers the distinction between public and private AI models, emphasising the advantages of proprietary data-driven insights in ensuring competitive advantage and regulatory compliance. Concluding with actionable insights for AI implementation, the paper advocates for a strategic approach encompassing clear vision setting, risk oversight, data privacy management, centralised data architecture and comprehensive process automation. [ABSTRACT FROM AUTHOR]

The article presents studies related to the practical use of metallurgical slags by Limited Liability Partnership (LLP) "Casting", Limited Liability Partnership "Kazakhstan Steel Production-steel" in the production of building products. The process of preparation and experiments to determine the strength of control samples, full-scale tests of building products are shown. The relevance of the study lies in the fact that the technological process of production of building products involves technogenic waste that cannot be used in the process of metal production, which makes it possible to improve the ecological background in the region, as well as promising opportunities for obtaining raw materials used as ingredients of concrete mixtures. The presented practical implementation of the automation of the process of adding fillers (technogenic raw materials) in the preparation of a concrete mix allows increasing the efficiency and productivity of the production of building products. The article will be useful to everyone who conducts research in the field of recycling of industrial waste from metallurgy, as well as commercial use. [ABSTRACT FROM AUTHOR]

The article presents studies related to the practical use of metallurgical slags by Limited Liability Partnership (LLP) “Casting”, Limited Liability Partnership “Kazakhstan Steel Production-steel” in the production of building products. The process of preparation and experiments to determine the strength of control samples, full-scale tests of building products are shown. The relevance of the study lies in the fact that the technological process of production of building products involves technogenic waste that cannot be used in the process of metal production, which makes it possible to improve the ecological background in the region, as well as promising opportunities for obtaining raw materials used as ingredients of concrete mixtures. The presented practical implementation of the automation of the process of adding fillers (technogenic raw materials) in the preparation of a concrete mix allows increasing the efficiency and productivity of the production of building products. The article will be useful to everyone who conducts research in the field of recycling of industrial waste from metallurgy, as well as commercial use.

This study explores the application of the BPM lifecycle to optimize the market analysis process within the market intelligence department of a major energy company. The semi-structured, virtual nature of the process necessitated careful adaptation of BPM methodology, starting with process discovery through data collection, modeling, and validation. Qualitative analysis, including value-added and root-cause analysis, revealed inefficiencies. The redesign strategy focused on selective automation using Python 3.10 scripts and Power BI dashboards, incorporating techniques such as linear programming and forecasting to improve process efficiency and quality while maintaining flexibility. Post-implementation, monitoring through a questionnaire showed positive results, though ongoing interviews were recommended for sustained performance evaluation. This study highlights the value of BPM methodology in enhancing decision-critical processes and offers a model for adaptable, value-driven process improvements in complex organizational environments.

The automotive industry is one of the most demanding sectors of all manufacturing industries due to its competitiveness. It is necessary to innovate through the implementation of automated and robotic equipment, leading to cycle time and labor cost reduction. This work aims to design semi-automatic equipment to assemble cabling connectors used in the automotive sector, replacing a manual process currently taking place in an automotive components company. In the proposed equipment, the operator places a connector in the equipment, and the components (pins and seals) are automatically inserted. A vision sensor with artificial intelligence then confirms the correct application. The equipment operation defined as Finite Element Method (FEM) was applied for structural verification; the materials and fabrication processes were detailed; the associated costs were calculated, and the equipment subsets were validated. The design was successfully accomplished, and the imposed requirements were fulfilled, with significant advantages over the current process, providing new knowledge on how semi-automatic systems can be deployed to enhance the productivity and quality of manufacturing processes. The design principles and insights gained from this work can be applied to other automation challenges, particularly where manual processes need to be replaced by more efficient semi-automatic or automatic systems. The modularity of the overall solution and the design concepts of the component inserter, component feeder, and assembly process allow for its use in different assembly scenarios beyond the automotive sector, such as electronics or aerospace, providing a contribution to increased competitiveness and survival in the global market.

Background & Purpose: Artificial intelligence (AI) has made a digital transformation in human resource management, capturing the attention of HR professionals and managers. However, there remains a gap in research addressing the full spectrum of AI applications and challenges in HR management within organizations. This study aims to identify both the applications and challenges of AI in digitalizing human resource processes within companies. Methodology: To achieve this goal, a review of theoretical literature was conducted and the required data was collected from ten semi-structured interviews with experts specializing in HR AI technology and digital HR practices. The qualitative data were conceptualized through the thematic analysis technique. Subsequently, in the quantitative stage, the applications and challenges were ranked using the weighted average technique. Findings: 67 AI applications in nine dimensions were identified using thematic analysis including job design, personnel recruitment, performance evaluation, training, retention, compensation, operational enhancement, decision-making, and disciplinary actions. Moreover, 32 challenges were identified and categorized. Conclusion: The integration of AI into human resources processes results in enhanced precision, consistent data analysis, simplifying, automating and personalizing processes, ultimately saving time and improving the quality of HR operations. However, implementation this technology confronts challenges and restrictions. [ABSTRACT FROM AUTHOR]

With the increasing demand for digitalization, organizations look to emerging technologies such as Robotic Process Automation (RPA) to increase their business performance. This makes it essential to identify and select the most suitable processes to maximize the benefits for organizations. However, despite the increasing interest of academics and professionals in RPA, the literature lacks a study on the main criteria organizations should consider to decide which processes to automate. Therefore, this research lists the main criteria for process automation based on scientific and professional know-how. A systematic literature review was performed, followed by a Delphi study with RPA professionals, to tune the former insights collected from the scientific literature. Our findings point to 32 criteria that organizations and decision-makers should consider before choosing which processes to automate. Feasibility, process description, and input and output data are the most voted. The criteria are evaluated with 18 processes in six organizations with positive results. While professionals may find valuable information in this document to help them decide which processes must be automated first, academics are now aware of which areas deserve further investigation. [ABSTRACT FROM AUTHOR]

