{"id":109198,"date":"2025-06-12T22:42:05","date_gmt":"2025-06-12T20:42:05","guid":{"rendered":"https:\/\/industry-science.com\/?post_type=article&#038;p=109198"},"modified":"2025-07-01T14:24:47","modified_gmt":"2025-07-01T12:24:47","slug":"digital-twin","status":"publish","type":"article","link":"https:\/\/industry-science.com\/en\/articles\/digital-twin\/","title":{"rendered":"Open-Source and Cost-Effective Digital Twin"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Industry 4.0\u2019s revolution in manufacturing has driven progress in technologies that blend physical and digital, including <a href=\"https:\/\/industry-science.com\/en\/artificial-intelligence\/\">AI<\/a>, IoT, and cloud computing [1]. Digital Twin (DT) technology [2] is central to this progress; it virtually replicates physical assets and processes, enabling real-time monitoring, simulation, and optimization. Despite its advantages, DT technology faces significant adoption challenges across various sectors. High implementation costs and technical and organizational issues often keep industries from reaping the full benefits of these solutions [3].<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This study aims to bridge the gap between advanced technology and practical applications. It achieves this by creating an affordable, easy to implement, validated DT at Technology Readiness Level 5 (TRL 5) with open-source platforms and widely available commercial tools.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">DT technology enhances real-time monitoring, predictive maintenance, and automation, benefiting Industry 4.0. Despite its widespread use in manufacturing, the automotive industry, and healthcare, the technology sees limited use in agriculture [4].<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">In Germany, key adoption barriers include strict data protection laws (77%), a shortage of skilled workers (64%), and financial constraints [5]. In agriculture, challenges extend to high costs, unclear return of investment, and limited technical support [6].<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Despite these challenges, DTs can transform agricultural digitization by providing real-time virtual representations of assets and processes, supporting sustainable farming practices. Agriculture is a significant source of greenhouse gas emissions and energy consumption [7], but DTs enable tracking of carbon emissions, biodiversity, and soil health, promoting the adoption of more sustainable practices [8].<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This study explores the design of an accessible and affordable DT in agriculture using Arduino-based IoT sensors and Microsoft tools such as Power BI. It aims to develop a functional digital twin, validated with TRL 5, within a short time frame of two weeks using open source and office suite tools. The following research questions guided this study:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>RQ1: Is it possible to build a validated TRL 5 digital twin on the short term using open-source and office suite tools?<\/li>\n\n\n\n<li>RQ2: How do affordable DTs facilitate real-time agricultural monitoring and predictive analysis?<\/li>\n\n\n\n<li>RQ3: How does this model contribute to Industry 5.0\u2019s sustainability and human-centered goals?<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">A case study using Design Science Research (DSR) assesses the feasibility and impact of Technology Readiness Level 5 DT in agriculture, showing its potential to democratize advanced digital technologies and promote sustainable innovation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Background: why digital twin?<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A Digital Twin (DT) is a dynamic digital replica of a physical object, which enables real-time two-way data exchange for monitoring, control, and optimization. It integrates actual space, virtual space, and bidirectional data flow, allowing the digital system to simulate the physical system\u2019s behavior under varying conditions [9]. Developed for aerospace, DTs have become integral to Industry 4.0, incorporating simulations, real-time analytics, and automation [10]. DTs offer the ability to prototype, virtual testing, and evaluation of new features or operational strategies without physical alterations [9].<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The concept has evolved into the Digital Triplet (D3) [11], which includes human expertise and knowledge in decision-making in the DT framework, aligning with Industry 5.0\u2019s focus on human-machine collaboration and sustainability [12]. Industry 5.0 prioritizes resilient, human-centric, and sustainable manufacturing.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">DTs can significantly enhance energy efficiency and environmental responsibility [13]. Agriculture&#8217;s rising food needs, indicated by an expected global population of 9.8 billion by 2050 [14], demand innovative solutions. Smart farming, using digital twins, leads to sustainable food production and improved food security. But success hinges on dependable technology and smooth integration within current systems.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">DT in smart agriculture enables precise monitoring of environmental variables, improving resource efficiency and crop yields. Yet most applications remain in prototype stages and many concepts remain theoretical [15]. Easy-to-use, reliable, and simple implementations are key to ensure adoption. The shift from Industry 4.0 to 5.0 emphasizes human-centered technologies; using familiar workplace tools can encourage adoption. Among those tools is Microsoft 365, with more than two million companies using it worldwide, and 62% of organizations relying heavily on Microsoft software [16][<a href=\"https:\/\/www.statista.com\/statistics\/1106115\/types-software-used-by-companies\/\" target=\"_blank\" rel=\"noopener\">17<\/a>].<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">While commercial tools offer ease of use and scalability, open-source technologies present an affordable, flexible alternative for DT development. Message Queuing Telemetry Transport (MQTT), a lightweight messaging protocol, efficiently transmits sensor data, making it ideal for environmental monitoring [18]. Arduino, an open-source hardware platform, simplifies IoT prototyping for smart agriculture with its user-friendly design.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Open-source tools offer customization and transparency, but they can be technically complex and have fragmented support. Conversely, commercial platforms such as Microsoft Azure IoT may lead to vendor lock-in because of proprietary formats, APIs, and extended licensing contracts, which raise switching costs and limit operational adaptability [19]. Self-hosted platforms offer more control over data and system behavior, avoiding subscription costs but requiring technical expertise and strong infrastructure management [20]. The decision between cloud and self-hosted platforms depends on an organization\u2019s needs, digital maturity, and the trade-off between convenience, cost, and control.