Development of a novel 3D simulation modelling system for distributed manufacturing

This paper describes a novel 3D simulation modelling system for supporting our distributed machine design and control paradigm with respect to simulating and emulating machine behaviour on the Internet. The system has been designed and implemented using Java2D and Java3D. An easy assembly concept of drag-and-drop assembly has been realised and implemented by the introduction of new connection features (unified interface assembly features) between two assembly components (modules). The system comprises a hierarchical geometric modeller, a behavioural editor, and two assemblers. During modelling, designers can combine basic modelling primitives with general extrusions and integrate CAD geometric models into simulation models. Each simulation component (module) model can be visualised and animated in VRML browsers. It is reusable. This makes machine design re-configurable and flexible. A case study example is given to support our conclusions

Symbiotic Assembly Systems – A New Paradigm

AbstractAssembly systems have been pressed in recent years to provide highly adaptable and quickly deployable solutions in order to deal with unpredictable changes following market trends. This has led to the development of multiple paradigms, namely Flexible Assembly System, Holonic Assembly Systems, Evolvable Assembly Systems, Modular Assembly systems, etc. Mostly these focus on increasing availability of automation, however this focus has overshadowed the human element in assembly systems. The lack of a clear human element in these approaches resulted in non-necessary automation and increase complexity. This paper proposes a new paradigm of Symbiotic Assembly Systems (SAS) in order to integrate the human aspects into these developments. The motivation is human actors should be treated as an intrinsic component of assembly systems. This would result in a system that can take advantage of its component's individual strengths (human or machines), and create a symbiotic environment. Beyond machine automation, human interventions in the system need not only to be modelled as processes but also integrated into the whole system operation. The idea builds on biological systems and their ability to establish symbiotic environments resulting in optimal collaborations. This paper proposes the conceptual vision of Symbiotic Assembly Systems and identifies the necessary developments required to achieve such paradigm. Furthermore it reports on how the developments from other paradigms can be integrated into SAS. An illustrative example is presented to demonstrate the potential of this approach

Quality-oriented design of rotor assembly strategies for electric drive production systems

Electric mobility is an emerging industrial sector that requires innovative quality control methods as common manufacturing and testing methods of combustion engines cannot be transferred directly to electric motors. This paper presents new solutions for the quantitative evaluation of quality-oriented rotor assembly strategies in electric drive production systems. The proposed methods assist the analysis of productivity and quality performance of two different assembly strategies namely selective assembly and sequential assembly. The impacts of these approaches are validated within a real industrial context, where state of the art quality and process control technologies show strong limitations. Experimental results have shown that the application of the proposed strategies yield a significant improvement in the production rate of conforming parts of the system. Moreover, the general applicability of these approaches to similar industrial problems encourages their adoption for defect reduction and elimination thus paving the way to zero-defect manufacturing paradigm

Uncovering Extremely Metal-Poor Stars in the Milky Way's Ultra-Faint Dwarf Spheroidal Satellite Galaxies

We present new metallicity measurements for 298 individual red giant branch stars in eight of the least luminous dwarf spheroidal galaxies (dSphs) in the Milky Way (MW) system. Our technique is based on medium resolution Keck/DEIMOS spectroscopy coupled with spectral synthesis. We present the first spectroscopic metallicities at [Fe/H] < -3.0 of stars in a dwarf galaxy, with individual stellar metallicities as low as [Fe/H] = -3.3. Because our [Fe/H] measurements are not tied to empirical metallicity calibrators and are sensitive to arbitrarily low metallicities, we are able to probe this extremely metal-poor regime accurately. The metallicity distribution of stars in these dSphs is similar to the MW halo at the metal-poor end. We also demonstrate that the luminosity-metallicity relation previously seen in more luminous dSph galaxies (M_V = -13.4 to -8.8) extends smoothly down to an absolute magnitude of M_V = -3.7. The discovery of extremely metal-poor stars in dSphs lends support to the LCDM galaxy assembly paradigm wherein dwarf galaxies dissolve to form the stellar halo of the MW.Comment: 5 pages, 5 figures, accepted for publication in ApJ

Binary pattern tile set synthesis is NP-hard

In the field of algorithmic self-assembly, a long-standing unproven conjecture has been that of the NP-hardness of binary pattern tile set synthesis (2-PATS). The $k$-PATS problem is that of designing a tile assembly system with the smallest number of tile types which will self-assemble an input pattern of $k$ colors. Of both theoretical and practical significance, $k$-PATS has been studied in a series of papers which have shown $k$-PATS to be NP-hard for $k = 60$, $k = 29$, and then $k = 11$. In this paper, we close the fundamental conjecture that 2-PATS is NP-hard, concluding this line of study. While most of our proof relies on standard mathematical proof techniques, one crucial lemma makes use of a computer-assisted proof, which is a relatively novel but increasingly utilized paradigm for deriving proofs for complex mathematical problems. This tool is especially powerful for attacking combinatorial problems, as exemplified by the proof of the four color theorem by Appel and Haken (simplified later by Robertson, Sanders, Seymour, and Thomas) or the recent important advance on the Erd\H{o}s discrepancy problem by Konev and Lisitsa using computer programs. We utilize a massively parallel algorithm and thus turn an otherwise intractable portion of our proof into a program which requires approximately a year of computation time, bringing the use of computer-assisted proofs to a new scale. We fully detail the algorithm employed by our code, and make the code freely available online

Multidomain Simulation Model for Analysis of Geometric Variation and Productivity in Multi-Stage Assembly Systems

