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
Process mining-based anomaly detection of additive manufacturing process activities using a game theory modeling approach
تشخیص ناهنجاری مبتنی بر استخراج فرآیند از فعالیت های فرآیند تولید مواد افزودنی با استفاده از رویکرد مدل سازی تئوری بازی-2020
As a new production procedure Additive Manufacturing will present a time-effective production system when adopted in distributed 3D printing mode. In this case, the distributed manufacturing leads to different challenges such as control between production sites. Based on the cloud infrastructure usage for distributed production systems, the product reliability handling is vital. Moreover, AM is used to produce safety–critical systems components and this product type defines AM as an interesting attack target. This study presents a new extension of uncertain Business Process Management System (uncertain BPMS) architecture for detecting anomaly using this extension capability. This extension has a new component as event-based anomaly detector, where intrusion detection can take place through an integration of process mining and game theory techniques. The proposed component could operate based on pre-processor, conformance checker, and anomaly detection optimizer modules. These modules can intelligently control the AM process activities between expected behavior and actual behavior using distributed event logs, a hybrid of highly accurate algorithms such as Improved Particle Swarm Optimization (IPSO), firefly, and AdaBoost algorithms inside the game theory modeling approach. In this case, the game theory technique as an optimizer provides optimal selection strategies for the proposed component to detect untrusted behaviors. The results of the new extension execution on a case study and its evaluation using Nash Equilibrium (NE) solution indicate that the proposed anomaly detector component is highly accurate in anomaly detection for AM process activities and can detect more attacks successfully through guidance of the game theory framework in the system.
Keywords: Event-based anomaly detection | Additive manufacturing | Business process management system | Process mining technique | Game theory modeling | Distributed production system
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
Consensus-oriented cloud manufacturing based on blockchain technology: An exploratory study
تولید ابر توافق گرا مبتنی بر فناوری بلاکچین : یک مطالعه اکتشافی-2019
In the era of cloud computing and Industry 4.0, significant research efforts on cloud manufacturing have been witnessed in recent years. Nevertheless, challenges, such as issues of trust, safety, payment, remain in this emerging area, which cause less confidence for industry to adopt cloud manufacturing. In this regard, the recent development of blockchain technology provides a potential viable solution thanks to its unique advantages in decentralization and security. As such, we propose a new framework of cloud manufacturing by integrating the blockchain technology. In essence, consensus-oriented mechanisms are employed to generate the operating standards for the blockchain cloud manufacturing model. Moreover, based on the open source Ethereum code, we construct a simulation case study for 3D printing services using the proposed framework. A consortium or federated blockchain is simulated which uses Proof-of-Authority (PoA) as the consensus algorithm of block generation. The simulation involves 939 job requests from 100 users, as well as 10 service providers. The k-nearest neighbors (KNN) algorithm is employed to recommend the service provider for each request. The results show that the provider’s score of service evaluation tends to be stabilize, and 934 requests for service are successfully fulfilled by the appropriate providers while the remaining 5 requests fail to be serviced.
Keywords: Cloud manufacturing | Blockchain technology | KNN | Ethereum | POA | Consensus-oriented
Digital academic entrepreneurship: The potential of digital technologies on academic entrepreneurship
کارآفرینی دانشگاهی دیجیتال: پتانسیل فناوری های دیجیتال در کارآفرینی دانشگاهی-2019
Todays digital technologies, such as social media, business analytics, the Internet of Things, big data, advanced manufacturing, 3D printing, cloud and cyber-solutions and MOOCs, permeate every private and public organization. However, even if this phenomenon has been analyzed for entrepreneurship in general, to the best of our knowledge, the impact of digital technologies on academic entrepreneurship remains not only slightly addressed. With the aim of filling this gap, this paper proposes a novel contribution regarding the emerging concept of Digital Academic Entrepreneurship. Based on a qualitative literature review, an interpretative framework for Digital Academic Entrepreneurship is deductively proposed that is composed of the following components: the rationale for the adoption of digital technologies for academic entrepreneurship (why), the emerging forms of digital academic entrepreneurship (what), the stakeholders involved through the digital technologies to achieve the academic entrepreneurship goal (who), and the processes of academic entrepreneurship supported by digital technologies (how). The discussion section provides a conceptualization of Digital Academic Entrepreneurship. The paper closes with the identification of a research agenda for this promising and under-researched field.
Keywords: Academic entrepreneurship | Digital academic entrepreneurship | Digital technologies | Entrepreneurial university
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