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Building a digital twin in two weeks: methodology and framework<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">This study employs a Design Science Research (DSR) methodology to develop and validate a scalable, low-cost DT model. DSR enhances knowledge through innovative artifacts and iterative cycles: problem identification, objective of a solution, design and development, and demonstration [21]. Design knowledge (DK) represents the relationship between problem and solution through artifacts, principles, and theories.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The Technology Readiness Levels (TRL) framework evaluates technology maturity from basic research (TRL 1) to full deployment (TRL 9) [22]. This study\u2019s DT development falls under TRL 5, meaning validation in a real environment, integrating IoT sensors for real-time monitoring and data visualization, with a future scope in agriculture.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Case study<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The case study reflects a real dilemma that companies face when implementing new technologies deciding between user-friendly commercial platforms and adaptable open-source tools. This study uses both open-source and commercial tools for flexible and user-friendly results. The study uses a testbed that simulates real-world precision farming conditions, featuring variable soil moisture, controlled temperatures, and energy monitoring. The objective was to assess the feasibility of an open-source DT for optimizing agricultural processes while ensuring sustainability and energy efficiency by integrating a system to assess the efficiency of irrigation and electrical consumption.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The study utilizes five key environmental and operational sensors:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li>a temperature sensor for monitoring and assessing the climate\u2019s effect on crops;<\/li>\n\n\n\n<li>a soil moisture sensor for measuring soil hydration to enable precision watering;<\/li>\n\n\n\n<li>a light intensity sensor for measuring sunlight exposure to analyze crop growth;<\/li>\n\n\n\n<li>an atmospheric pressure sensor for observing weather patterns and microclimate conditions;<\/li>\n\n\n\n<li>an electric current sensor for monitoring power consumption to improve energy efficiency.<\/li>\n<\/ol>\n\n\n\n<p class=\"wp-block-paragraph\">The DT system architecture included four main layers: data acquisition, data transmission, data processing, and data visualization\/automation. Figure 1 depicts the DT model\u2019s architecture, data transmission workflow, and structure.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"487\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-1024x487.webp\" alt=\"Architecture framework of the digital twin\" class=\"wp-image-109199\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-1024x487.webp 1024w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-764x363.webp 764w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-768x365.webp 768w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-514x244.webp 514w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-1536x730.webp 1536w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-510x242.webp 510w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1-64x30.webp 64w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-1.webp 1851w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>Figure 1: Architecture framework of the digital twin.<\/em><\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Sensors connect to Arduino MKR WiFi 1010 microcontrollers, transmitting data via MQTT in JSON format to Azure IoT Hub. Azure Stream Analytics processes the data, which is visualized through Power BI dashboards. Power Automate facilitates alerts and notifications in Microsoft Teams, ensuring anomaly detection and automated workflows. Moreover, the DT has to satisfy four key criteria: real-time visualization, forecasting, what-if scenario simulation, and notifications and\/or bidirectional communication.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Implementation and findings<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The study aimed to develop a TRL 5 DT within two weeks using open-source and commercial tools, prioritizing sustainability, ease of use, and human-centric design.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Experimental setup<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The experiment was set up in a simulated agricultural environment within a laboratory. Two participants with different backgrounds, a computer engineer and a mechanical engineer, were considered for the development. The experiment was based on two phases.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Phase one focused primarily on hardware setup and data collection. The initial week involved setting up Arduino MKR WiFi 1010 microcontrollers and environmental sensors. To create a forecast, data was gathered every five minutes for seven days to build a historical dataset. Power BI received CSV file data to build predictive models and analyze trends. Thresholds were established for temperature, humidity, soil moisture, and energy use. Environmental conditions for the next seven days were forecast using Power BI&#8217;s Exponential Smoothing ETS time-series model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">During phase two, real-time sensor data was sent from an Arduino to Azure IoT Hub using MQTT. Incoming data was processed by Azure Stream Analytics, then sent to Power BI for visualization. What-if simulations were used to test the system\u2019s predictive analysis of sudden environmental changes. When sensor readings surpassed predefined thresholds, Power Automate workflows sent a notification to Microsoft Teams. If an anomaly was detected, Power Automate sent a command to Azure IoT Hub, triggering a buzzer or LED to signal bidirectional communication. From the eighth day onwards, real time values were obtained within the model, which allowed for a comparison of the predicted values with the actual values of the following days.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Real-time analytics and automation in Power BI<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The DT dashboard displayed real-time data, forecasting, what-if simulations, and alerts. Predictive analytics improved decision-making, with a 95% confidence interval ensuring reliable predictions. Thresholds for anomalies were established:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Temperature: Below 5\u00b0C or above 28\u00b0C.