Virtual bloXing - assembly rapid prototyping for near net shapes

Virtual reality (VR) provides another dimension to many engineering applications. Its immersive and interactive nature allows an intuitive approach to study both cognitive activities and performance evaluation. Market competitiveness means having products meet form, fit and function quickly. Rapid Prototyping and Manufacturing (RP&M) technologies are increasingly being applied to produce functional prototypes and the direct manufacturing of small components. Despite its flexibility, these systems have common drawbacks such as slow build rates, a limited number of build axes (typically one) and the need for post processing. This paper presents a Virtual Assembly Rapid Prototyping (VARP) project which involves evaluating cognitive activities in assembly tasks based on the adoption of immersive virtual reality along with a novel nonlayered rapid prototyping for near net shape (NNS) manufacturing of components. It is envisaged that this integrated project will facilitate a better understanding of design for manufacture and assembly by utilising equivalent scale digital and physical prototyping in one rapid prototyping system. The state of the art of the VARP project is also presented in this paper

Virtual assembly rapid prototyping of near net shapes

Virtual reality (VR) provides another dimension to many engineering applications. Its immersive and interactive nature allows an intuitive approach to study both cognitive activities and performance evaluation. Market competitiveness means having products meet form, fit and function quickly. Rapid Prototyping and Manufacturing (RP&M) technologies are increasingly being applied to produce functional prototypes and the direct manufacturing of small components. Despite its flexibility, these systems have common drawbacks such as slow build rates, a limited number of build axes (typically one) and the need for post processing. This paper presents a Virtual Assembly Rapid Prototyping (VARP) project which involves evaluating cognitive activities in assembly tasks based on the adoption of immersive virtual reality along with a novel non-layered rapid prototyping for near net shape (NNS) manufacturing of components. It is envisaged that this integrated project will facilitate a better understanding of design for manufacture and assembly by utilising equivalent scale digital and physical prototyping in one rapid prototyping system. The state of the art of the VARP project is also presented in this paper

Workstation Configuration and Process Planning for RLW Operations

The application of Remote Laser Welding (RLW) has become an attractive assembly technology in various branches of industry, as it offers higher efficiency at lower costs compared to traditional Resistance Spot Welding (RSW) when high volumes of sheet metal assemblies are to be produced. However, the introduction of RLW technology raises multiple new issues in designing the configuration, the layout, and the behavior of the assembly system. Since configuring an RLW workstation and planning the welding process are closely interrelated problems, a hierarchical decision process must be applied where configuration and planning go hand in hand. The paper presents a hierarchical workflow forworkstation configuration and process planning for RLW operations, and proposes methods for solving the decision problems related to each step of this workflow. A software toolbox is introduced that has been developed to facilitate a semi-Automatic, mixed-initiative workstation design and t o guide the expert user throughout the configuration, planning, programming, evaluation, and simulation of the RLW workstation. A case study from the automotive industry is presented, where the software tools developed are applied to configuring and planning the behavior of an RLW workstation that replaces RSW technology in assembling a car door

On-Demand Big Data Integration: A Hybrid ETL Approach for Reproducible Scientific Research

Scientific research requires access, analysis, and sharing of data that is distributed across various heterogeneous data sources at the scale of the Internet. An eager ETL process constructs an integrated data repository as its first step, integrating and loading data in its entirety from the data sources. The bootstrapping of this process is not efficient for scientific research that requires access to data from very large and typically numerous distributed data sources. a lazy ETL process loads only the metadata, but still eagerly. Lazy ETL is faster in bootstrapping. However, queries on the integrated data repository of eager ETL perform faster, due to the availability of the entire data beforehand. In this paper, we propose a novel ETL approach for scientific data integration, as a hybrid of eager and lazy ETL approaches, and applied both to data as well as metadata. This way, Hybrid ETL supports incremental integration and loading of metadata and data from the data sources. We incorporate a human-in-the-loop approach, to enhance the hybrid ETL, with selective data integration driven by the user queries and sharing of integrated data between users. We implement our hybrid ETL approach in a prototype platform, Obidos, and evaluate it in the context of data sharing for medical research. Obidos outperforms both the eager ETL and lazy ETL approaches, for scientific research data integration and sharing, through its selective loading of data and metadata, while storing the integrated data in a scalable integrated data repository.Comment: Pre-print Submitted to the DMAH Special Issue of the Springer DAPD Journa

Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure

IkeaBot: An autonomous multi-robot coordinated furniture assembly system

We present an automated assembly system that directs the actions of a team of heterogeneous robots in the completion of an assembly task. From an initial user-supplied geometric specification, the system applies reasoning about the geometry of individual parts in order to deduce how they fit together. The task is then automatically transformed to a symbolic description of the assembly-a sort of blueprint. A symbolic planner generates an assembly sequence that can be executed by a team of collaborating robots. Each robot fulfills one of two roles: parts delivery or parts assembly. The latter are equipped with specialized tools to aid in the assembly process. Additionally, the robots engage in coordinated co-manipulation of large, heavy assemblies. We provide details of an example furniture kit assembled by the system.Boeing Compan

Immersive Computing Technology to Investigate Tradeoffs Under Uncertainty in Disassembly Sequence Planning

The scientific and industrial communities have begun investigating the possibility of making product recovery economically viable. Disassembly sequence planning may be used to make end-of-life product take-back processes more cost effective. Much of the research involving disassembly sequence planning relies on mathematical optimization models. These models often require input data that is unavailable or can only be approximated with high uncertainty. In addition, there are few mathematical models that include consideration of the potential of product damage during disassembly operations. The emergence of Immersive Computing Technologies (ICT) enables designers to evaluate products without the need for physical prototypes. Utilizing unique 3D user interfaces, designers can investigate a multitude of potential disassembly operations without resorting to disassembly of actual products. The information obtained through immersive simulation can be used to determine the optimum disassembly sequence. The aim of this work is to apply a decision analytical approach in combination with immersive computing technology to optimize the disassembly sequence while considering trade-offs between two conflicting attributes: disassembly cost and damage estimation during disassembly operations. A wooden Burr puzzle is used as an example product test case. Immersive human computer interaction is used to determine input values for key variables in the mathematical model. The results demonstrate that the use of dynamic programming algorithms coupled with virtual disassembly simulation is an effective method for evaluating multiple attributes in disassembly sequence planning. This paper presents a decision analytical approach, combined with immersive computing techniques, to optimize the disassembly sequence. Future work will concentrate on creating better methods of estimating damage in virtual disassembly environments and using the immersive technology to further explore the feasible design space