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Abstract The demand for contactless, rapid manufacturing has increased over the years, especially during the COVID-19 pandemic. Additive manufacturing (AM), a type of rapid manufacturing, is a computer-based system that precisely manufactures products. It proves to be a faster, cheaper, and more efficient production system when integrated with cloud-based manufacturing (CBM). Similarly, the need for semiconductors has grown exponentially over the last five years. Several companies could not keep up with the increasing demand for many reasons. One of the main reasons is the lack of a workforce due to the COVID-19 protocols. This article proposes a novel technique to manufacture semiconductor chips in a fast-paced manner. An algorithm is integrated with cloud, machine vision, sensors, and email access to monitor with live feedback and correct the manufacturing in case of an anomaly.

Aluminum alloys are employed in agricultural equipment, aerospace sectors, medical instruments, machinery, automobiles, etc. due to their physical and mechanical characteristics. The geometrical shape and size of the parts are modified in turning operation by using a single-point cutting tool. A356 aluminum alloy is widely used in various engineering sectors, hence there is a necessity to produce A-356 components with quality. The inappropriate cutting parameters used in turning operation entail high production costs and reduce tool life. Box–Behnken design (BBD) based on response surface methodology (RSM) was used to design the experiments such that the experiment trials were conducted by varying cutting parameters like N-spindle speed (rpm), f-feed rate (mm/rev), and d-depth of cut (mm). The multi-objective responses, such as surface roughness (SR) and metal removal rate (MRR) were analyzed with the desirability method.

This course is verified by Probitas Authentication as meeting the AS9104/3A requirements for continuing Professional Development. This one-day program is designed to provide introductory information for those organizations who are considering transitioning from the Aeronautic, Space and Defense industry to the Food & Drug Administration (FDA), Medical Device Manufacturing market. Reviewing essential information necessary to understand and successfully begin the journey to FDA Medical Device approval, this course will examine many of the controls between the AS9100 Standard and FDA Regulations and identify the similarities.

This standard establishes the performance specifications for the zero-tolerance breath alcohol detection system to reduce the risks of driving under the influence of alcohol. It defines the accuracy and precision requirements of the BrAC measurement, as well as the acceptability criteria and key parameters to test these requirements. Additionally, this standard sets the performance requirements of the system for ethanol sensitivity, the response time, and the electrical, mechanical, and environmental conditions the system may encounter throughout the lifespan of the vehicle.

This SAE Standard establishes the performance specifications for the zero-tolerance breath alcohol detection system to reduce the risks of driving under the influence of alcohol. It defines the accuracy and precision requirements of the breath alcohol concentration (BrAC) measurement, as well as the acceptability criteria and key parameters to test these requirements. Additionally, this standard sets the performance requirements of the system for ethanol sensitivity, the response time, and the electrical, mechanical, and environmental conditions the system may encounter throughout the lifespan of the vehicle.

People at work are frequently distracted (“hijacked”) by a mix of in and out of workplace events, frequently including poor communications. As a result, they sometimes find themselves in situations in which they can be seriously injured or killed. An investigation into the “how” these situations were initiated led to list of six primary causes. Based on this list, an experiential program was developed to help people remain focused on their work, not get hijacked, and improve their communications.

Using tolerance stacks ensures that parts fit together properly, reducing scrap and rework, thereby increasing value. This 2-day foundational-level course explains how to use tolerance stacks to analyze product designs and how to use geometric tolerances in stacks.

Additive manufacturing (AM), is a manufacturing process of choice for functional part production, adding to the suite of choices a designer has available when designing a part for manufacturing. Like other traditional processes like casting and machining, AM has its set of constraints. An added layer of complexity comes from the fact that there are several different AM processes, and some of the design constraints are process-specific. On the other hand, AM offers a range of opportunities in design freedom and mass customization as well as in cost and lead time reduction in some cases.

To improve the biofidelity of the currently available Hybrid III 10-year-old (HIII-10C) Anthropomorphic Test Device (ATD), the National Highway Traffic Safety Administration (NHTSA) has developed the Large Omnidirectional Child (LODC) ATD. The LODC head is a redesigned HIII-10C head with mass properties and modified skin material required to match pediatric biomechanical impact response targets from the literature. A dynamic, nonlinear finite element (FE) model of the LODC head has been developed using the mesh generating tool Hypermesh based on the three-dimensional CAD model. The material data, contact definitions, and initial conditions are defined in LS-PrePost and converted to LS-Dyna solver input format. The aluminum head skull is stiff relative to head flesh material and was thus modeled as a rigid material. For the actual LODC, the head flesh is form fit onto the skull and held in place through contact friction.

Abstract The use of nanomaterials and nanostructures have been revolutionizing the advancements of science and technology in various engineering and medical fields. As an example, Carbon Nanotubes (CNTs) have been extensively used for the improvement of mechanical, thermal, electrical, magnetic, and deteriorative properties of traditional composite materials for applications in high-performance structures. The exceptional materials properties of CNTs (i.e., mechanical, magnetic, thermal, and electrical) have introduced them as promising candidates for reinforcement of traditional composites. Most structural configurations of CNTs provide superior material properties; however, their geometrical shapes can deliver different features and characteristics. As one of the unique geometrical configurations, helical CNTs have a great potential for improvement of mechanical, thermal, and electrical properties of polymeric resin composites.