<\/li>\n\n\n\n<li>Humidity: Below 10% or above 80%.<\/li>\n\n\n\n<li>Energy Consumption: Above 3.73 kWh.<\/li>\n\n\n\n<li>Soil Moisture: Below 190 (requires water) or above 260 (excess water).<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Automated alerts and bidirectional communication were enabled through Power Automate, sending notifications and triggering physical responses like activating buzzers or lights. The dashboard in Figure 2 displays the real-time moisture level model and forecast at the top. In the bottom-left corner, a what-if scenario simulator sits beside the notification box. Press the trigger at the bottom right to activate notifications in Microsoft Teams via Power Automate.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"575\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-1024x575.webp\" alt=\"Digital twin dashboard with real-time visualizations, forecasting, what-if simulations, and notifications\/bidirectional communication.\" class=\"wp-image-109201\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-1024x575.webp 1024w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-667x375.webp 667w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-768x432.webp 768w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-514x289.webp 514w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-1536x863.webp 1536w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-510x287.webp 510w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2-64x36.webp 64w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-2.webp 1783w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>Figure 2: Digital twin dashboard with real-time visualizations, forecasting, what-if simulations, and notifications\/bidirectional communication.<\/em><\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Power Automate allowed real-time alerts and bidirectional communication between digital and physical systems. Automated alerts in Microsoft Teams sent notifications of critical changes, such as temperature anomalies. The system\u2019s temperature sensors activated a buzzer and warning light, signaling a need for cooling. Power Automate used HTTP requests to communicate with Azure IoT Hub, which then communicated with an Arduino.Power Automate allowed real-time alerts and bidirectional communication between digital and physical systems. Automated alerts in Microsoft Teams sent notifications of critical changes, such as temperature anomalies. The system\u2019s temperature sensors activated a buzzer and warning light, signaling a need for cooling. Power Automate used HTTP requests to communicate with Azure IoT Hub, which then communicated with an Arduino.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Validating real-time monitoring and automation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Controlled tests validated system functionality. Temperature sensors detected heat source changes, triggering alerts. A soil moisture validation test was performed by adding water to the soil. The system precisely measured and showed the higher moisture levels. Power Automate sent notifications successfully, averaging a response time of two seconds. This trigger was also activated when the data changes were simulated in the dashboard.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Key outcomes<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The experiment successfully demonstrated that a TRL 5 Digital Twin can be developed in two weeks using open-source technologies and commercial tools, providing real-time monitoring, predictive analytics, anomaly detection, and alerting functionalities. The human-centered design ensured usability for non-experts.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">However, certain limitations came to light. A subscription is necessary to access a fully functional version of Azure IoT Hub and Stream Cloud Analytics. Power Automate workflows requiring features like HTTP connection also necessitate Microsoft 365 Pro or Premium. Although they have limitations, cloud-based IoT platforms are still very practical and useful, mainly due to their user-friendliness, simple integration, scalability, and widespread familiarity.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Future research could consider exploring hybrid DT architecture that combines the strengths of self-hosted and cloud-based IoT platforms. This would allow organizations to retain data ownership and flexibility through local infrastructure, while leveraging the scalability and AI capabilities of commercial cloud services when needed. Investigating methods for secure, modular integration between platforms like Eclipse Ditto, Node-RED, and Azure IoT could address interoperability challenges and reduce vendor lock-in.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Assessing the accuracy, insights, and challenges of the model<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The forecasting model\u2019s accuracy was assessed using relative error analysis:<\/p>\n\n\n\n<figure class=\"wp-block-image size-full\"><img loading=\"lazy\" decoding=\"async\" width=\"403\" height=\"77\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Formula.webp\" alt=\"Relative error forcasted realtime\" class=\"wp-image-109203\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Formula.webp 403w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Formula-64x12.webp 64w\" sizes=\"auto, (max-width: 403px) 100vw, 403px\" \/><figcaption class=\"wp-element-caption\"><em>(I)<\/em><\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The average relative error was 7.76%, indicating moderate precision. The model followed actual data trends but had deviations that affected irrigation efficiency. The forecast line closely follows the actual data, indicating a reasonably accurate model, but enhancing accuracy could improve water usage. Whether this accuracy level is acceptable depends on the application and industry standards. Figure 3 presents a six-day time series depicting real-time and forecasted soil moisture.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"570\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-1024x570.webp\" alt=\"Realtime data vs. forecasted data.\" class=\"wp-image-109205\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-1024x570.webp 1024w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-673x375.webp 673w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-768x428.webp 768w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-514x286.webp 514w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-510x284.webp 510w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3-64x36.webp 64w, https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/Figure-3.webp 1158w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><figcaption class=\"wp-element-caption\"><em>Figure 3: Realtime data vs. forecasted data.