Fostering skills for the 21st century: The role of Fab labs and makerspaces
پرورش مهارت برای قرن بیست و یکم: نقش آزمایشگاه های Fab و فضاهای سازندگان-2020
Based on a study of a network of fab labs and makerspaces, this article investigates the role that such ‘fabrication spaces’ can play in fostering 21st century skills. Using a combination of the two main 21st century skills frameworks—DigComp and EntreComp—developed by the EU Commission, we study by the means of two combined qualitative research methods—semi-structured interviews of 13 fab lab/makerspace founders, fol- lowed by a focus group with founders and policymaker—the entrepreneurial and digital skills that are fostered by these fab labs and makerspaces. Our findings are that while fab labs and makerspaces naturally foster some entrepreneurial 21st century skills, only explicit and proactive entrepreneurship and education programme en- able to foster the whole spectrum of these skills. In regard to technical skills, fab labs and makerspaces enable to develop skills beyond what is generally considered as 21st century digital skills, because they combine digital skills with hands-on ‘making’ skills, since they are themselves mixed environment, both digital and physical. Consequently, the growing importance of ‘maker technologies’ may force to redefine what 21st century skills should be.
Keywords: Entrepreneurship | Technology education | 21st Century Skills | Fab labs | Makerspaces | 3D printing
Vascularized neural constructs for ex-vivo reconstitution of blood-brain barrier function
سازه های عصبی عروقی برای بازسازی قبلی در داخل بدن و عملکرد سد خونی مغز-2020
Ex-vivo blood-brain barrier (BBB) model is of great value for studying brain function and drug development, but it is still challenging to engineer macroscale three-dimensional (3D) tissue constructs to recapitulate physiological and functional aspects of BBB. Here, we describe a delicate 3D vascularized neural constructs for ex-vivo reconstitution of BBB function. The tissue-engineered tissue construct is based on a multicomponent 3D coculture of four types of cells, which typically exist in the BBB and were spatially defined and organized to mimic the in vivo BBB structure and function. A porous polycaprolactone/poly (D,L-lactide-co-glycolide) (PCL/PLGA) microfluidic perfusion system works as the vasculature network, which was made by freeze-coating a 3D-printed sacrificial template. Endothelial cells were seeded inside the channels of the network to form 3D interconnected blood vessels; while other types of cells, including pericytes, astrocytes, and neurons, were co-cultured in a collagen matrix wrapping the vasculature network to derive a vascularized neural construct that recapitulates in vivo BBB function with great complexity and delicacy. Using this model, we successfully reconstituted BBB function with parameters that are similar to the in vivo condition, and demonstrated the identification of BBBpenetrating therapeutics by examining the molecular delivery to neuronal cells when relevant biologic molecules were applied to the vasculature circulation system of the neural construct.
Keywords: Tissue engineering | 3D printing | Organ on a chip | Blood-brain barrier | Vasculature network | Neuro-engineering | Drug screening
Application of a fuzzy-logic based model for risk assessment in additive manufacturing r&d projects
استفاده از یک مدل مبتنی بر منطق فازی برای ارزیابی ریسک در پروژه های تحقیق و توسعه افزودنی-2020
Experts from industry and academics have highlighted Additive Manufacturing (AM) as a technology that is revolutionizing manufacturing. AM is a process that consists of creating a three-dimensional object by incorporating layers of a material such as metal or polymer. This research studies risks associated with AM R&D Project Management. A significant set of risks with a potential negative impact on project objectives in terms of scope, schedule, cost and quality are identified through an extensive literature review. These risks are assessed through a survey answered by ninety academics and professionals with noteworthy sector expertise. This process is made by the measurement of two parameters: likelihood of occurrence and impact on project objectives. According to the responses of the experts, the level of relevance of each risk is calculated, innovatively, through a fuzzy logic-based model, specifically developed for this study, implemented in MATLAB Fuzzy Logic Toolbox. The results of this study show that the risks “Defects occurring during the manufacturing process”, “Defective design”, “Poor communication in the project team” and “Insufficient financing” are determined as the most critical in AM R&D Project Management. The proposed model is presented as a powerful new tool for organizations and academics, to prioritize the risks that are more critical to develop appropriate response strategies to achieve the success of their projects.
