3D Printing and Industrial Ecology

Additive Manufacturing (AM) enables the manufacture of three-dimensional components and products out of raw materials and three-dimensional design data. AM is also known as 3D printing is a set of emerging technologies that can be seen as a future of manufacturing. The ability of additive manufacturing in manufacturing complex products makes it more popular. Nowadays, many companies like aerospace, automotive, and healthcare industries are moving towards additive manufacturing for assembling their products. Many researches are being conducted in additive manufacturing to increase its efficiency. This chapter is a comprehensive study on future trends and technologies in additive manufacturing. Also, shows a comparison between additive manufacturing and subtractive manufacturing on different grounds. The article highlights the techniques that are currently being used in additive manufacturing and its future trends. The techniques include photopolymer, deposition, lamination, powder-based, etc. The trends in a number of papers published in additive manufacturing are shown. Both local and overseas research activities on additive manufacturing have been focusing on new processes, new materials, new software capabilities, and new applications of the emerging additive manufacturing technology. The article also includes predictions on the market value of additive manufacturing in its different sectors like hardware, software, materials, post-processing, etc.

The Manufacturing Automation course in the Mechanical Engineering program at the University of Connecticut (UConn) was one of the most popular courses in the ME curriculum. The students’ benefits from the course were already described in the companion paper [1]. In this paper the advantages of prototyping and part production through Subtractive Manufacturing (SM) and Additive Manufacturing (AM) are described. The paper discusses parts fabrication done as subtractive and additive manufacturing operations. This was done in the scope of the UConn Engineering i.e. in the ME and MEM programs where Manufacturing Automation and Senior Design courses are taught. Such operations were possible thanks to the equipment available at UConn School of Engineering and thanks to the cooperation with the creator of the Mastercam software - CNC Software Inc and aircraft engines and equipment manufacturer - Pratt & Whitney of East Hartford. The integration of design and manufacturing in the course was done through putting together the operations of conceptual design, geometric design and modeling of the parts designed during the course. The models of parts done by AM were created using 3D printing in ME Laboratory out of acrylonitrile butadiene styrene and different kinds of plastic and in PW/UConn laboratory using laser and electron beam AM machines. To demonstrate further integration of design and machining automation, the students were introduced to complicated problems of surfaces crossing, connections of surfaces and edges of cross sections of the tops and valleys. Thanks to the support and cooperation of the CNC Software, Inc., it was possible to show the students how to cut complicated surfaces on different computer numerically controlled (CNC) machines that ranged from three to nine degrees of freedom specifically designed for accurate and repeatable metal working. In addition, the additive manufacturing (AM) capabilities were introduced in the course thanks to the support of Pratt & Whitney/UConn Additive Manufacturing Laboratory located on the UConn campus. The AM machines are Arcam and laser machines that use electron and laser beams to meld titanium powder. The fabricated parts of high strengths are useful as rapid prototypes or in some cases as substitution parts in an existing mechanical systems. Thanks to the UConn Engineering program and support of the corporations: CNC Software, Inc. and P&W, students were introduced to the spectrum of modern Rapid Prototyping and part sintering operations going through subtractive and additive manufacturing. The process details of the theory, practice of operations, and recommendation for use of the technologies discussed above, as well as possibilities of further applications, are described in this paper. After learning the fundamentals of these processes, students are prepared to design and analyze parts as well as the process required for different machining capabilities. Methods to introduce students to the concepts of using laser and electron beams AM machine as well the prototype machining are described in the paper. Conclusions recommending the teaching methods of product SM and AM machining concepts and lessons learned are also pointed out.

Additive manufacturing of cementitious composites: Materials, methods, potentials, and challenges

This study was aimed at preparing zirconia samples via additive manufacturing (AM) and subtractive manufacturing (SM) and testing the following aspects: (1) the manufacturing accuracy of the zirconia samples and (2) the bond strength of porcelain to zirconia to evaluate the applicability of the zirconia fabricated by AM in dental clinics. We used three milling machines for SM (AR, K5, and UP) and a 3D printer for AM (AO). The manufacturing accuracy of the zirconia specimen in the internal and marginal areas was evaluated by superimposing techniques to calculate the root mean square (RMS) values. The bond strengths of porcelain to zirconia prepared via SM and AM were measured using a universal testing machine. The internal and marginal RMS values of the zirconia prepared by AM (AO) were within the range of those of the zirconia prepared by SM (AR, K5, and UP). Moreover, the bond strength value of the zirconia prepared by AM (35.12 ± 4.09 MPa) was significantly higher than that of the zirconia prepared by SM (30.26 ± 5.20 MPa). Therefore, AM technology has significant potential for applications in dentistry.

