## 5 Digital Twin AR in Chemical Industry
This resource integration streamlines global management and can improve decision making, operational control, continuous learning, and other essential facets of industry. Additionally, this proposed mix of augmented reality with digital twins allows for more realistic immersion during training and simulation in industry. In this case, during immersive training, the proportions of flows, volumes, and other physical properties can be perceived in a more user-friendly way. On the other hand, pure mathematical models, such as differential or algebraic equations, or process simulations, such as those used in process-flow simulators, require higher analytical and abstraction skills. Likewise, if an augmented reality model is adopted that is not faithful to the process issues, the analysis may be impaired. Thus, this paper argues that a joint approach should be sought since the use of augmented reality is directly aligned with the ability of new generations to learn in virtual environments and to be typically more adapted to immersive activities. Additionally, the associated use of models will allow for a more accurate physical understanding of the process. However, despite its considerable potential, the implementation of AR in the chemical industry also presents several key barriers and challenges that companies must address to use this technology effectively. These include the following:  
* High initial investment, not only in software and hardware but also in infrastructure upgrades, as mentioned above. Chemical processes are highly complex and require a large amount of data from sensors, equipment, and operating systems. In addition, exposure to hazardous environments could limit the type of AR hardware, introducing additional safety risks when using the equipment. * Technical and operational constraints related to the importance of accuracy and reliability in chemical processes and compatibility with legacy systems and regulatory standards. * Specific and ongoing training may be required as AR technology evolves, accompanied by some resistance to change from workers. * Cybersecurity risks could lead to significant operational risks, regulatory penalties, and intellectual property theft; privacy issues must address worker concerns about surveillance and data collection. Hardware durability is critical in harsh chemical plant environments where workers are exposed to chemicals, high temperatures, or dust. Battery life and connectivity are also necessary. * Scalability can be challenging and costly, so implementing AR across multiple plant sizes with appropriate integration with legacy systems requires careful planning and resources. Some limitations can be highlighted, such as the bulkiness and discomfort of AR devices and their limited battery life, which are indeed significant barriers to the widespread adoption of AR in the chemical industry. Then, the high costs and specialized skills required for developing and maintaining AR content pose substantial challenges. Addressing these issues will require advances in AR hardware design to improve usability and battery life and investment in training and resources to support the creation of high-quality AR content. By overcoming these barriers, companies can better leverage the benefits of AR to improve safety, training, and operational efficiency. Data security and privacy issues are also critical to the successful implementation of AR in the chemical industry, particularly given AR's reliance on real-time data from potentially sensitive sources. These concerns include risks to intellectual property, unauthorized access, and data breaches. Organizations must prioritize these aspects in their AR strategies by adopting robust encryption, secure data transmission protocols, and strict access controls. Furthermore, investing in employee training and awareness ensures adequate protection of sensitive data and maintains stakeholder trust.