Knowledge Reuse for Customization: Metamodels in an Open Design Community for 3d Printing

Theories of knowledge reuse posit two distinct processes: reuse for replication and reuse for innovation. We identify another distinct process, reuse for customization. Reuse for customization is a process in which designers manipulate the parameters of metamodels to produce models that fulfill their personal needs. We test hypotheses about reuse for customization in Thingiverse, a community of designers that shares files for three-dimensional printing. 3D metamodels are reused more often than the 3D models they generate. The reuse of metamodels is amplified when the metamodels are created by designers with greater community experience. Metamodels make the community's design knowledge available for reuse for customization-or further extension of the metamodels, a kind of reuse for innovation

3D Printing Path Reallocation for Concurrent IDEX Systems

3D Printing is a growing field of interest, with research topics and commercial advancements in materials, processes, and systems. One of these advancements is the introduction of Independent Dual Extrusion (IDEX) Fused Deposition Modeling (FDM) printers in both the enterprise and consumer space. The unique feature on these printers is their dual extruders, which allows them to use multiple materials to create a printed part. These two extruders, in collaboration with two hotends, are responsible for the controlled deposition of material. In present systems, only one hotend can operate on the part at a time. However, as implied by the name, the hotends can be positioned independently. Therefore, the ability to utilize the two hotends concurrently could significantly reduce print time, a behavior not presently available. In this document we develop an algorithm to enable Collaborative Dual Extrusion (CODEX) printing, a model in which both hotends can be utilized simultaneously on one part. To do so we outline a two-phase greedy algorithm for transforming an input GCode file, intended for a traditional FDM printer, into one that could be utilized on IDEX printers. This algorithm exploits the sequential nature of GCode to find large runs of concurrently printable 2 segments. These runs are then linked to produce output paths. Approximately 13,500 publicly available GCode files are utilized to test and validate the algorithm across three different conceptual models for IDEX printers. The first model provides a theoretical maximum upper bound on efficiency. The second represents a mechanically feasible model. The final model simulates those IDEX printers available today. We show an approximate 24% and 20% improvement for the first two models, and a 9% deterioration on the final model. The document concludes with a discussion of possible improvements and directions for future work

Do makerspaces represent scalable production models of community-based redistributed manufacturing?

This research explores the development of local community-based “makerspaces” as potential scalable forms of redistributed manufacturing (RDM). Makerspaces are rapidly emerging in post-industrial economies and have been identified as a catalyst of local regeneration in urban areas. However, their role in local production systems is limited. There is a gap in the literature, with respect to the evolution of makerspaces and their productive contribution. The purpose of this paper therefore is to identify, classify and examine the different types of makerspaces. Our focus is on the implementation characteristics that enable industrial production activity to take place. First, we used Leximancer (to identify from the literature) three types of makerspace. Second, we then identify five RDM implementation characteristics. The characteristics were integrated together to form the RDM-makerspace implementation model. Third, case studies were purposively selected to test and advance this model. They were subsequently classified as a Type 1 (educational), Type 2 (design) or Type 3 (production) makerspace. Only one of the case studies was classified as a fully evolved Type 3 production space. The findings concur with the literature that makerspaces tend to be primarily Type 1 or Type 2. Finally, the contribution to local production theory is emphasised

AN ALGORITHM FOR RECONSTRUCTING THREE-DIMENSIONAL IMAGES FROM OVERLAPPING TWO-DIMENSIONAL INTENSITY MEASUREMENTS WITH RELAXED CAMERA POSITIONING REQUIREMENTS, WITH APPLICATION TO ADDITIVE MANUFACTURING