Urgency of the research. The accelerated digitization of society and the automation of processes in various economic sectors, including the printing industry, pose several pressing questions for employers: How can the staff be quickly trained to master their job responsibilities? How can the level of digital competencies among the personnel be raised? How can training be conducted with minimal disruption to the production process and minimal costs, and so on? An effective solution to these challenges may lie in the realm of non-formal education for the staff, which can significantly help employees elevate their professional competencies, especially in the digital domain. Target setting. The printing industry in modern realities faces various challenges and problems, in particular, with the loss of personnel potential and insufficient level of professional development of personnel in times of digitalization and automation. Therefore, the development of digital competences of specialists in the printing industry in the conditions of non-formal education is absolutely necessary. Actual scientific researches and issues analysis. Research on digital competencies has been conducted by V. Bykov, O. Ovcharuk, T. Balanovska, A. Oleshko, Ye. Hrabovsky, O. Dannikov, O. Kravchuk, B. Virzhikovska, O. Berezhna, O. Pushkar, T. Andryushchenko, and others. The issue of non-formal education was considered in their works by A. Cropley, Ch. Duke, E. Hummel, P. Williams, K. Knapper, N. Nychkalo, O. Ohiienko, L. Lukyanova, V. Davydova, V. Kusherets, O. Parashchuk and others. The development and utilization of digital technologies in the printing industry have been explored by Ye. Hrabovsky, M. Olenych, O. Pushkar, I. Bondar, V. Havrilov, Yu. Sisoieva, V. Chychuk, L. Potrashkova, P. Kyrychok, Yu. Barnych, S. Knyazev, Ya. Yatskiv and others. The research objective. Analyze the problem of developing digital competencies among professionals in the printing industry within the context of non-formal education and assess the state of its research in theory and practice. The statement of basic materials. Challenges and problems faced by printing enterprises in modern realities, particularly in the context of insufficient personnel development, during the times of digitization and automation of societal processes, have been analyzed. The importance of developing digital competencies among specialists in the printing industry, especially within enterprises, has been emphasized. The importance of the use of digital tools in the non-formal education of specialists in the printing industry has been revealed. Conclusions. The development of digital competences of specialists in the printing industry in the conditions of nonformal education increases the level of interaction of employees within the production process and contributes to the efficient operation of the enterprise as a whole. An important role in the development of digital competences of specialists in the printing industry is played by their nonformal education, which, thanks to the development of digital technologies, becomes more accessible to the general public, and in a short period of time can increase the level of knowledge of the specialist and improve his professional skills. [ABSTRACT FROM AUTHOR]

The research aimed to test the effect of management information systems on operational performance with mediating effect of decision-making performance and process automation as a moderating variable in the context of Saudi Arabia. For this purpose, data was collected from the 299 employees of Saudi Arabian textile companies using a convenient sampling technique. Used cross-sectional research design, quantitative research approach, and Partial Least Square (PLS)-Structural Equation Modeling (SEM). The results show that management information system capabilities have a positive and significant impact on business operation performance. Indirect mediating effect results also show the partial mediation of operations decision making performance among all management information system capabilities and business operations performance. On the other hand, process automation has also shown a significant moderating effect on the relationship of management information system capabilities and business operations performance. The study with significant mediating and moderating effect contributed a novel research finding in the extant literature. The study could also help the regulators focus on the process automation system that could increase the information system of the organization which could support operational performance.

The agriculture industry is experiencing a transformative shift towards greater efficiency and sustainability through the integration of artificial intelligence (AI) tools into various production processes. This article presents an overview of selected AI tools and their practical utilization in agriculture, shedding light on their profound impact on enhancing crop yields, resource management, and overall farm productivity. The article also provides an overview of the definition of artificial intelligence and a timeline starting with the first mention of artificial intelligence and ending with the present to better understand the described issue. The article highlights the importance of responsible AI development and integration. The ethical and societal implications of AI in agriculture, such as job displacement and data privacy concerns, are also addressed. The adoption of AI technologies is expected to play a vital role in meeting the global food demand while addressing the challenges faced by the agriculture sector. However, it is crucial to navigate these advancements responsibly, ensuring that the benefits of AI in agriculture are maximized while minimizing potential drawbacks.

In the process industry, a control system is important to ensure the process runs smoothly and keeps the product under predetermined specifications. Oscillations in process variables can affect the decreasing profitability of the plant. It is important to detect the oscillation before it becomes a problem for profitability. Various methods have been developed; however, the methods still need to improve when implemented online for multi-oscillation. Therefore, this research uses a machine learning-based method with the K-Nearest Neighbour (KNN) algorithm to detect multi-oscillation in the control loop, and the detection methods are made to carry out online detection from real plants. The developed method simulated the Tennessee Eastman Process (TEP), and it used Python programming to create a KNN model and extract time series data into the frequency domain. The Message Queuing Telemetry Transport (MQTT) communication protocol has been used to implement as an online system. The result of the implementation showed that two KNN models were made with different window size variations to get the best performance model. The best model for multi-oscillation detection was obtained with an F1 score of 76% for detection.

Copyright of Polish Technical Review is the property of Wydawnictwo SIGMA-NOT and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)