Additive manufacturing (AM), commonly known as 3D printing, has revolutionized the manufacturing landscape by enabling layer-by-layer fabrication of complex geometries from digital models. This paper provides a comprehensive overview of the evolution, current capabilities, and future directions of AM. Beginning with the historical rise of AM, it explores and compares its major technological categories, including material extrusion, vat photopolymerization, powder bed fusion, and directed energy deposition. Each technology is discussed with regard to standard classifications and operational mechanisms. It further examines the crucial role of material properties and selection, emphasizing how polymers, metals, ceramics, and composites influence mechanical performance and application suitability. The paper investigates the deployment of AM across industries such as aerospace, biomedical, automotive, construction, and consumer goods, highlighting transformative applications. Despite its benefits, AM faces challenges such as anisotropic mechanical properties, limited material diversity, high energy consumption, and scalability constraints. Recent advancements leveraging machine learning (ML) or (AI) integration are discussed, particularly in process monitoring, defect prediction, and print quality optimization. ML-integrated process optimization techniques are shown to enhance part performance and production efficiency. Additionally, this study compares AM with subtractive manufacturing (SM), focusing on material utilization, energy efficiency, and production flexibility. A life cycle assessment (LCA) is conducted to evaluate the environmental and economic impacts of AM technologies. Market analysis indicates substantial global growth of the AM industry, fueled by technological maturation and increasing demand for customized solutions. Finally, it projects future research directions, including the development of multi-material printing, integration of AI-driven adaptive systems, sustainable material innovations, and the role of AM in decentralized manufacturing. This holistic analysis affirms AM’s pivotal role in reshaping the future of manufacturing with enhanced sustainability, precision, and design freedom. Overall, this review offers a big-picture view of AM where it stands today and how it’s paving the way for a more innovative, sustainable, and flexible future in manufacturing.

Growing consciousness regarding the environmental impacts of additive manufacturing (AM) processes has led to research focusing on quantifying their environmental impacts using Life Cycle Assessment (LCA) methodology. The main objective of this paper is to review the state of the art of the existing LCA studies of AM processes. In this paper, a systematic literature review is carried out where a total of 77 papers focusing on LCA, including social-Life Cycle Assessment (S-LCA), are analyzed. Accordingly, the application of LCA methodology to different AM technologies was studied and different research themes such as the goal and scope of LCA studies, life cycle inventory data for different AM technologies, AM part quality and mechanical properties, the environmental, economic, and social performances of various AM technologies, and factors affecting AM´s sustainability potential were analyzed. Based on the critical analysis of the existing research, five major shortcomings of the existing research are realized: (i) some AM technologies are under studied; (ii) more focus only on the environmental sustainability dimension of AM, neglecting its economic and social dimensions; (iii) exclusion of AM pat quality and its mechanical performance from the sustainability assessment; (iv) not enough focus on the life cycle stages after product manufacture by AM; (v) effect of different product variables on AM´s sustainability not studied extensively. Lastly, based on these shortcomings realized, the following research directions for future works are suggested: (i) inclusion of new AM materials and technologies; (ii) transition to a triple-bottom-line sustainability assessment considering environmental, economic, and social dimensions of AM; (iii) extending the scope of LCA studies to post-manufacture stages of AM products; (iv) development of predictive environmental impact and cost models; (v) integration of quality and mechanical characterization with sustainability assessment of AM technologies.

This paper explores the critical role of spatiality and scale in industrial ecology (IE) research to promote circularity within the built environment. Traditional IE frameworks are predominantly a‐spatial and a‐political, overlooking the complex socio‐ecological–technological dynamics of urban–regional environments. This gap limits the development of holistic assessments and effective strategies for circularity, often externalizing political, economic, and societal implications. In this paper, we emphasize the need to integrate diverse spatial entities, such as social actors, natural resources, and infrastructure, into IE frameworks. Drawing on recent developments within the IE community (including insights from the ISIE 2023 conference) we demonstrate how multiple spatialities and politics are already integral to several areas of IE research and practice, such as circularity accounting and industrial symbiosis. We highlight how spatial concepts—such as urbanization patterns, geographic features, territory, place, and actor‐networks—reveal context‐specific drivers and barriers to circular transformation. We then leverage the concept of scales established across spatial sciences to introduce a typology of scales relevant to IE, and identify which scale types have yet to be operationalized in IE research. Given the potential analytical yield of each scale type, we advocate for a reflective multi‐scalar approach to incorporate multiple spatialities into IE research. Ultimately, we call for a spatial turn in re‐conceptualizing IE tools to support the transformation of the built environment toward circularity.