Cameras are everywhere for security purposes and there are often many cameras installed close to each other to cover areas of interest, such as airport passenger terminals. These systems are often designed to have overlapping fields of view to provide different aspects of the scene to review when, for example, law enforcement issues arise. However, these cameras are rarely, if ever positioned in a way that would be conducive to conventional stereo image processing. To address this, issue an algorithm was developed to rectify images measured under such conditions, and then perform stereo image reconstruction. The initial experiments described here were set up using two scientific cameras to capture overlapping images in various cameras positons. The results showed that the algorithm was accurately reconstructing the three-dimensional (3-D) surface locations of the input objects. During the research an opportunity arose to further develop and test the algorithms for the problem of monitoring the fabrication process inside a 3-D printer. The geometry of 3-D printers prevents the location of cameras in the conventional stereo imaging geometry, making the algorithms described above seem like an attractive solution to this problem. The emphasis in 3-D printing on using extremely low cost components and open source software, and the need to develop the means of comparing observed progress in the fabrication process to a model of the device being fabricated posed additional development challenges. Inside the 3-D printer the algorithm was applied using two scientific cameras to detect the errors during the printing of the low-cost open-source RepRap style 3-D printer developed by the Michigan Tech’s Open Sustainability Technology Lab. An algorithm to detect errors in the shape of a device being fabricated using only one camera was also developed. The results show that a 3-D reconstruction algorithm can be used to accurately detect the 3-D printing errors. The initial development of the algorithm was in MATLAB. The cost of the MATLAB software might prevent it from being used by open-source communities. Thus, the algorithm was ported to Python and made open-source for everyone to use and customize. To reduce the cost, the commonly used and widely available inexpensive webcams were also used instead of the expensive scientific cameras. In order to detect errors around the printed part, six webcams were used, so there were 3 pairs of webcams and each pair were 120 degrees apart. The results indicated that the algorithms are precisely detect the 3-D printing errors around the printed part in shape and size aspects. With this low-cost and open-source approach, the algorithms are ready for wide range of use and applications

Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

Material extrusion-based additive manufacturing: G-code and firmware attacks and Defense frameworks

Additive Manufacturing (AM) refers to a group of manufacturing processes that create physical objects by sequentially depositing thin layers. AM enables highly customized production with minimal material wastage, rapid and inexpensive prototyping, and the production of complex assemblies as single parts in smaller production facilities. These features make AM an essential component of Industry 4.0 or Smart Manufacturing. It is now used to print functional components for aircraft, rocket engines, automobiles, medical implants, and more. However, the increased popularity of AM also raises concerns about cybersecurity. Researchers have demonstrated strength degradation attacks on printed objects by injecting cavities in the design file which cause premature failure and catastrophic consequences such as failure of the attacked propeller of a drone during flight. Since a 3D printer is a cyber-physical system that connects the cyber and physical domains in a single process chain, it has a different set of vulnerabilities and security requirements compared to a conventional IT setup. My Ph.D. research focuses on the cybersecurity of one of the most popular AM processes, Material Extrusion or Fused Filament Fabrication (FFF). Although previous research has investigated attacks on printed objects by altering the design, these attacks often leave a larger footprint and are easier to detect. To address this limitation, I have focused on attacks at the intermediate stage of slicing through minimal manipulations at the individual sub-process level. By doing so, I have demonstrated that it is possible to implant subtle defects in printed parts that can evade detection schemes and bypass many quality assessment checks. In addition to exploring attacks through design files or network layer manipulations, I have also proposed firmware attacks that cause damage to the printed parts, the printer, and the printing facility. To detect sabotage attacks on FFF process, I have developed an attack detection framework that analyzes the cyber and physical domain state of the printing process and detects anomalies using a series of estimation and comparison algorithms in time, space, and frequency domains. An implementation case study confirms that cyber-physical security frameworks are an effective solution against sophisticated sabotage attacks. The increasing use of 3D printing technology to produce functional components underscores the growing importance of compliance and regulations in ensuring their quality and safety. Currently, there are no standards or best practices to guide a user in making a critical printing setup forensically ready. Therefore, I am proposing a novel forensic readiness framework for material extrusion-based 3D printing that will guide standards organizations in formulating compliance criteria for important 3D printing setups. I am optimistic that my offensive and defensive research endeavors presented in this thesis will serve as a valuable resource for researchers and industry practitioners in creating a safer and more secure future for additive manufacturing

Exploring Attacks and Defenses in Additive Manufacturing Processes: Implications in Cyber-Physical Security

Many industries are rapidly adopting additive manufacturing (AM) because of the added versatility this technology offers over traditional manufacturing techniques. But with AM, there comes a unique set of security challenges that must be addressed. In particular, the issue of part verification is critically important given the growing reliance of safety-critical systems on 3D printed parts. In this thesis, the current state of part verification technologies will be examined in the con- text of AM-specific geometric-modification attacks, and an automated tool for 3D printed part verification will be presented. This work will cover: 1) the impacts of malicious attacks on AM using geometrically-modified 3D models, 2) a 3D part reconstruction approach from medical imaging scans, 3) a mesh alignment technique based on point set registration, de- signed to handle abnormal part geometries, and 4) an automatic error detection and defect visualization tool for comparing the geometric similarity of 3D printed parts to their intended geometries