<\/em><\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Response time tests for notifications confirmed a two-second average, demonstrating the system\u2019s effectiveness in real-time alerting. Integrating various platforms, particularly the unfamiliar Azure tool, presented some challenges. Improvements are needed in AI-driven automation, edge computing, and security. While not yet at an industrial scale, DT provides a solid foundation for further deployment.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">From concept to reality: the impact of a two-week digital twin<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The research addressed its questions by proving that a validated TRL 5 Digital Twin could be constructed within a short period using open-source and office suite tools (RQ1). By combining real-time monitoring, predictive analytics, and automation, the DT demonstrated its ability to support affordable real-time agricultural monitoring and predictive analysis (RQ2). Moreover, the model supports Industry 5.0 objectives by fostering sustainability and improving human-centric decision-making in smart farming (RQ3).<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Although the model had a 7.76% average relative error, its predictions were reliable, and anomaly detection was achieved within two seconds. Challenges remain, especially with cloud service restrictions and automation limitations caused by subscription prerequisites. However, this DT model offers a promising, affordable, accessible, and sustainable solution for smart agriculture.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Further studies should strive to enhance the TRL through extensive testing in real operating environments and varied agricultural scenarios. Demonstrating the Digital Twin&#8217;s performance at higher readiness levels (for example, TRL 6\u20137) is critical for validating its robustness, reliability, and scalability for field deployment. This research can propel large-scale agricultural use, thus speeding up DT adoption on the way to achieving a two-week success rate!<\/p>\n<hr><div class=\"gito-pub-content-bibliography\"><h2>Bibliography <\/h2>[1] Attaran, S., Attaran, M., Celik, B. G.: Digital Twins and Industrial Internet of Things: Uncovering operational intelligence in industry 4.0. In: Decision Analytics Journal 10 (2024), p. 100398.\r<br>[2] Attaran, M., Attaran, S., Celik, B. G.: The impact of digital twins on the evolution of intelligent manufacturing and Industry 4.0. In: Advances in Computational Intelligence 3 (2023) 3, p. 11.\r<br>[3] Pileggi, P., Bujari, A., Barrowclough, O., Haenisch, J., Woitsch, R.: Overcoming nine digital twin barriers for manufacturing SMEs. Change2Twin Project. 2021.\r<br>[4] Pylianidis, C., Osinga, S., Athanasiadis, I. N.: Introducing digital twins to agriculture. In: Computers and Electronics in Agriculture (2021) 184, p. 105942.\r<br>[5] Bitkom: What are the biggest obstacles in the development of digital products or services in your company? In: Statista (2023). URL: https:\/\/www.statista.com\/statistics\/1356352\/obstacles-to-digital-development-of-companies-germany\/m, accessed 04.03.2025.\r<br>[6] McKinsey &amp; Company: Main global challenges for the adoption of agricultural technology in 2024, by region. In: Statista (2024). URL: https:\/\/www.statista.com\/statistics\/1549977\/challenges-for-agricultural-technology-adoption-worldwide-by-region\/, accessed 11.03.2025.\r<br>[7] Food and Agriculture Organization of the United Nations: World agriculture: towards 2030\/2050. Interim report. Rome (2006).\r<br>[8] Fiala N.: The greenhouse hamburger. In: Sci Am (2009) 300, pp. 72\u201375.\r<br>[9] Grieves, M., Vickers, J.: Digital twin: Mitigating unpredictable, undesirable emergent behavior in complex systems. In: Transdisciplinary perspectives on complex systems: New findings and approaches (2017), pp. 85-113.\r<br>[10] Singh, M., Fuenmayor, E., Hinchy, E. P., Qiao, Y., Murray, N., &amp; Devine, D.: Digital twin: Origin to future. In: Applied System Innovation 4 (2021) 2, p. 36.\r<br>[11] Umeda, Y., Hongo, Y., Goto, J., &amp; Kondoh, S.: Digital triplet and its implementation on learning factory. In: IFAC-PapersOnLine 55 (2022) 2, pp. 1-6.\r<br>[12] Leng, J., Sha, W., Wang, B., Zheng, P., Zhuang, C., et al.: Industry 5.0: Prospect and retrospect. In: Journal of Manufacturing Systems (2022) 65, pp. 279-295.\r<br>[13] Cisneros Saldana, S., Kapoor, A., Acharya, S., &amp; Markus, H.: Energy Efficiency Analysis in Industry 4.0 set up leveraging Industry 5.0 methods for Sustainable Manufacturing: Case Study. In: Procedia Computer Science (2025) 253, pp. 594-602.\r<br>[14] The State of Food and Agriculture 2017: Leveraging Food Systems for Inclusive Rural Transformation. 2017. URL: https:\/\/www.fao.org\/3\/i7658e\/i7658e.pdf\r<br>[15] Monteiro, J., Barata, J., Veloso, M., Veloso, L., Nunes, J.: A scalable digital twin for vertical farming. In: Journal of Ambient Intelligence and Humanized Computing 14 (2023) 10, pp. 13981-13996.\r<br>[16] Enlyft: Number of companies using Office 365 worldwide as of February 2025, by leading country. URL:https:\/\/www.statista.com\/statistics\/983321\/worldwide-office-365-user-numbers-by-country\/, accessed 14.04.2025.\r<br>[17] Flexera Software: Types of services\/software used by global organizations from leading tech vendors (Microsoft, Oracle, and IBM). URL: https:\/\/www.statista.com\/statistics\/1106115\/types-software-used-by-companies\/, accessed 14.04.2025.\r<br>[18] Al-Fuqaha, A., Guizani, M., Mohammadi, M., Aledhari, M., Ayyash, M.: Internet of things: A survey on enabling technologies, protocols, and applications. In: IEEE communications surveys &amp; tutorials 17 (2015) 4, pp. 2347-2376.\r<br>[19] Opara-Martins, J., Sahandi, R., Tian, F.: Critical analysis of vendor lock-in and its impact on cloud computing migration: a business perspective. In: Journal of Cloud Computing 5 (2016) 1, p. 4.\r<br>[20] Minerva, R., Biru, A., Rotondi, D.: Towards a definition of the Internet of Things (IoT). In: IEEE Internet Initiative 1 (2015) 1, pp. 1-86.\r<br>[21] Peffers, K., Tuunanen, T., Rothenberger, M. A., Chatterjee, S.: A design science research methodology for information systems research. In: J Manag Inf Syst (2007) 24, pp. 45\u201377.\r<br>[22] Mankins, J. C.: Technology readiness levels. 1995.