Additive manufacturing (AM), an enabler of Industry 4.0, recently opened limitless possibilities in various sectors covering personal, industrial, medical, aviation and even extra-terrestrial applications. Although significant research thrust is prevalent on this topic, a detailed review covering the impact, status, and prospects of artificial intelligence (AI) in the manufacturing sector has been ignored in the literature. Therefore, this review provides comprehensive information on smart mechanisms and systems emphasizing additive, subtractive and/or hybrid manufacturing processes in a collaborative, predictive, decisive, and intelligent environment. Relevant electronic databases were searched, and 248 articles were selected for qualitative synthesis. Our review suggests that significant improvements are required in connectivity, data sensing, and collection to enhance both subtractive and additive technologies, though the pervasive use of AI by machines and software helps to automate processes. An intelligent system is highly recommended in both conventional and non-conventional subtractive manufacturing (SM) methods to monitor and inspect the workpiece conditions for defect detection and to control the machining strategies in response to instantaneous output. Similarly, AM product quality can be improved through the online monitoring of melt pool and defect formation using suitable sensing devices followed by process control using machine learning (ML) algorithms. Challenges in implementing intelligent additive and subtractive manufacturing systems are also discussed in the article. The challenges comprise difficulty in self-optimizing CNC systems considering real-time material property and tool condition, defect detections by in-situ AM process monitoring, issues of overfitting and underfitting data in ML models and expensive and complicated set-ups in hybrid manufacturing processes.

Additive manufacturing (AM), commonly known as 3D printing, has garnered significant attention across various industries for its flexibility and simplicity in fabrication. This review explores the evolution of AM technologies, encompassing rapid prototyping and 3D printing, which have revolutionized conventional manufacturing processes. The paper discusses the transition from rapid prototyping to AM and highlights its role in creating fully customized products, optimizing topologies, and fabricating complex designs, especially in the aerospace, medical, automotive, defense energy and food industries. The study delves into the fundamental principles of 3D and 4D printing technologies, detailing their processes, materials, and applications. It provides an overview of the various AM techniques, such as Vat photopolymerization, powder bed fusion, material extrusion, and directed energy deposition, shedding light on their classifications and applications. Furthermore, the paper explores the emergence of 4D printing, which introduces an additional dimension of “time” to enable dynamic changes in printed structures. The role of AM in different industries, including aerospace, medical, automotive, energy, and Industry 4.0, is thoroughly examined. The aerospace sector benefits from AM's ability to reduce production costs and lead times, while the medical field leverages bioprinting for synthetic organ fabrication and surgical equipment development. Similarly, AM enhances flexibility and customization in automotive manufacturing, energy production, and Industry 4.0 initiatives Overall, this review provides insights into the growing significance of AM technologies and their transformative impact on various industries. It underscores the potential of 3D and 4D printing to drive innovation, optimize production processes, and meet the evolving demands of modern manufacturing.

Additive manufacturing technology overcomes the limitations imposed by traditional manufacturing techniques, such as fixtures, tools, and molds, thereby enabling a high degree of design freedom for parts and attracting significant attention. Combined with subtractive manufacturing technology, additive and subtractive hybrid manufacturing (ASHM) has the potential to enhance surface quality and machining accuracy. This paper proposes a method for simulating the additive and subtractive manufacturing process, enabling accurate deformation prediction during processing. The relationship between stress distribution and thermal stress deformation of thin-walled 316L stainless steel parts prepared by Laser Metal Deposition (LMD) was investigated using linear scanning with a laser displacement sensor and finite element simulation. The changes in stress and deformation of these thin-walled parts after milling were also examined. Firstly, 316L stainless steel box-shaped thin-walled parts were fabricated using additive manufacturing, and the profile information was measured using a Micro Laser Displacement Sensor. Then, finite element software was employed to simulate the stress and deformation of the box-shaped thin-walled part during the additive manufacturing process. The experiments mentioned were conducted to validate the finite element model. Finally, based on the simulation of the box-shaped part, a simulation prediction was made for the box-shaped thin-walled parts produced by two-stage additive and subtractive manufacturing. The results show that the deformation tendency of outward twisting and expanding occurs in the additive process to the box-shaped thin-walled part, and the deformation increases gradually with the increase of the height. Meanwhile, the milling process is significant for improving the surface quality and dimensional accuracy of the additive parts. The research process and results of the thesis have laid the foundation for further research on the influence of subtractive process parameters on the surface quality of 316L stainless steel additive parts and subsequent additive and subtractive hybrid manufacturing of complex parts.

