Biblio

In this paper, we use selective laser melting (SLM) technology to fabricate AlNiCo magnetic materials, and the effects of laser processing parameters on the density and mechanical properties of AlNiCo magnetic materials were studied. We tested the magnetic properties of the heat-treated magnets. The results show that both laser power and scanning speed affect the forming. In this paper, the influence of laser power on the density of samples far exceeds the scanning speed. Through the experiment, we obtained the optimal range of process parameters: laser power (150 170W) and laser scanning speed (800 1000mm/s). Although the samples formed within this range have higher density, there are still many cracks, further research work should be done.

An increasing number of industries around the world are adopting advance manufacturing technologies for product design, among which additive manufacturing (AM) is gaining attention among aerospace, defense, automotive and health care domains. Products with complicated designs demanding lesser weight, improved performance and conformance are manufactured by companies using AM technologies. Some noticeable examples of ducting, airflow system and vent products in the aerospace domain can be seen being made out of AM techniques. One of the benefits being mentioned is the significant reduction in the number of components going into a finished product, thereby impacting the supply chain as well. However, one of the challenges in AM process is to reduce the process variation which affects the reliability of the product. To realize the true benefits of additively manufactured products, it is imperative to ensure that the reliability of AM products is similar or better than traditionally manufactured products. Current state of art for assessing reliability of traditionally manufactured products is mature. However, the reliability assessment framework for products manufactured by advanced technologies are being studied upon. In this direction, this paper highlights a structured reliability assessment framework for additive manufactured products, which will help in identifying, analyzing and mitigating reliability risks as part of product development life cycle.

Within “Industrie 4.0” approach 3D printing technology is characterized as one of the disruptive innovations. Conventional supply chains are replaced by value-added networks. The spatially distributed development of printed components, e.g. for the rapid delivery of spare parts, creates a new challenge when differentiating between “original part”, “copy” or “counterfeit” becomes necessary. This is especially true for safety-critical products. Based on these changes classic branded products adopt the characteristics of licensing models as we know them in the areas of software and digital media. This paper describes the use of digital rights management as a key technology for the successful transition to Additive Manufacturing methods and a key for its commercial implementation and the prevention of intellectual property theft. Risks will be identified along the process chain and solution concepts are presented. These are currently being developed by an 8-partner project named SAMPL (Secure Additive Manufacturing Platform).

Additive manufacturing (AM, or 3D printing) is a novel manufacturing technology that has been adopted in industrial and consumer settings. However, the reliance of this technology on computerization has raised various security concerns. In this paper, we address issues associated with sabotage via tampering during the 3D printing process by presenting an approach that can verify the integrity of a 3D printed object. Our approach operates on acoustic side-channel emanations generated by the 3D printer’s stepper motors, which results in a non-intrusive and real-time validation process that is difficult to compromise. The proposed approach constitutes two algorithms. The first algorithm is used to generate a master audio fingerprint for the verifiable unaltered printing process. The second algorithm is applied when the same 3D object is printed again, and this algorithm validates the monitored 3D printing process by assessing the similarity of its audio signature with the master audio fingerprint. To evaluate the quality of the proposed thresholds, we identify the detectability thresholds for the following minimal tampering primitives: insertion, deletion, replacement, and modification of a single tool path command. By detecting the deviation at the time of occurrence, we can stop the printing process for compromised objects, thus saving time and preventing material waste. We discuss various factors that impact the method, such as background noise, audio device changes and different audio recorder positions.

This paper introduces a research agenda focusing on cybersecurity in the context of product lifecycle management. The paper discusses research directions on critical protection techniques, including protection techniques from insider threat, access control systems, secure supply chains and remote 3D printing, compliance techniques, and secure collaboration techniques. The paper then presents an overview of DBSAFE, a system for protecting data from insider threat.