From Design to Display: Tackling Manufacturing Challenges in AR Waveguides

This chapter provides a list of product quality tests for topically applied drug products. The limitation in local pharmacokinetics (PK) knowledge and tools impedes the chemistry, manufacturing and controls (CMC) development of locally acting dermal systems for both new and generic drugs. One can expect that CMC information to support such a product may be more than what is typically required for a simple solution/suspension/emulsion. With the availability of cleaner medical grade plastics and more sophisticated manufacturing equipment/process, the aforementioned CMC challenges have been overcome. Traditional dermatological product development was often empirical in CMC activities. CMC overlook is usually due to an ignorance of the clinical/regulatory implications of CMC elements. Early identification of critical product attributes and important manufacturing process parameters is essential to the eventual success in the development. A non-aqueous, volatile formulation was uncommon in the past due to challenges in manufacturing and handling as well as concerns related to safety and quality.

Additive Manufacturing (AM) not only allows the component production with complex shapes, also offers the openings of control of microstructures and design of materials for metals and alloys. The fundamental concepts of additive manufacturing and its growth is to be evaluated since this field is growing rapidly. In this chapter, a brief outline of AM and its challenges in processing are discussed. The present state of metal and alloy AM is also presented. In particular, the challenges in the additive manufacturing of metals and alloys are discussed in detail. It reviews the challenges in the additive manufacturing process of metals and alloys including how rapidly changing conditions during AM process influence metals and alloys microstructure development. A deeper understanding of AM metal solidification and solid-state phase transitions is needed to process the additive manufacturing of metals and alloys and to control their microstructures. It also discusses other common problems in the AM process of metals and alloys. This work provides a direction for scientific research to enable the production of high performance AM metallic parts of reliably high-quality microstructures and mechanical properties.

<div class="section abstract"><div class="htmlview paragraph">Countries around the world are expected to continue to adopt more stringent emissions standards for heavy-duty markets for both oxides of nitrogen (NOx) and greenhouse gases (GHG). While there is uncertainty about the timing and extent of these regulations, it is clear that significant reductions will be required to address urban air pollution and climate change concerns. The rate and pace of technology evolution and how it will affect the energy pathways for commercial transportation and industrial use are dependent on multiple variables such as national energy and environmental policies and public-private partnerships. Although it adds complexity, the engine system has great potential to evolve as it continues to be highly integrated into the super system for which it is producing power. This paper examines the potential opportunities and challenges for engine manufacturers to continue to be the supplier of power to vehicles and equipment of the future.</div></div>

Negative coupling is widely used in microwave filter design, especially for filters with finite transmission zeros (TZs). Conventionally, negative coupling is realized through capacitive irises or probes. However, when the negative coupling is small, capacitive irises need to be very narrow, which presents significant challenges in manufacturing and tuning the filters. In this paper, a negative dispersion-less coupling structure (NDLCS) is proposed based on a partial-height post for waveguide filters. Compared to capacitive irises, the NDLCS achieves a comparable effect while allowing the minimum dimension of coupling structures to increase from tens of micrometers to a few millimeters. The NDLCS also enables the installation of tuning screws, which significantly lowers both the manufacturing difficulty and the sensitivity to manufacturing tolerances. Two waveguide filters with narrow bandwidths are designed using the proposed NDLCS and compared to filters with conventional capacitive irises and dispersive coupling structures. The investigated and measured results demonstrate the advantages of the proposed NDLCS in manufacturing and tuning when realizing small negative coupling for waveguide filters.

Structural heterogeneity in 3D printed Zr-based bulk metallic glass by selective laser melting

The Flexible Job Shop Scheduling Problem (FJSP) poses significant challenges in manufacturing and logistics. While metaheuristic algorithms struggle with large-scale instances and Priority Dispatching Rules (PDRs) lack global optimization capability, this paper presents an innovative Deep Reinforcement Learning framework that effectively captures operation-machine interactions through CrossNet and Dual Attention Network. The proposed DAKF-CrossDAN framework incorporates a feature augmentation module (DAKF) to adaptively emphasize critical features. Experimental results demonstrate superior makespan minimization and enhanced generalization compared to state-of-the-art methods.