Keywords: Additive Manufacturing | 3D printing | Risk Assessment | Project Management | Fuzzy Logic
A novel biomimetic design of a 3D vascular structure for self-healing in cementitious materials using Murrays law
طراحی biomimetic جدید از ساختار عروقی سه بعدی برای بهبودی در مواد سیمانی با استفاده از قانون موری-2020
Nature has always been a source of inspiration in engineering applications and vascular networks, as in human skin and in a tree leaf, are one attribute that has received attention in the design of resilient structures. A vascular system houses healing agents within its hollow channels or interconnected networks which are incorporated within a cement matrix. It is the only self-healing approach that has the capability to address different scales of damage in cementitious materials. The main aim of this work is to develop a novel vascular network inspired by nature for self-healing in cementitious systems. To achieve this, a biomimetic three-dimensional (3D) vascular networkwas designed and generated followingMurrays lawfor circulatory blood volume transfer. The designed structureswere constructed through 3D printing and assessed in a cement-based matrix. One-dimensional (1D) and two-dimensional (2D) models were also designed, printed and embedded into cement prisms to compare with the 3Dvascular system. Load recoverywas used to assess recovery inmechanical properties after the sample was cracked and pumped with sodium silicate for 28 days. Mechanical testing assessed the compatibility of the system with the surrounding matrix as well as the functionality of the network in delivering and releasing the healing agent at the location of damage. This initial proof of conceptwork confirmed the ability of all vascular systems to deliver the healing agent after a damage event, and the 3D vascular system demonstrated a significantly enhanced healing performance.
Keywords: Vascular networks | Biomimetic structures | 3D printing | Self-healing | Cementitious materials
Challenges of 3D printing technology for manufacturing biomedical products: A case study of Malaysian manufacturing firms
چالش های فن آوری چاپ سه بعدی برای تولید محصولات زیست پزشکی: یک مطالعه موردی از شرکت های تولید مالزی-2020
Additive manufacturing has attracted increasing attention worldwide, especially in the healthcare, biomedical, aerospace, and construction industries. In Malaysia, insufficient acceptance of this technology by local industries has resulted in a call for government and local practitioners to promulgate the development of this technology for various industries, particularly for biomedical products. The current study intends to frame the challenges endured by biomedical industries who use 3D printing technology for their manufacturing processes. Qualitative methods, particularly in-depth interviews, were used to identify the challenges faced by manufacturing firms when producing 3D printed biomedical products. This work was able to identify twelve key challenges when deploying additive manufacturing in biomedical products and these include issues related to binder selection, poor mechanical properties, low-dimensional accuracy, high levels of powder agglomeration, nozzle size, distribution size, limited choice of materials, texture and colour, lifespan of materials, customization of fit and design, layer height, and, lastly, build-failure. Furthermore, there also are six challenges in the management of manufacturing biomedical products using 3D printing technology, and these include staff re-education, product pricing, limited guidelines, cyber-security issues, marketing, and patents and copyright. This study discusses the reality faced by 3D printing players when producing biomedical products in Malaysia, and presents a primary reference for practitioners in other developing countries.
Keywords: Business | Biomedical products | Additive manufacturing | 3D printing technology
Applying Neural-Network-Based Machine Learning to Additive Manufacturing: Current Applications, Challenges, and Future Perspectives
استفاده از یادگیری ماشین مبتنی بر شبکه عصبی برای تولید افزودنی: برنامه های فعلی ، چالش ها و دیدگاه های آینده-2019
Additive manufacturing (AM), also known as three-dimensional printing, is gaining increasing attention from academia and industry due to the unique advantages it has in comparison with traditional subtractive manufacturing. However, AM processing parameters are difficult to tune, since they can exert a huge impact on the printed microstructure and on the performance of the subsequent products. It is a difficult task to build a process–structure–property–performance (PSPP) relationship for AM using traditional numerical and analytical models. Today, the machine learning (ML) method has been demonstrated to be a valid way to perform complex pattern recognition and regression analysis without an explicit need to construct and solve the underlying physical models. Among ML algorithms, the neural network (NN) is the most widely used model due to the large dataset that is currently available, strong computational power, and sophisticated algorithm architecture. This paper overviews the progress of applying the NN algorithm to several aspects of the AM whole chain, including model design, in situ monitoring, and quality evaluation. Current challenges in applying NNs to AM and potential solutions for these problems are then outlined. Finally, future trends are proposed in order to provide an overall discussion of this interdisciplinary area.