BackgroundThis study presents different zirconia additive manufacturing (AM) materials and technologies while assessing the fit, hardness, and shear bond strength of crowns produced by AM and subtractive manufacturing (SM) methods, as well as their surface characteristics.MethodsZirconia crowns were fabricated using a 5-axis SM and five AM approaches, including four digital light processing principles and one stereolithography (SLA) technique. Each method utilized varying slurry delivery and light-curing mechanisms. The replica technique measured marginal and internal gaps (axial, line angle, and occlusal) between the crowns and abutments. The Vickers hardness and shear bond strength of crowns bonded with resin cement were assessed. Surface characteristics were analyzed with scanning electron microscopy (SEM) post-printing and sandblasting. The fit, hardness, and shear bond strength of crowns were manufactured through AM and SM methods. Sixty crowns were fabricated (10 per group). Statistical analysis was conducted using one-way analysis of variance (ANOVA) with Tukey post-hoc testing (α = 0.05).ResultsThe marginal fits were 48.45 µm and 42.83 to 81.95 µm for the S and AM groups, respectively. Significant differences were observed between groups (< 0.001), although all measurements fell within the clinical acceptance range (120 µm). The Vickers hardness measurements revealed that the SM group had a hardness of 1473.87 HV, whereas those of the AM groups ranged from 1441.94 to 1532.53 HV, showing statistically significant differences (P < 0.001). Shear bond strength measurements displayed 7.97 MPa and 6.97 to 8.97 MPa for the SM and AM groups, respectively, with no significant differences between the groups. SEM analysis of the crown surfaces revealed agglomerated zirconia particles with various grooves after sandblasting.ConclusionsZirconia crowns produced through the AM and SM methods demonstrated clinically acceptable marginal fit and ideal hardness exceeding 1200 HV. Some AM groups demonstrated higher hardness and shear bond strength than the SM group. The diverse physical and mechanical properties of various zirconia AM technologies suggest their selective use in specific clinical situations. Certain AM techniques, such as SLA spreading demonstrated comparable or even superior results to those of SM in terms of fit and hardness, indicating their potential as viable alternatives in clinical settings.

Manufacturing processes are typically divided into three categories: formative, subtractive, and additive. While formative and subtractive manufacturing processes are considered more traditional, additive manufacturing (AM) is a family of evolving technologies that are rapidly growing with techniques and constraints yet to be explored. In this paper, a life cycle assessment comparison of casting (formative), machining (subtractive), and three AM methods, namely, binder jetting (BJ), powder bed fusion (PBF), and novel bound powder extrusion (BPE) has been performed. To compare each method from the sustainability standpoint, a life cycle assessment was conducted on a double cardan H-yoke, as a case study, focusing on environmental metrics such as water consumption, energy requirements, and CO2 emissions. This study focuses on the environmental effects of the novel BPE process with respect to current traditional manufacturing and AM methods. The case study was divided into two scenarios of the original and topology-optimized H-yoke to investigate the potential environmental footprint reduction by utilizing the capability of AM in generating complex geometries. The results proved that casting, as a formative manufacturing process, is the most environmentally friendly option for large-scale production of the investigated processes. Among the AM technologies that have been studied, PBF was the most environmentally friendly choice when coupled with renewable energy, reducing the total CO2 emission by 9.2% when compared to casting. In contrast, BJ was more environmentally friendly when fossil fuel was assumed as the main source of energy, showing only an 8.7% increase in CO2 emissions. The novel BPE preformed equal to or just short of BJ in all metrics, showing only a 9.4% increase of CO2 emission using fossil fuel compared to the 41.7% increase seen by PBF, with respect to BJ. AM environmental metrics were significantly improved when the topology-optimized part was employed. Machining, as a subtractive method, performed the worst from the environmental perspective due to the initial billet size and the amount of material to be removed (wasted). The production time for each process was analyzed to display the feasibility of producing the cast study part in a mass manufacturing scenario. The LCA case study proves that the increased number of BPE manufacturing steps does not negatively affect the environmental impact of the process, based on current LCA data. However, the BPE process is the most time-consuming process and must be considered when selecting the method of manufacture.

