Advances in laser‐based manufacturing techniques for specialty optical fiber

Additive manufacturing has shown potential for manufacturing parts out of metals, plastics and even ceramics. This paper reports on Selective Laser Melting (SLM) for depositing glass which has significantly different material properties from metals, ceramics or polymers. A CO2 laser is used to locally melt portions of a powder bed to explore the effects of process parameters on stationary particle formation as well as continuous line quality. Numerical modeling is also applied to gain insight into the physical process. The experimental and numerical results indicate that the absorptivity of the glass powder is nearly constant with respect to the processing parameters. Finally we show that higher quality parts can be created using a wire-fed instead of powder-bed process. Industrially, the additive manufacturing of glass is potentially relevant for gradient index optics, systems with embedded optics and applications where glass is used to form a hermetic seal.

Additive manufacturing (AM) has gained notoriety for offering advantages over traditional manufacturing methods, such as increased design complexity and flexibility. However, it has not found widespread use beyond rapid prototyping. One hindrance to the acceptance of AM processes in industry is the time and cost of fabrication per component. While metal AM by itself can be inexpensive, extra manufacturing steps in the form of subtractive manufacturing (SM) may need to be performed to reach final part tolerances, leading to hybrid additive-subtractive manufacturing (HASM) of a part, which increases time and cost. A potential area to reduce cost is through increasing the efficiency of the HASM process by conducting additive and subtractive manufacturing simultaneously. Usually, HASM is performed in a process where AM is completed in one machine or cell and transferred to another machine or cell for SM in a sequential assembly line process. This efficiency decreases part cost, but high aspect ratio parts or parts with internal geometry that require interleaved additive deposition and machining cannot be produced. One unexplored solution to simultaneous HASM that allows for interleaved operations is to operate the deposition head and machining spindle concurrently within the same machine envelope, known as concurrent HASM (CHASM). In this type of process, both AM and SM occur simultaneously on a batch of small parts or a single large part, maintaining a high efficiency without sacrificing the full range of complex geometries that AM allows for. A potential approach to the single-machine method could be to combine a robot and mill within the same envelope. A challenge to this approach, however, is control of both systems. Most machine controllers have limited external communication or, if a robot has been integrated, only offer movement of either the robot or mill at any given time. As a result, systems must pause either the AM or SM process to switch between them rather than working simultaneously. The present work investigates the positional accuracy of such a CHASM system comprised of a robotic arm and a 3-axis mill. Open-loop tests with limited communication between machines are performed on the system to verify positional error during concurrent robot-mill movements. Under certain conditions, it is demonstrated that position error can stay within 2 mm for the duration of a single layer; however, these tests show that, generally, the open-loop positioning performance of the system is inadequate for CHASM without part-specific hand-tuning of parameters. Based on these results, a set of requirements for successful robot-CNC CHASM is proposed for future integrations.

Additive manufacturing, characterized by its inherent layer by layer fabrication methodology has been coined by many as the latest revolution in the manufacturing industry. Due to its diversification of Materials, processes, system technology and applications, Additive Manufacturing has been synonymized with terminology such as Rapid prototyping, 3D printing, free-form fabrication, Additive Layer Manufacturing, etc. A huge media and public interest in the technology has led to an innovative attempt of exploring the technology for applications beyond the scope of the traditional engineering industry. Nevertheless, it is believed that a critical factor for the long-term success of Additive Manufacturing would be its ability to fulfill the requirements defined by the traditional manufacturing industry. A parallel development in market trends and product requirements has also lead to a wider scope of opportunities for Additive Manufacturing. The presented paper discusses some of the key challenges which are critical to ensure that Additive Manufacturing is truly accepted as a mainstream production technology in the industry. These challenges would highlight on various aspects of production such as product requirements, process management, data management, intellectual property, work flow management, quality assurance, resource planning, etc. In Addition, changing market trends such as product life cycle, mass customization, sustainability, environmental impact and localized production will form the foundation for the follow up discussion on the current limitations and the corresponding research opportunities. A discussion on ongoing research to address these challenges would include topics like process monitoring, design complexity, process standardization, multi-material and hybrid fabrication, new material development, etc.