Nowadays, the new era of industry 4.0 is forcing manufacturers to develop models and methods for managing the geometric variation of a final product in complex manufacturing environments, such as multistage manufacturing systems. The stream of variation model has been successfully applied to manage product geometric variation in these systems, but there is a lack of research studying its application together with the material and order flow in the system. In this work, which is focused on the production quality paradigm in a model-based system engineering context, a digital prototype is proposed to integrate productivity and part quality based on the stream of variation analysis in multistage assembly systems. The prototype was modelled and simulated with OpenModelica tool exploiting the Modelica language capabilities for multidomain simulations and its synergy with SysML. A case study is presented to validate the potential applicability of the approach. The proposed model and the results show a promising potential for future developments aligned with the production quality paradigm

UB Robot Swarm System: Design and Implementation

In this poster we described the hardware architecture of an inexpensive, heterogeneous, mobile robot swarm, designed and developed at RISC lab, University of Bridgeport. Each UB robot swarm is equipped with sensors, actuators, control and communication units, power supply, and interconnection mechanism. Robot swarms have become a new research paradigm in the last ten years offering novel approaches, such as self-reconfigurabity, self-assembly, self-replication and self-learning. Developing a multi-agent robot system with heterogeneity and larger behavioral repertoire is a great challenge. This robot swarm is capable of performing user defined tasks such as wall painting, mapping, human rescue operations, task allocation, obstacle avoidance, and object transportation

The genome of the protozoan parasite Cystoisospora suis and a reverse vaccinology approach to identify vaccine candidates

Vaccine development targeting protozoan parasites remains challenging, partly due to the complex interactions between these eukaryotes and the host immune system. Reverse vaccinology is a promising approach for direct screening of genome sequence assemblies for new vaccine candidate proteins. Here, we applied this paradigm to Cystoisospora suis, an apicomplexan parasite that causes enteritis and diarrhea in suckling piglets and economic losses in pig production worldwide. Using Next Generation Sequencing we produced an ∼84 Mb sequence assembly for the C. suis genome, making it the first available reference for the genus Cystoisospora. Then, we derived a manually curated annotation of more than 11,000 protein-coding genes and applied the tool Vacceed to identify 1,168 vaccine candidates by screening the predicted C. suis proteome. To refine the set of candidates, we looked at proteins that are highly expressed in merozoites and specific to apicomplexans. The stringent set of candidates included 220 proteins, among which were 152 proteins with unknown function, 17 surface antigens of the SAG and SRS gene families, 12 proteins of the apicomplexan-specific secretory organelles including AMA1, MIC6, MIC13, ROP6, ROP12, ROP27, ROP32 and three proteins related to cell adhesion. Finally, we demonstrated in vitro the immunogenic potential of a C. suis-specific 42 kDa transmembrane protein, which might constitute an attractive candidate for further testing

Local Digital Twin-based control of a cobot-assisted assembly cell based on Dispatching Rules

In the context of an increasing digitalization of production processes, Digital Twins (DT) are emerging as new simulation paradigm for manufacturing, which leads to potential advances in the production planning and control of production systems. In particular, DT can support production control activities thanks to the bidirectional connection in near real-time with the modeled system. Research on DT for production planning and control of automated systems is already ongoing, but manual and semi-manual systems did not receive the same attention. In this paper, a novel framework focused on a local DT is proposed to control a cobot-assisted assembly cell. The DT replicates the behavior of the cell, providing accurate predictions of its performances in alternative scenarios. Then, building on these predicted estimates, the controller selects, among different dispatching rules, the most appropriate one to pursue different performance objectives. This has been proven beneficial through a simulation assessment of the whole assembly line considered as testbed

Towards an ontology framework for the integrated design of modular assembly systems

Next generation manufacturing companies have to become highly responsive in order to succeed in an ever more rapidly changing global market. The ability to effectively develop and adapt their assembly facilities (systems) to changing requirements on demand plays a crucial role in achieving high responsiveness since the assembly process has to deal with the full inherent complexity of increasingly mass-customised products. This work was motivated by the current lack of a holistic assembly system design theory that would enable design environments to address the need for rapid system development and adaptation. The challenge is to create a common environment where domain experts can effectively collaborate while taking advantage of the best practices of their diverse domains. This thesis investigates how a domain ontology can help to overcome those challenges. The approach is taking advantage of the higher levels of standardisation inherent in the modular assembly system paradigm which is considered to be one of the fundamental enabling factors to achieve a high level of adaptation. A new ontology framework has been developed to support the design and adaptation of modular assembly systems (ONTOMAS). The ONTOMAS framework is based on engineering ontology principles structuring the domain using formalisms for aggregation, topology, taxonomies, and system theory principles. A number of design patterns have been identified and formalised to support key design decision-making tasks during the design of modular assembly systems. Furthermore, the function-behaviour-structure paradigm has been applied to capture the characteristics of modular assembly equipment at different levels of abstraction that reflect the specific needs of the engineering design process. The proposed ONTOMAS framework provides a sound foundation for computer based support tools to reduce the assembly system design effort and time while maintaining a high level of quality. An integrated design framework for the requirements driven specification of assembly processes and configuration of modular assembly system has been developed. The design approach applies the new formalisms of ONTOMAS to support the design decision-making activities. The developed ONTOMAS framework has been applied in several industrial and synthetic use cases to verify its applicability and appropriateness. Furthermore, the new ontology and design framework have been used as foundation for the development of a prototype collaborative design environment which allows different domain experts to participate in the design of modular assembly systems