<\/div><div id=\"download-section\" class=\"gito-pub-download-section\" style=\"text-align:center;margin:20px;\"><h2>Your downloads<\/h2><button style=\"font-size:14px;margin-right:15px;\" class=\"button gito-pub-cpt-download-button\" data-postid=\"109198\" data-userid =\"0\" data-filename=\"Cisneros_Schneller und einfacher Digitaler Zwilling_I4S_DE.pdf\"><span style=\"margin-top:5px !important;\" class=\"dashicons dashicons-download\"><\/span>&nbsp;&nbsp;PDF (DE)<\/button><button style=\"font-size:14px;margin-right:15px;\" class=\"button gito-pub-cpt-download-button\" data-postid=\"109198\" data-userid =\"0\" data-filename=\"Cisneros_Open-Source Cost-Effective Digital Twin_I4S_EN.pdf\"><span style=\"margin-top:5px !important;\" class=\"dashicons dashicons-download\"><\/span>&nbsp;&nbsp;PDF (EN)<\/button><\/div><br>Potentials: <span class=\"gito-pub-tag-element\"><a href=\"\/potentials\/energy-efficiency\/\">Energy Efficiency<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/potentials\/profitability\/\">Profitability<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/potentials\/resource-efficiency\/\">Resource Efficiency<\/a><\/span> <br>Solutions: <span class=\"gito-pub-tag-element\"><a href=\"\/en\/functions\/production-control\/\">Production Control<\/a><\/span> <div class=\"gito-pub-tags-social-share\" style=\"display:flex;justify-content:space-between;\"><div>Tags: <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/digitale-transformation-en\/\">Digitale Transformation<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/digitaler-zwilling-en\/\">digitaler Zwilling<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/digitalisierung-en\/\">Digitalisierung<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/industrie-4-0-en\/\">Industrie 4.0<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/internet-of-things-en\/\">Internet of things<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/kuenstliche-intelligenz-en\/\">K\u00fcnstliche Intelligenz<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/nachhaltigkeit-en\/\">Nachhaltigkeit<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"\/tag\/simulation-en\/\">Simulation<\/a><\/span> <br>Industries: <span class=\"gito-pub-tag-element\"><a href=\"https:\/\/industry-science.com\/en\/industries\/manufacturing-en\/\">Manufacturing<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"https:\/\/industry-science.com\/en\/industries\/smart-objects\/\">Smart Objects<\/a><\/span> <span class=\"gito-pub-tag-element\"><a href=\"https:\/\/industry-science.com\/en\/industries\/technical-services\/\">Technical Services<\/a><\/span> <\/div><div><div class=\"social-icons share-icons share-row relative\" ><a href=\"whatsapp:\/\/send?text=Open-Source%20and%20Cost-Effective%20Digital%20Twin - https:\/\/industry-science.com\/en\/articles\/digital-twin\/\" data-action=\"share\/whatsapp\/share\" class=\"icon button circle is-outline tooltip whatsapp show-for-medium\" title=\"Share on WhatsApp\" aria-label=\"Share on WhatsApp\"><i class=\"icon-whatsapp\" aria-hidden=\"true\"><\/i><\/a><a href=\"https:\/\/www.facebook.com\/sharer.php?u=https:\/\/industry-science.com\/en\/articles\/digital-twin\/\" data-label=\"Facebook\" onclick=\"window.open(this.href,this.title,&#039;width=500,height=500,top=300px,left=300px&#039;); return false;\" target=\"_blank\" class=\"icon button circle is-outline tooltip facebook\" title=\"Share on Facebook\" aria-label=\"Share on Facebook\" rel=\"noopener nofollow\"><i class=\"icon-facebook\" aria-hidden=\"true\"><\/i><\/a><a href=\"https:\/\/x.com\/share?url=https:\/\/industry-science.com\/en\/articles\/digital-twin\/\" onclick=\"window.open(this.href,this.title,&#039;width=500,height=500,top=300px,left=300px&#039;); return false;\" target=\"_blank\" class=\"icon button circle is-outline tooltip x\" title=\"Share on X\" aria-label=\"Share on X\" rel=\"noopener nofollow\"><i class=\"icon-x\" aria-hidden=\"true\"><\/i><\/a><a href=\"mailto:?subject=Open-Source%20and%20Cost-Effective%20Digital%20Twin&body=Check%20this%20out%3A%20https%3A%2F%2Findustry-science.com%2Fen%2Farticles%2Fdigital-twin%2F\" class=\"icon button circle is-outline tooltip email\" title=\"Email to a Friend\" aria-label=\"Email to a Friend\" rel=\"nofollow\"><i class=\"icon-envelop\" aria-hidden=\"true\"><\/i><\/a><a href=\"https:\/\/www.linkedin.com\/shareArticle?mini=true&amp;url=https:\/\/industry-science.com\/en\/articles\/digital-twin\/&amp;title=Open-Source%20and%20Cost-Effective%20Digital%20Twin\" onclick=\"window.open(this.href,this.title,&#039;width=500,height=500,top=300px,left=300px&#039;); return false;\" target=\"_blank\" class=\"icon button circle is-outline tooltip linkedin\" title=\"Share on LinkedIn\" aria-label=\"Share on LinkedIn\" rel=\"noopener nofollow\"><i class=\"icon-linkedin\" aria-hidden=\"true\"><\/i><\/a><\/div><\/div><\/div><hr style=\"margin-top:0px;\">\n<h2 class=\"gito-pub-frontend-post-headline\">You might also be interested in<\/h2>\n<!-- GITO_PUB_POST start flex-container -->\n<div class=\"gito-pub-flex-container\">\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/industry-4-0-digitalization-limbo\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Donhauser_AdobeStock_507850396_Gorodenkoff-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Donhauser_AdobeStock_507850396_Gorodenkoff-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Donhauser_AdobeStock_507850396_Gorodenkoff-196x180.webp\" alt=\"Industry 4.0\u2014Progress and Digitalization in Limbo\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Industry 4.0\u2014Progress and Digitalization in Limbo\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Industry 4.0\u2014Progress and Digitalization in Limbo<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Status of sustainable transformation and digitalization in production engineering<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/christian-donhauser\/\">Christian Donhauser<\/a> <a href=\"https:\/\/orcid.org\/0009-0009-0366-1828\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/daniel-riepl\/\">Daniel Riepl<\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     <div class=\"gito-pub-frontend-post-card-abo-sign gito-pub-login-register-link\" data-targetabo=\"expert\" data-targeturl=\"https:\/\/industry-science.com\/en\/articles\/industry-4-0-digitalization-limbo\/\" title=\"please login or register - content can only be read in its entirety with a subscription  expert\">\n\t\t\t                         <img decoding=\"async\" src=\"https:\/\/industry-science.com\/wp-content\/plugins\/gito-publisher\/img\/i4s-login.png\">\n\t\t\t                      <\/div>Digitalization projects help users represent complex processes more simply and efficiently. However, there are many obstacles to implementation. Reluctance to implement these projects is palpable. This affects, among others, employers and employees, who may fall behind economically by waiting or avoiding change. These observations can be traced back to an overarching research question: What barriers and systemic challenges hinder sustainable transformation within the context of Industry 4.0, particularly when considering human labor in production engineering? What questions are the affected stakeholders asking? The primary goal of this long-term research project is to define these questions decisively and in detail in order to develop a conceptual foundation that integrates research, teaching, and technological development and thus combines the potential of digital technologies with the experiential and practical knowledge of production workers.