Recently, there has been great interest in using additive manufacturing (AM) to produce spare parts: allowing to produce spare parts with short lead times and close to the point of use, AM reduces the need for large inventories otherwise required by conventional manufacturing (CM) techniques to deal with intermittent spare parts demand. However, using AM to produce spare parts is limited by two main drawbacks: high production costs and uncertain failure rates arising from AM still being a relatively new production technique. While the former can be counterbalanced by inventory cost reductions, it is unclear how the latter impacts the sourcing option decision (i.e. AM or CM). We aim to fill this gap by studying a periodic review model in which spare parts demands follow a Poisson process. To make our analysis accurate and reliable, we leverage a material science approach to obtain realistic values for the failure rate uncertainties. From the results, it emerges that AM is heavily penalized by failure rate uncertainties much higher than those of CM. Consequently, we then focus on some recent tools developed to reduce AM failure rate uncertainties: porosity assessment and in-situ monitoring. We find that the failure rate uncertainty should be reduced by five and six percentage points to make it worthwhile to invest in porosity assessment and in-situ monitoring, respectively. Finally, we determine under which circumstances each tool is preferred over the other and found that porosity assessment is typically the most competitive uncertainty reduction tool.

<p>Additive manufacturing (AM) or commonly called 3D printing (3DP) and rapid prototyping (RP) is a technique of blending materials by either fusion, binding, or solidifying materials. Despite many advantages of AM, there is a drawback of AM such as the surface quality may not be as good as subtractive machining (SM) process, therefore it will be better to have the initial shape forming process with AM and then finishing the required surface with SM process within a single setup. This paper presents the preliminary design of hybrid AM-SM machine to process a resin based material. The design includes structural design and control design of the machine using the material and firmware widely available in the market.</p><p align="center"><strong> </strong></p><strong>Keyword: </strong>Additive, Subtractive, Manufacturing, Hybrid Machine

This article reports on the first demonstration of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> , real-time dosimetry realized with an enhanced backscattering optical fiber, and a high-resolution optical backscattering reflectometry measurement. This work is devised to overcome the current problems in monitoring radiotherapy treatments, in particular, the difficult evaluation of not only the actual X-ray dose that is accumulated on the target volume but also the distribution profile of the ionizing radiation beam. Overall, the research aims at developing a dose sensor with the most demanding features of small form factor, spatial profiling, and remote interrogation. The experiments have been conducted by evaluating the spatial profile of radiation-induced spectral shift of the Rayleigh backscattering along an optical fiber exposed to X-rays. The sensing element is a section of specialty optical fiber whose Rayleigh backscattering signature changes under ionizing radiation. The specialty fiber is designed to exhibit an enhanced backscattering, in order to overcome the poor sensitivity to radiation of standard optical fibers that are normally, used in telecommunications. The enhanced sensitivity is achieved by doping the core with either aluminum or magnesium nanoparticles, and two different fibers have been fabricated and tested. The experimental results show the capability of real time detection of the radiation profile from high-dose rates (700 Gy/min) to low-dose rates (2 Gy/min). Moreover, different sensing mechanisms and responses to high- and low-dose rates are evidenced. A comparison with a quasi-distributed sensing system based on an array of fiber Bragg gratings (FBGs) is discussed, highlighting the superior performance of the backscattering approach in terms of sensitivity and spatial resolution, whereas the array of FBGs exhibits an advantage in terms of sampling speed.

The Adoption of Additive Manufacturing Technology in Sweden

The increasing demand for novel fiber design has brought major challenges with the current fabrication methods. Additive manufacturing is an innovative fabrication process that has been attracting attention to the optical fiber community. 3D printed porous bodies from commercial silica powder were produced based on selective laser sintering (SLS). Complex structures such as antiresonant fiber (ARF), photonic crystal fiber (PCF) and multicore fiber (MCF) preforms were produced by this method. Additionally, a multi-material fiber with a silica cladding and a GeO2-SiO2 core was fabricated from a 3D printed preform. The optical and physical properties of the fabricated 3D printed structures were reported. This Dataset support paper delivered at the International Society for optics and Photonics.SPIE Photonic West 1-6 Feb. 2020. San Francisco.

In today’s world, Additive Manufacturing (AM) is quickly becoming the dominant manufacturing technology. Massive development has occurred in recent decades, and it is occurring at a much faster rate. It has also progressed from simple prototype to actual end-use items and manufacturing tools. Various manufacturing processes, such as SLS, LENS, FDM, PolyJet, SLA, LTP, DMLS FDM, and binder jet printing, are produced using additive manufacturing techniques. Layer by layer material deposition/addition is a critical component in all these operations, which is why this technology is known as additive manufacturing. Rapid prototyping, 3D printing, digital manufacturing, and other such names are used. Automotive, Aerospace components, medical equipment parts, consumer goods and gadgets, fashion sector, jewelry, and other industries employ additive manufacturing.Currently all designed parts can manufacture using either subtractive or additive manufacturing processes. However, distinct design elements established for production provide additional manufacturing obstacles in metal substation and metal addition manufacturing procedures. As the number of parts made directly utilizing additive manufacturing techniques grows, it is critical to compile a list of the best design for manufacturing principles applicable for various additive manufacturing procedures. This will assist the design community in ensuring that items are developed for additive manufacturing rather than generic strategy and produced.The primary goal of this effort is to evaluate and comprehend the various additive processes and choose the optimal design for manufacturing procedures to be used. As a result, one should be prepared to select a suitable additive manufacturing process for printing based on the design aspects of the component to be produced.

