Layer-by-Layer: Opportunities in 3D printing Technology trends, growth drivers and the emergence of innovative applications in 3D printing
Notice bibliographique
Résumé
Additive Manufacturing (AM) is a manufacturing process that deposits materials layer-by-layer to build a tangible product. The most common, and the most popular currently, is 3D printing. AM is claimed to have triggered a third industrial revolution because the technology presents new and expanding technical, economical and social impacts (Economist, 2012). Particularly, the increased accessibility to 3D printing capabilities has allowed mass customization to become more widespread in industries such as healthcare and consumer markets. Since the advent of mass production in the early 20th century, consumers’ demands have been met by producing large numbers of goods in significantly less time than ever before. While production time and price decreased, they did so at the expense of customization. AM makes it possible to offer customers options to personalize the products and goods they are purchasing, from custom-made prosthetics to a personalized smartphone case. The importance of customization cannot be understated. Researchers agree that customization will continue to grow as a major trend across industries. J.P. Gownder, vice president and principal analyst for infrastructure and operations professionals for Forrester, says that while “mass customization has long been the next big thing in product strategy … changes in customer-facing technology are opening up new opportunities for product strategists to bring customers into product design, creating both customer loyalty and higher margins” (Forrester, 2011, p. 12). Marina Wall of the Heinz Nixdorf Institute at the University of Paderborn also contends that, “individuality or mass customization are important trends driving change so increased product diversity is important for the future and for meeting individual customer requirements. AM has great potential for freedom of design that can cope with these challenges” (as cited in AM Platform, 2013, p. 29). 3D printing is expected to play a significant role in the future of mass customization. This report explores the potential impact that this technology may have in various sectors. Through secondary research and conversations with business analysts, investors, members of the 3D printing community, experts and entrepreneurs, we investigated some of the potential market opportunities the technology is unveiling. We also explore sources of capital and nascent business models for those innovators interested in capitalizing on this technology. As part of our investigation, we also profile some organizations involved with 3D printing or related markets. These entrepreneurs are actively and creatively pushing the limits of 3D technology. For the purposes of this document, the terms 3D printing and additive manufacturing will be used interchangeably.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,002 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,003 |
| Communication savante | 0,012 | 0,019 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,003 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».