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 56-60<\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/ai-lubrication-thread-forming\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Donhauser_AdobeStock_1969238171_Gorodenkoff-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Donhauser_AdobeStock_1969238171_Gorodenkoff-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Donhauser_AdobeStock_1969238171_Gorodenkoff-196x180.webp\" alt=\"AI-Powered Lubrication Strategies for Thread Forming\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"AI-Powered Lubrication Strategies for Thread Forming\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">AI-Powered Lubrication Strategies for Thread Forming<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Adaptive spray jet control to increase process reliability and tool life<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/reinhard-schmied\/\">Reinhard Schmied<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/marco-susic\/\">Marco Susic<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/christian-donhauser\/\">Christian Donhauser<\/a> <a href=\"https:\/\/orcid.org\/0009-0009-0366-1828\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     <div class=\"gito-pub-frontend-post-card-abo-sign gito-pub-login-register-link\" data-targetabo=\"expert\" data-targeturl=\"https:\/\/industry-science.com\/en\/articles\/ai-lubrication-thread-forming\/\" title=\"please login or register - content can only be read in its entirety with a subscription  expert\">\n\t\t\t                         <img decoding=\"async\" src=\"https:\/\/industry-science.com\/wp-content\/plugins\/gito-publisher\/img\/i4s-login.png\">\n\t\t\t                      <\/div>Thread forming requires precise lubricant application because high contact pressures and process temperatures strongly influence tool loading, friction, and process stability. Although minimum quantity lubrication (MQL) systems are widely used, current spray-based approaches can still suffer from spray losses, insufficient wetting of the thread grooves, and unstable droplet transport. This article presents a concept for adaptive precision lubrication in thread forming based on computational fluid dynamics (CFD)-supported flow analysis, experimental validation, and artificial intelligence (AI)-assisted optimization. The focus is on droplet size, spray jet geometry, nozzle position, ambient flow conditions, and their influence on wetting intensity. Preliminary simulation-based investigations indicate that data-driven optimization can help identify wetting deficiencies and support the development of future control strategies for resource-efficient lubricant application.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2027 | Edition 3 | Pages 76-83<\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/human-models-optimized-assembly\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Brockmann_AdobeStock_1505788468_vegefox.com_-640x325.webp\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Brockmann_AdobeStock_1505788468_vegefox.com_-196x180.webp\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/05\/Brockmann_AdobeStock_1505788468_vegefox.com_-196x180.webp\" alt=\"Optimized Manual Processes in Automotive Production\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Optimized Manual Processes in Automotive Production\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Optimized Manual Processes in Automotive Production<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">A module-based approach for the efficient creation of work system simulations<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/barbara-brockmann\/\">Barbara Brockmann<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/tobias-jurk\/\">Tobias Jurk<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/beate-stoffels\/\">Beate Stoffels<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/jochen-deuse-en\/\">Jochen Deuse<\/a> <a href=\"https:\/\/orcid.org\/0000-0003-4066-4357\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     <div class=\"gito-pub-frontend-post-card-abo-sign gito-pub-login-register-link\" data-targetabo=\"expert\" data-targeturl=\"https:\/\/industry-science.com\/en\/articles\/human-models-optimized-assembly\/\" title=\"please login or register - content can only be read in its entirety with a subscription  expert\">\n\t\t\t                         <img decoding=\"async\" src=\"https:\/\/industry-science.com\/wp-content\/plugins\/gito-publisher\/img\/i4s-login.png\">\n\t\t\t                      <\/div>In the manufacturing industry, the integration of digital human models into the product development and manufacturing process is becoming increasingly important. Particularly in assembly, which is characterized by a high proportion of manual tasks, motion simulations enable a realistic representation of human work and thus make a significant contribution to the evaluation of motion economy, process validation, and efficiency improvement. However, widespread application in production planning faces various challenges, such as the high initial effort required to create human simulations as well as volatile planning conditions. This article presents a practice-oriented solution from the automotive assembly sector that enables the creation of simulations with reduced effort as well as their early and consistent use in the planning process.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 48-55<\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/application-potentials-of-chinese-knowledge-platforms\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/Braun-640x325.jpg\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/Braun-196x180.jpg\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/Braun-196x180.jpg\" alt=\"Application Potentials of Chinese Knowledge Platforms\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Application Potentials of Chinese Knowledge Platforms\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Application Potentials of Chinese Knowledge Platforms<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Digital platforms for knowledge transfer in research and education<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/yunhao-su\/\">Yunhao Su<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/martin-braun-en\/\">Martin Braun<\/a> <a href=\"https:\/\/orcid.org\/0000-0003-0857-6760\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     <div class=\"gito-pub-frontend-post-card-abo-sign gito-pub-login-register-link\" data-targetabo=\"expert\" data-targeturl=\"https:\/\/industry-science.com\/en\/articles\/application-potentials-of-chinese-knowledge-platforms\/\" title=\"please login or register - content can only be read in its entirety with a subscription  expert\">\n\t\t\t                         <img decoding=\"async\" src=\"https:\/\/industry-science.com\/wp-content\/plugins\/gito-publisher\/img\/i4s-login.png\">\n\t\t\t                      <\/div>Knowledge drives innovation, which is why digital platforms are increasingly used for knowledge transfer. The People\u2019s Republic of China (PRC) is a global leader in digitalization and digital platforms are central to Chinese knowledge transfer and innovation systems. This study supplements theoretical concepts of knowledge transfer with empirical findings on the (further) development of relevant knowledge platforms. It examines the influence of specific design features on the functionality and quality of digital knowledge platforms. A literature review identifies seven condensed success criteria. Nine leading Chinese knowledge platforms are categorized based on their transfer logic and functional scope. Online survey participants assess the platform-specific manifestations of the identified criteria and highlight potential and areas for improvement in platform-based knowledge transfer.