A Smart System to Standardize the Specifications of Haptic Quality Control

Subcutaneous (subQ) administration of biologic drug products is increasingly preferred to enable patient self-administration and reduce healthcare burden. However, the small dosing volume for subQ delivery necessitates high-concentration formulations, which often suffer from elevated viscosity and physical instability, creating challenges in manufacturing, injectability, and storage. Spray drying has emerged as a versatile particle engineering technique to produce solid biologic powders that can be redispersedinto suspensions. While suspensions of spray-dried particles have shown promise in reducing viscosity compared to liquid solutions, the influence of biologic particle properties on suspension performance remains poorly understood. This study aimed to elucidate how particle size and surface characteristics affect viscosity and stability of high-concentration monoclonal antibody (mAb) suspensions. Spray-dried mAb particles were prepared with varied sizes and leucine addition. Suspensions were evaluated for viscosity, injectability through 27G needles, sedimentation, physical, chemical and structural stability during storage at 5°C and 25°C for 3months and at 40°C for 1month. Larger particle size, less surface dimpling and leucine addition significantly reduced viscosity without compromising physical and chemical stability; no sedimentation was observed. All suspensions were injectable via 27G needles. No notable aggregation or fragmentation occurred under tested conditions. Particle size and surface properties modulate suspension viscosity but do not impact stability. Particle engineering through spray drying represents an effective approach to enable high-concentration biologic suspensions for subQ delivery.

Challenges in Manufacture of PFBR Steam Generators

Genetic engineering of attenuated malaria parasites for vaccination

Configure-to-Order (CTO) assembly systems are becoming pivotal in meeting the rising demand for mass customization. However, enabling rapid and cost-effective system reconfiguration remains a major challenge in manufacturing. Despite the flexibility of general-purpose machines, fixture design introduces significant bottlenecks, often requiring extensive manual effort to access, organize, and interpret fragmented or incomplete data. This leads to inefficient design pipelines that can compromise product functionality and result in costly redesign iterations, even when using advanced Computer-Aided Fixture Design (CAFD) tools. Although the Model-Based Definition (MBD) paradigm offers a promising response to these information-related challenges, its adoption within the CAFD domain remains limited. This work aims to support the broader adoption of MBD in this field through a multi-level contribution. First, a structured literature review identifies the essential semantic information required in an MBD dataset tailored to CAFD. Second, this content is structured in a machine-readable form using the ISO standard STEP AP242. Third, an MBD-driven CAFD framework is proposed. Finally, a proof-of-concept CAFD tool is developed by integrating established methodologies with commercial software to automate non-value-added tasks, such as configuring Computer-Aided Technologies (CAx). The results demonstrate the potential of this approach to streamline CAFD processes and establish a fully connected digital thread.

<div class="section abstract"><div class="htmlview paragraph">Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks.</div><div class="htmlview paragraph">The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN.</div><div class="htmlview paragraph">This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on business needs.</div><div class="htmlview paragraph">The paper also discusses integration of IT and OT through protocols such as MQTT and Apache Kafka to enable real-time connectivity and explores how sensor data acquisition can support predictive analytics, including calibration compliance and maintenance forecasting.</div><div class="htmlview paragraph">The proposed multi-layered framework combining sensing, communication, and predictive intelligence demonstrates how digital tool tracking enhances efficiency, reduces downtime, and supports Lean manufacturing principles such as just-in-time readiness, continuous improvement, and overall equipment effectiveness (OEE).</div></div>

Regulatory Challenges in Manufacturing of Pancreatic Islets

Worldwide cooperation among manufacturing companies is increasingly gaining importance to face emerging challenges in manufacturing. The traditional Computer Integrated Manufacturing (CIM) systems cannot satisfy the needs of global market as they are deployed only within an enterprise. Therefore, a more flexible and comprehensive integrating methodology is required to overcome distance barriers, facility sharing problems and communication obstacles. These issues lead to the concept of Virtual CIM (VCIM). In this paper, the limitations of current agent based implementation of VCIM concept are analyzed. It also describes approaches to address those limitations and propose further development on Agent based Resource Scheduling Process in Small and Medium Enterprises in VCIM network.KeywordsVirtual CIMVCIMSmall and medium manufacturing enterprisesMulti-criteria selectionAgent based systems

Performance analysis and time prediction in manufacturing systems