A Porter's Five Forces Model Proposal for Additive Manufacturing Technology: A Case Study in Portuguese industry

In recent years, there has been widespread adoption of machine learning (ML) technologies to unravel intricate relationships among diverse parameters in various additive manufacturing (AM) techniques. These ML models excel at recognizing complex patterns from extensive, well-curated datasets, thereby unveiling latent knowledge crucial for informed decision-making during the AM process. The collaborative synergy between ML and AM holds the potential to revolutionize the design and production of AM-printed parts. This review delves into the challenges and opportunities emerging at the intersection of these two dynamic fields. It provides a comprehensive analysis of the publication landscape for ML-related research in the field of AM, explores common ML applications in AM research (such as quality control, process optimization, design optimization, microstructure analysis, and material formulation), and concludes by presenting an outlook that underscores the utilization of advanced ML models, the development of emerging sensors, and ML applications in emerging AM-related fields. Notably, ML has garnered increased attention in AM due to its superior performance across various AM-related applications. It is envisioned that the integration of ML into AM processes will significantly enhance 3D printing capabilities across diverse AM-related research areas.

Sustainable additive manufacturing supply chains with a plithogenic stakeholder analysis: Waste reduction through digital transformation

Additive manufacturing (AM) is a process that creates a three-dimensional (3D) physical object from a digital design by building layers of material directly from a computer-aided design (CAD) file, allowing for precise and rapid production of parts or prototypes. AM is increasingly recognised as a sustainable production method due to its potential to reduce waste, energy consumption, and environmental impact. The versatility and efficiency of AM have made it an essential tool for rapid prototyping and developing custom parts and components with intricate designs that were previously difficult or impossible to produce. This review highlights the significant progress in utilising AM for the synthesis of organic compounds and the fabrication of organic devices. AM technologies are used in the synthesis of organic compounds, particularly through the use of 3D-printed catalysts, reactors and flow systems. Advances in AM have enabled this technology to be used to synthesise organic compounds and produce low-cost, customised organic equipment. This makes it possible to obtain sophisticated reactors, laboratory equipment or their individual parts, tailored to a specific chemical process in more sustainable way. AM has great potential for advancing green and sustainable chemical processes, with the ability to integrate multiple enabling technologies and facilitate safer and more efficient processes in a cost-effective manner. Overall, the integration of AM in organic synthesis has opened up new possibilities for innovative solutions in the field.

The aim of this study was to systematically describe the additive manufacturing (AM) technologies used for various casting technologies and how rapid investment casting (RIC) is changing the field of casting. The capability and effectiveness of additive manufacturing to provide investment casting production solutions has been investigated. The traditional investment casting method is less efficient in terms of cost and time to develop new wax models of solid tooling for low volume production or prototypes. To overcome this problem, it is proposed to introduce additive manufacturing to these processes to produce investment casting models. This paper discusses specific applications of rapid prototyping in this area. The study concluded that the use of additive manufacturing for investment casting instead of the traditional method is more cost- and time-efficient. Terms and designations: RP – Rapid Prototyping, IC, RIC –(Rapid) Investment Casting, PM – Project Manager, AT – Additive technologies, AM – Additive manufacturing

Design for Additive Manufacturing (DfAM) encompasses two primary strategies: adapting traditional designs for 3D printing and developing designs specifically optimized for additive manufacturing. The latter emphasizes consolidating assemblies and reducing weight, leveraging complex geometries and negative space through advanced techniques such as generative design and topology optimization. Critical considerations in the design phase include printing methods, material selection, support structures, and post-processing requirements. DfAM offers significant advantages over conventional subtractive manufacturing, including enhanced complexity, customization, and optimization, with transformative applications in aerospace, medical devices, and automotive industries. This review focuses on the automotive sector, systematically examining DfAM’s potential to redefine vehicle design, production processes, and industry standards. By conducting a comprehensive analysis of the existing literature and case studies, this research identifies gaps in the integration of additive manufacturing into broader manufacturing frameworks. The study contributes to the literature by providing insights into how 3D printing is currently reshaping automotive production by offering a forward-looking perspective on its future implications for the industry.