Digital Twin (DT) refers to the virtual copy or model of any physical entity (physical twin) both of which are interconnected via exchange of data in real time. Conceptually, a DT mimics the state of its physical twin in real time and vice versa. Application of DT includes real-time monitoring, designing/planning, optimization, maintenance, remote access, etc. Its implementation is expected to grow exponentially in the coming decades. The advent of Industry 4.0 has brought complex industrial systems that are more autonomous, smart, and highly interconnected. These systems generate considerable amounts of data useful for several applications such as improving performance, predictive maintenance, training, etc. A sudden influx in the number of publications related to ‘Digital Twin’ has led to confusion between different terminologies related to the digitalization of industries. Another problem that has arisen due to the growing popularity of DT is a lack of consensus on the description of DT as well as so many different types of DT, which adds to the confusion. This paper intends to consolidate the different types of DT and different definitions of DT throughout the literature for easy identification of DT from the rest of the complimentary terms such as ‘product avatar’, ‘digital thread’, ‘digital model’, and ‘digital shadow’. The paper looks at the concept of DT since its inception to its predicted future to realize the value it can bring to certain sectors. Understanding the characteristics and types of DT while weighing its pros and cons is essential for any researcher, business, or sector before investing in the technology.

One of the most promising technologies that is driving digitalization in several industries is Digital Twin (DT). DT refers to the digital replica or model of any physical object (physical twin). What differentiates DT from simulation and other digital or CAD models is the automatic bidirectional exchange of data between digital and physical twins in real-time. The benefits of implementing DT in any sector include reduced operational costs and time, increased productivity, better decision making, improved predictive/preventive maintenance, etc. As a result, its implementation is expected to grow exponentially in the coming decades as, with the advent of Industry 4.0, products and systems have become more intelligent, relaying on collection and storing incremental amounts of data. Connecting that data effectively to DTs can open up many new opportunities and this paper explores different industrial sectors where the implementation of DT is taking advantage of these opportunities and how these opportunities are taking the industry forward. The paper covers the applications of DT in 13 different industries including the manufacturing, agriculture, education, construction, medicine, and retail, along with the industrial use case in these industries.

Material choice is a fundamental consideration when it comes to designing a solid dosage form. The matrix material will ultimately determine the rate of drug release since the physical properties (solubility, viscosity, and more) of the material control both fluid ingress and disintegration of the dosage form. The bulk properties (powder flow, concentration, and more) of the material should also be considered since these properties will influence the ability of the material to be successfully manufactured. Furthermore, there is a limited number of approved materials for the production of solid dosage forms. The present study details the complications that can arise when adopting pharmaceutical grade polymers for fused-filament fabrication in the production of oral tablets. The paper also presents ways to overcome each issue. Fused-filament fabrication is a hot-melt extrusion-based 3D printing process. The paper describes the problems encountered in fused-filament fabrication with Kollidon^® VA64, which is a material that has previously been utilized in direct compression and hot-melt extrusion processes. Formulation and melt-blending strategies were employed to increase the printability of the material. The paper defines for the first time the essential parameter profile required for successful 3D printing and lists several pre-screening tools that should be employed to guide future material formulation for the fused-filament fabrication of solid dosage forms.

The introduction of three-dimensional printing (3DP) has created exciting possibilities for the fabrication of dosage forms, paving the way for personalized medicine. In this study, oral dosage forms of two drug concentrations, namely 2.50% and 5.00%, were fabricated via stereolithography (SLA) using a novel photopolymerizable resin formulation based on a monomer mixture that, to date, has not been reported in the literature, with paracetamol and aspirin selected as model drugs. In order to produce the dosage forms, the ratio of poly(ethylene glycol) diacrylate (PEGDA) to poly(caprolactone) triol was varied with diphenyl(2,4,6-trimethylbenzoyl)phosphine oxide (Irgacure TPO) utilized as the photoinitiator. The fabrication of 28 dosages in one print process was possible and the printed dosage forms were characterized for their drug release properties. It was established that both drugs displayed a sustained release over a 24-h period. The physical properties were also investigated, illustrating that SLA affords accurate printing of dosages with some statistically significant differences observed from the targeted dimensional range, indicating an area for future process improvement. The work presented in this paper demonstrates that SLA has the ability to produce small, individualized batches which may be tailored to meet patients’ specific needs or provide for the localized production of pharmaceutical dosage forms.

Oral tablets are a convenient form to deliver active pharmaceutical ingredients (API) and have a high level of acceptance from clinicians and patients. There is a wide range of excipients available for the fabrication of tablets thereby offering a versatile platform for the delivery of therapeutic agents to the gastrointestinal tract. However, the geometry of tablets is limited by conventional manufacturing processes. This study aimed to compare three manufacturing processes in the production of flat-faced oral tablets using the same formulation composed of a polymer blend and caffeine as a model drug: fused-filament fabrication (FFF), direct compression (DC) and injection molding (IM). Hot-melt extrusion was used to convert a powder blend into feedstock material for FFF and IM processes, while DC was performed on the powder mixture. Tablets were produced with the same dimensions and were characterized for their physical and dissolution properties. There were statistical differences in the physical properties and drug release profiles of the tablets produced by the different manufacturing processes. DC tablets displayed immediate release, IM provided sustained release over 48 h, and FFF tablets displayed both release types depending on the printing parameters. FFF continues to demonstrate high potential as a manufacturing process for the efficient production of personalized oral tablets.

A digital twin (DT) is a virtual/digital model of any physical object (physical twin), interconnected through data exchange. In the context of Industry 4.0, DTs are integral to intelligent automation driving innovation at scale by providing significant improvements in precision, flexibility, and real-time responsiveness. A critical challenge in developing DTs is achieving a model that reflects real-time conditions with precision and flexibility. This paper focuses on evaluating latency and accuracy, key metrics for assessing the efficacy of a DT, which often hinder scalability and adaptability in robotic applications. This article presents a comprehensive framework for developing DTs using Unity and Robot Operating System (ROS) as the main layers of digitalization and communication. The MoveIt package was used for motion planning and execution for the robotic arm, showcasing the framework’s versatility independent of proprietary constraints. Leveraging the versatility and open-source nature of these tools, the framework ensures interoperability, adaptability, and scalability, crucial for modern smart manufacturing applications. Our approach was validated by conducting extensive accuracy and latency tests. We measured latency by timestamping messages exchanged between the physical and digital twin, achieving a latency of 77.67 ms. Accuracy was assessed by comparing the joint positions of the DT and the physical robotic arm over multiple cycles, resulting in an accuracy rate of 99.99%. The results highlight the potential of DTs in enhancing operational efficiency and decision-making in manufacturing environments.