This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Project Management and Advanced Product Quality Planning (APQP) are two critical techniques used in product development in the mobility industry today. This course will bring these techniques together in an easy to understand format that goes beyond the typical concept of constructing timelines and project planning, by exploring not only the Automotive APQP process, but also key aspects of PM processes.

Evolving to MedDev provides a new opportunity for executives in aerospace, automotive and medical devices companies to connect and develop long-term growth strategies and find ways to meet the increased short-term demand for medical supplies

The experimental investigation aims to improve natural composite materials aligned with feasible development principles. These composites can be exploited across several industries, including the automobile and biomedical sectors. This research employs date seed powder and neem gum powder as reinforcing agents, along with polyester resin as the base material. The fabrication route comprises compression moulding, causing the production of the natural composite material. This study focuses extensively on mechanical characteristics such as tensile strength, flexural strength, hardness, and impact resistance to undergo comprehensive testing. Furthermore, the chemical properties of the composites are examined using the FTIR test to gain understanding by integrating different proportions of date seed powder (5%, 10%, 15%, and 20%) and neem gum powder (0%, 3%, 6%, and 9%) in the matrix phase.

Under body blast (UBB) loading to military transport vehicles is known to cause foot-ankle fractures to occupants due to energy transfer from the vehicle floor to the feet of the soldier. The soldier posture, the proximity of the event with respect to the soldier, the personal protective equipment (PPE) and age/sex of the soldier are some variables that can influence injury severity and injury patterns. Recently conducted experiments to simulate the loading environment to the human foot/ankle in UBB events (~5ms rise time) with variables such as posture, age and PPE were used for the current study. The objective of this study was to determine statistically if these variables affected the primary injury predictors, and develop injury risk curves. Fifty below-knee post mortem human surrogate (PMHS) legs were used for statistical analysis. Injuries to specimens involved isolated and multiple fractures of varying severity.

ISO 13485:2016 is an international standard that establishes the requirements for a quality management system specific to the medical devices industry. It specifies requirements for a quality management system, and how to demonstrate compliance to meet customer and applicable regulatory requirements. ISO 13485 is designed to be used by organizations involved in the design, production, installation, and servicing of medical devices and related services. It can also be used by internal and external parties, such as certification bodies, to help them with their auditing processes.  Estimated to take up to 15-hours to complete.

ISO 13485:2016 is an international standard that establishes the requirements for a quality management system specific to the medical devices industry. It specifies requirements for a quality management system where an organization needs to demonstrate its ability to provide medical devices and related services that consistently meet customer and applicable regulatory requirements. ISO 13485 is designed to be used by organizations involved in the design, production, installation and servicing of medical devices and related services.

ISO 13485:2016 is an international standard that establishes the requirements for a quality management system specific to the medical devices industry. It specifies requirements for a quality management system where an organization needs to demonstrate its ability to provide medical devices and related services that consistently meet customer and applicable regulatory requirements. ISO 13485 is designed to be used by organizations involved in the design, production, installation and servicing of medical devices and related services.

ISO 13485:2016 is an international standard that establishes the requirements for a quality management system specific to the medical devices industry. It specifies requirements for a quality management system where an organization needs to demonstrate its ability to provide medical devices and related services that consistently meet customer and applicable regulatory requirements. ISO 13485 is designed to be used by organizations involved in the design, production, installation and servicing of medical devices and related services.

In the early days, there were significant limitations to the build size of laser powder bed fusion (L-PBF) additive manufacturing (AM) machines. However, machine builders have addressed that drawback by introducing larger L-PBF machines with expansive build volumes. As these machines grow, their size capability approaches that of directed energy deposition (DED) machines. Concurrently, DED machines have gained additional axes of motion which enable increasingly complex part geometries—resulting in near-overlap in capabilities at the large end of the L-PBF build size. Additionally, competing technologies, such as binder jet AM and metal material extrusion, have also increased in capability, albeit with different starting points. As a result, the lines of demarcation between different processes are becoming blurred.

Mass is one important suspicious object for breast cancer diagnosis in mammograms. Computer-aided detection (CAD) based on fully supervised deep learning achieves high performance for mass detection in mammograms. The lack of fine-grained expert labels becomes the bottleneck for the large-scale application of CAD to achieve detection in mammograms. Weakly supervised methods provide a solution to tackle the annotation problems, including in the application for mass detection. However, previous works face the problem of insufficient localization information, which affect the ability of mass detection. In this paper, we propose a multi-view enhancing mass detection network (MVMDNet) with dual view inputs that contains craniocaudal (CC) and mediolateral oblique (MLO) view of mammograms, where different view features are interacted and fused to enhance localization information.