Additive manufacturing (AM) is a recent emerging technology that is being adopted in various industry sectors and supply chains. Life cycle assessment (LCA) and life cycle costing (LCC) are powerful methods that can be used for assessing the environmental and economic performance of emerging manufacturing technologies. This study aims to evaluate the life cycle environmental impacts and cost of computerized numerical control-based (CNC) manufacturing and direct metal laser sintering technology (DMLS) through a cradle-to-gate life cycle analysis. This research has four main novel elements: (i) conducting a recent comprehensive review of metal AM and conventional manufacturing (CM) processes using a systematic method and meta-analysis (ii) comparing the conventional process “CNC machining” and the additive technology “direct metal laser sintering” from the environmental (LCA) and economic (LCC) perspectives, (iii) investigating the influence of geometry complexity and shape size factors on the environmental and cost performance of both manufacturing methods, and (iv) conducting a Monte Carlo simulation-based sensitivity analysis to tackle uncertainty in LCC input parameters. The midpoints and endpoints impact for CNC and AM processes were estimated using the Ecoinvent v3.8 database and ReCiPe (E) impact assessment method. The review revealed that global warming potential is one of the most widely studied environmental indicators; however, only 6% of the studies have investigated the life cycle economic impacts of AM technologies using sensitivity and uncertainty analysis. The results have shown that in terms of ReCiPe endpoints, DMLS has the highest environmental impact on human health while CM has more impact on the eco-system quality. Electricity consumption is the main contributor to environmental impact categories in both manufacturing technologies. This is due to the high electricity utilization for casting and milling conventionally manufactured parts and printing the AM parts. LCC net present values revealed that manufacturing all parts with AM costs 91% more compared to CNC. The LCC analysis has shown that AM is more suitable and cost-effective for parts with highly complex geometries. Whereas CNC machining was found to be economically feasible for large-sized and low-complexity parts. The Monte Carlo sensitivity analysis demonstrated that for the case of AM, the most significant parameter is the processing cost followed by material cost, which highlighted the importance of energy-efficient AM and dematerialization through design for circularity.

How has LCA been applied to 3D printing? A systematic literature review and recommendations for future studies

Additionally known as three-dimensional (3D) printing, additive manufacturing has made major advancements possible in the fields of engineering, business, the arts, education, and medical. Thanks to recent developments, it is now possible to print three-dimensional to create complex, useful living tissues, biocompatible substances, cells, and supporting structures are combined. Regenerative medicine is utilizing 3D bioprinting. Additive manufacturing technology, or 3D printing, has been labelled the “next big thing” and is predicted to overtake cell phones in popularity. 3D printers use digital templates to produce actual, three-dimensional items. Adding layers to a print, commonly referred to as additive manufacturing, allows for the use of more than a hundred different materials, including nylon, metal, and plastic. Applications for 3D printing can be found in many different industries, such as industrial design, manufacturing, dental, automotive, aerospace, civil engineering, education, jewellery, footwear, and geographic information systems. It has shown to be a simple and affordable solution for a variety of use cases. Using computer-aided design tools and programming, three-dimensional printing is a sophisticated technique that adds material to a base surface to create three-dimensional things. Additive layer manufacturing, also referred to as 3D printing, is the technique of creating three-dimensional things by depositing or solidifying material one layer at a time. Using a computer-aided design module, pharmaceutical components are organized in a three-dimensional pattern. Afterwards, the constituents are converted into a machine-readable format resembling the surface of a three-dimensional dosage form. 3D printing has been used for jewelry, shoe-making, architecture, engineering &amp; construction, the automotive industry as well as the aerospace field, dentistry and medicine, plus geographic information systems (GIS), civil engineering and education. After that stage of the process is completed, the surface transferred to the machine is then printed in different layers. Bioprinting is an interdisciplinary domain that integrates additive manufacturing with biology and material sciences to manufacture threedimensional structures representative of living organisms. The ability to create biological tissues and organs has attracted considerable attention in biomedical research owing to the rising demand for personalized medicine. This scenario propelled bioprinting forward which received much interest thus triggering comprehensive research efforts by various players such as companies, universities as well as research institutes. The goal of this book is to provide a thorough analysis of the complex and rapidly evolving field of bioprinting by critically analyzing and evaluating the existing scientific literature.