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 84-93<\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/smartbending-inline-measurement-for-process-correction\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/susic-640x325.jpg\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/susic-196x180.jpg\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/susic-196x180.jpg\" alt=\"SmartBending\u2014Inline Measurement for Process Correction\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"SmartBending\u2014Inline Measurement for Process Correction\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">SmartBending\u2014Inline Measurement for Process Correction<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">Inline process optimization for error compensation in swivel bending<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/christian-donhauser\/\">Christian Donhauser<\/a> <a href=\"https:\/\/orcid.org\/0009-0009-0366-1828\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/reinhard-schmied\/\">Reinhard Schmied<\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/marco-susic\/\">Marco Susic<\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     <div class=\"gito-pub-frontend-post-card-abo-sign gito-pub-login-register-link\" data-targetabo=\"expert\" data-targeturl=\"https:\/\/industry-science.com\/en\/articles\/smartbending-inline-measurement-for-process-correction\/\" title=\"please login or register - content can only be read in its entirety with a subscription  expert\">\n\t\t\t                         <img decoding=\"async\" src=\"https:\/\/industry-science.com\/wp-content\/plugins\/gito-publisher\/img\/i4s-login.png\">\n\t\t\t                      <\/div>Swivel bending is an established forming process that minimizes material loss and enables efficient use of resources. However, the process requires complex optimizations that have traditionally relied heavily on the expertise of machine operators. This results in significant time and material costs, as optimization steps are performed iteratively. Given the shortage of skilled workers, a technological upgrade of the machines in line with Industry 4.0 is necessary. As part of a research project, intelligent sensor technology was used to record critical influencing factors that reveal correlations between product defects and machine deformations. Based on this, a methodology was developed that forms the foundation for inline compensation, enabling the equipment to autonomously adjust process parameters to correct product defects and, in the long term, enable defect-free production from the very first component.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 134-141<\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n   <div class=\"gito-pub-frontend-post-card gito-pub-flex-item gito-pub-flex-item-1\">\n      <a href=\"https:\/\/industry-science.com\/en\/articles\/digital-twin-technology-and-architecture\/\">\n         <div class=\"gito-pub-frontend-post-card-row\">         <div class=\"gito-pub-frontend-post-card-column gito-pub-frontend-post-card-column-image\">\n            <picture>\n               <source media=\"(max-width:640px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/chandra-640x325.jpg\">\n               <source media=\"(min-width:641px)\" srcset=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/chandra-196x180.jpg\">\n               <img decoding=\"async\" class=\"gito-pub-frontend-post-card-image\" src=\"https:\/\/industry-science.com\/wp-content\/uploads\/2026\/06\/chandra-196x180.jpg\" alt=\"Digital Twin Technology and Architecture\">\n            <\/picture>\n         <\/div>\n            <div class=\"gito-pub-frontend-post-card-column\">               <div class=\"ellipsis\" style=\"height:166px !important;overflow:hidden;\" title=\"Digital Twin Technology and Architecture\">                  <table class=\"gito-pub-frontend-post-card-header\">\n            \t     <tr>\n                        <td>                  \t\t   <h4 class=\"gito-pub-frontend-post-card-title\" style=\"line-height:1.2em;\">Digital Twin Technology and Architecture<\/h4>\n                        <div class=\"gito-pub-frontend-post-card-subtitle\">A synthesis of concept and practice<\/div>                        <div class=\"gito-pub-frontend-post-card-author\"><a href=\"https:\/\/industry-science.com\/en\/authors\/arka-mukherjee\/\">Arka Mukherjee<\/a> <a href=\"https:\/\/orcid.org\/0000-0003-4445-5886\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a>, <a href=\"https:\/\/industry-science.com\/en\/authors\/shibaji-chandra\/\">Shibaji Chandra<\/a> <a href=\"https:\/\/orcid.org\/0009-0008-9052-2641\" target=\"_blank\" title=\"ORCID eintrag \u00f6ffnen.\" rel=\"noopener\">\n        <img decoding=\"async\" src=\"https:\/\/orcid.org\/assets\/vectors\/orcid.logo.icon.svg\" alt=\"ORCID Icon\" style=\"width:16px;height:16px;vertical-align:middle;\"><\/a><\/div>\n                        <\/td>\n                     <\/tr>\n                  <\/table>\n                  <div class=\"gito-pub-frontend-post-card-text\">\n                     <div class=\"gito-pub-frontend-post-card-abo-sign gito-pub-login-register-link\" data-targetabo=\"expert\" data-targeturl=\"https:\/\/industry-science.com\/en\/articles\/digital-twin-technology-and-architecture\/\" title=\"please login or register - content can only be read in its entirety with a subscription  expert\">\n\t\t\t                         <img decoding=\"async\" src=\"https:\/\/industry-science.com\/wp-content\/plugins\/gito-publisher\/img\/i4s-login.png\">\n\t\t\t                      <\/div>Digital twins are a key enabling technology of the fourth industrial revolution, integrating physical systems with their digital counterparts to create intelligent, data-driven environments. This conceptual\/practice-oriented paper examines how to establish a modern architectural framework for digital twins leverages modern tech-stack like IoT, Data Fabric, AI\/ML, seamless integration and enterprise grade security. The paper is grounded in an abundance of literature by leading vendors and analysts in space. It offers a comparative study of different vendors implementing the solution stack in the proposed architecture.                  <\/div>\n               <\/div>\n               <div class=\"gito-pub-frontend-post-card-scientific\"><strong>Industry 4.0 Science<\/strong> | Volume 42 | 2026 | Edition 3 | Pages 114-122<\/div>            <\/div>\n         <\/div>\n      <\/a>\n   <\/div>\n<\/div>\n<!-- GITO_PUB_POST end flex-container -->\n","protected":false},"excerpt":{"rendered":"<p>Digital Twin (DT) adoption remains a challenge due to high costs, complexity and lack of skills. This study proposes a cost-effective, TRL 5-validated DT model that can be built using open-source and office suite tools within just two weeks. Integrating real-time sensor data, predictive analytics, anomaly detection and notification, the model improves efficiency and sustainability in agriculture. Even with cloud service constraints, the system delivers a 7.76% average relative error and rapid, automated notifications. The findings show how open-source in combination with common commercial tools technologies can make advanced digital tools accessible to all, creating scalable, human-centered, and affordable solutions in line with Industry 5.0 principles.<\/p>\n","protected":false},"featured_media":108882,"menu_order":0,"template":"","categories":[79167,79298],"tags":[79504,79631,79449,79627,80264,80025,79356,80214],"product_cat":[],"topic":[67838,68206,69611,79333,68267],"technology":[67790,79493,67946,67717,67596,67634],"knowhow":[],"industry":[79494,79354,79496],"writer":[],"content-type":[83932],"potential":[71227,67658,69462],"solution":[67776],"glossary":[],"class_list":["post-109198","article","type-article","status-publish","has-post-thumbnail","category-design-en","category-typeset","tag-digitale-transformation-en","tag-digitaler-zwilling-en","tag-digitalisierung-en","tag-industrie-4-0-en","tag-internet-of-things-en","tag-kuenstliche-intelligenz-en","tag-nachhaltigkeit-en","tag-simulation-en","topic-digital-twin","topic-industry-4-0","topic-internet-of-things-en","topic-process-optimization","topic-sustainability","technology-artificial-intelligence","technology-digitalization","technology-sensors","technology-simulation-en","technology-software-en","technology-tools","industry-manufacturing-en","industry-smart-objects","industry-technical-services","content-type-article","potential-energy-efficiency","potential-profitability","potential-resource-efficiency","solution-production-control","product","first","instock","downloadable","virtual","sold-individually","taxable","purchasable","product-type-article"],"uagb_featured_image_src":{"full":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros.webp",1400,788,false],"thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-150x150.webp",150,150,true],"medium":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-666x375.webp",666,375,true],"medium_large":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-768x432.webp",768,432,true],"large":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-1024x576.webp",1020,574,true],"front-page-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-1032x320.webp",1032,320,true],"post-entry":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-764x376.webp",764,376,true],"post-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-392x320.webp",392,320,true],"post-teaser-mobile":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-608x496.webp",608,496,true],"post-custom-size":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-640x325.webp",640,325,true],"whitepaper-teaser":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-274x376.webp",274,376,true],"card-big":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-514x292.webp",514,292,true],"card-portrait":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-320x440.webp",320,440,true],"card-big-company":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-514x289.webp",514,289,true],"gp-listing":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-196x180.webp",196,180,true],"1536x1536":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros.webp",1400,788,false],"2048x2048":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros.webp",1400,788,false],"woocommerce_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-510x510.webp",510,510,true],"woocommerce_single":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-510x287.webp",510,287,true],"woocommerce_gallery_thumbnail":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-100x100.webp",100,100,true],"dgwt-wcas-product-suggestion":["https:\/\/industry-science.com\/wp-content\/uploads\/2025\/06\/BB_Cisneros-64x36.webp",64,36,true]},"uagb_author_info":{"display_name":"Andrea Wollweber","author_link":"https:\/\/industry-science.com\/en\/author\/"},"uagb_comment_info":0,"uagb_excerpt":"Digital Twin (DT) adoption remains a challenge due to high costs, complexity and lack of skills. This study proposes a cost-effective, TRL 5-validated DT model that can be built using open-source and office suite tools within just two weeks. Integrating real-time sensor data, predictive analytics, anomaly detection and notification, the model improves efficiency and sustainability&hellip;","_links":{"self":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article\/109198","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/article"}],"about":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/types\/article"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media\/108882"}],"wp:attachment":[{"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/media?parent=109198"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/categories?post=109198"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/tags?post=109198"},{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/product_cat?post=109198"},{"taxonomy":"topic","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/topic?post=109198"},{"taxonomy":"technology","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/technology?post=109198"},{"taxonomy":"knowhow","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/knowhow?post=109198"},{"taxonomy":"industry","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/industry?post=109198"},{"taxonomy":"writer","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/writer?post=109198"},{"taxonomy":"content-type","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/content-type?post=109198"},{"taxonomy":"potential","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/potential?post=109198"},{"taxonomy":"solution","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/solution?post=109198"},{"taxonomy":"glossary","embeddable":true,"href":"https:\/\/industry-science.com\/en\/wp-json\/wp\/v2\/glossary?post=109198"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}