Keywords: Additive manufacturing | 3D printing | Neural network | Machine learning | Algorithm
The emergence of the maker movement: Implications for entrepreneurship research
ظهور جنبش سازنده: پیامدهای تحقیق کارآفرینی-2019
The maker movement has been touted as a harbinger of the next industrial revolution. Through shared access to tools and digital fabrication technologies, makers can act as producers in the sharing economy and potentially increase entrepreneurship rates, catalyze advanced manufacturing, and spur economic development. We develop a model of the maker movement configured around social exchange, technology resources, and knowledge creation and sharing. We highlight opportunities for studying the conditions under which the movement might foster entrepreneurship outcomes and discuss how research on the maker movement can deepen our understanding of entrepreneurial teams and corporate entrepreneurship.
Keywords: Innovation | Learning | Expertise | Collaboration | Community | Makerspace | FabLab | Crowdsourcing | 3D printing | Prototype | Design
The barriers to the progression of additive manufacture: Perspectives from UK industry
موانع پیشرفت ساخت افزودنی: دیدگاههایی از صنعت انگلیس-2018
Additive manufacture (AM) is receiving significant attention globally, reflected in the volume of research being carried out to support the commercialisation of the technology for industrial applications and the interest shown by government and policy makers in the technology. The lack of distinction between 3D printing and AM, as well as the portrayal of some highly publicised applications, may imply that the technology is now firmly established. However, this is not the case. The aim of this study is to identify the current barriers to the progression of AM for end-use products from an industrial perspective and to understand the nature of those barriers. Case study research has been conducted with organisations in the UK aerospace, automotive, defence, heavy machinery and medical device industries. Eighteen barriers are identified: education, cost, design, software, materials, traceability, machine constraints, in-process monitoring, mechanical properties, repeatability, scalability, validation, standards, quality, inspection, tolerances, finishing and sterilisation. Explanation building and logic models are used to generalise the findings. The results are discussed in the context of current academic research on AM. The outcomes of this study help to inform the frontiers of research in AM and how AM research agendas can be aligned with the requirements for industrial applications.
keywords: 3D printing |Case study research |Additive layer manufacture |Aerospace |Automotive |Biomedical
Study for development of a patient-specific 3D printed craniofacial medical device: Design based on 3D virtual biomodels/ CAD/ RP
مطالعه برای توسعه یک دستگاه پزشکی سر و صورت بیمار خاص چاپ سه بعدی: طراحی بر اساس مدل های بیولوژیکی RP/CAD-2018
Reconstructive surgery field is looking for sustainable alternatives on its procedures, specifically on affordable alternatives to manufacturing processes for medical devices. This paper outlines a design process to develop 3D printed medical devices for reconstructive surgery in a specific patient who had congenital, oncological or traumatic fracture cases in the face and/or skull. The implementation of the design process strategy was supported using endogenous capabilities and resources at Universidad Industrial de Santander, which could be applied in developing countries. So, this approach might offer solutions adapted to the South American population. For this reason, the research framework was a specific patient implant method, defined by modeling integration technologies, those supported by 3D virtual biomodels, computer-aided design, and rapid prototyping tools. A deep research has carried out with some surgeons within reconstructive surgery field, identifying needs and requirements for each case through an iterative process. Expected results of this paper were a workflow definition for 3D printed medical device development for a specific patient. Five cases were processed through the proposed workflow. From those cases, main identified outputs were related to devices such as implants, prosthesis surgical cutting guides, and pre-surgical planning to be performed. The proposed workflow showed strong viability implementation in future services among different academics and health facilities located in developing countries.
Keywords : patient-specific implant PSI | 3D printed medical device | biomodels | virtual engineering
تکنولوژی پیشرفته تغییر شکل هوشمند برای تغییر شکل طراحی محصول ، تولید و بازیابی
سال انتشار: 2014 - تعداد صفحات فایل pdf انگلیسی: 18 - تعداد صفحات فایل doc فارسی: 29
این مقاله یک مرور کلی را بر روی تکنولوژی تغییر شکل هوشمند (ASMT ) با توجه به تمرکز بر روی مواد پلیمری انجام میدهد. علاوه بر این، برای معرفی مفهوم و اصول ASMT؛ کاربردهای احتمالی از ASMT بصورت تنها یا همراه با تکنیکهای بالغ موجود ( مثل چاپ سه بعدی و پاسخ سریع و غیره) در طراحی محصول و تولید و بازیابی آن نشان داده میشود. مشخص شده است که ASMT قادر است محدوده ای از رویکردهای قدرتمند را برای تغییر شکل بخشی از چرخه عمر ویا کل چرخه عمر محصولات فراهم نماید.
کلمات کلیدی: اثر تغییر شکل | تکنولوژی تغییر شکل | طراحی | تولید | بازیافت
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