An assembly oriented design framework for product structure engineering and assembly sequence planning

The paper describes a novel framework for an assembly-oriented design (AOD) approach as a new functional product lifecycle management (PLM) strategy, by considering product design and assembly sequence planning phases concurrently. Integration issues of product life cycle into the product development process have received much attention over the last two decades, especially at the detailed design stage. The main objective of the research is to define assembly sequence into preliminary design stages by introducing and applying assembly process knowledge in order to provide an assembly context knowledge to support life-oriented product development process, particularly for product structuring. The proposed framework highlights a novel algorithm based on a mathematical model integrating boundary conditions related to DFA rules, engineering decisions for assembly sequence and the product structure definition. This framework has been implemented in a new system called PEGASUS considered as an AOD module for a PLM system. A case study of applying the framework to a catalytic-converter and diesel particulate filter sub-system, belonging to an exhaust system from an industrial automotive supplier, is introduced to illustrate the efficiency of the proposed AOD methodology

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Integrated product relationships management : a model to enable concurrent product design and assembly sequence planning

The paper describes a novel approach to product relationships management in the context of concurrent engineering and product lifecycle management (PLM). Current industrial practices in product data management and manufacturing process management systems require better efficiency, flexibility, and sensitivity in managing product information at various levels of abstraction throughout its lifecycle. The aim of the proposed work is to manage vital yet complex and inherent product relationship information to enable concurrent product design and assembly sequence planning. Indeed, the definition of the product with its assembly sequence requires the management and the understanding of the numerous product relationships, ensuring consistency between the product and its components. This main objective stresses the relational design paradigm by focusing on product relationships along its lifecycle. This paper gives the detailed description of the background and models which highlight the need for a more efficient PLM approach. The proposed theoretical approach is then described in detail. A separate paper will focus on the implementation of the proposed approach in a PLM-based application, and an in-depth case study to evaluate the implementation of the novel approach will also be given

A computer-based product classification and component detection for demanufacturing processes

This is an Author's Accepted Manuscript of an article published in International Journal of Computer Integrated Manufacturing, 24(10), 900-914, 2011 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/0951192X.2011.579169.The aim of this paper is to propose a novel computer-based product classification, component detection and tracking for demanufacturing and disassembly process. This is achieved by introducing a series of automated and sequential product scanning, component identification, image analysis and sorting – leading to the development of a bill of material (BOM). The produced BOM can then be associated with the relevant disassembly/demanufacture proviso. The proposed integrated image sorting and product classification (ISPC) approach can be considered as a step forward in automation of demanufacturing activities. The ISPC model proposed in this paper utilises and builds on the state-of-the-art technology and current body of research in computer-integrated demanufacturing and remanufacturing (CIDR). An appraisal of the latest research material and the factors that inhibit CIDR methods inpractice are presented. A novel solution for the integration of imaging and material identification techniques toovercome some of the existing shortcomings of automated recycling processes is proposed in this paper. The proposed product scanning and component detection ISPC software consists of four distinct models: the repertory database, the search engine, the product-attributes updater and the image sorting and classification algorithm. The software framework that integrates the four components is presented in this paper. Finally, an overall assessment of applying ISPC at various stages of CIDR processes concludes the article.University of Ibadan MacArthur Foundation Gran

Planning robot actions under position and shape uncertainty

Geometric uncertainty may cause various failures during the execution of a robot control program. Avoiding such failures makes it necessary to reason about the effects of uncertainty in order to implement robust strategies. Researchers first point out that a manipulation program has to be faced with two types of uncertainty: those that might be locally processed using appropriate sensor based motions, and those that require a more global processing leading to insert new sensing operations. Then, they briefly describe how they solved the two related problems in the SHARP system: how to automatically synthesize a fine motion strategy allowing the robot to progressively achieve a given assembly relation despite position uncertainty, and how to represent uncertainty and to determine the points where a given manipulation program might fail

Octree-based production of near net shape components

Near net shape (NNS) manufacturing refers to the production of products that require a finishing operation of some kind. NNS manufacturing is important because it enables a significant reduction in: machining work, raw material usage, production time, and energy consumption. This paper presents an integrated system for the production of near net shape components based on the Octree decomposition of 3-D models. The Octree representation is used to automatically decompose and approximate the 3-D models, and to generate the robot instructions required to create assemblies of blocks secured by adhesive. Not only is the system capable of producing shapes of variable precision and complexity (including overhanging or reentrant shapes) from a variety of materials, but it also requires no production tooling (e.g., molds, dies, jigs, or fixtures). This paper details how a number of well-known Octree algorithms for subdivision, neighbor findings, and tree traversal have been modified to support this novel application. This paper ends by reporting the construction of two mechanical components in the prototype cell, and discussing the overall feasibility of the system

NASA space station automation: AI-based technology review

Research and Development projects in automation for the Space Station are discussed. Artificial Intelligence (AI) based automation technologies are planned to enhance crew safety through reduced need for EVA, increase crew productivity through the reduction of routine operations, increase space station autonomy, and augment space station capability through the use of teleoperation and robotics. AI technology will also be developed for the servicing of satellites at the Space Station, system monitoring and diagnosis, space manufacturing, and the assembly of large space structures

Probabilistic Methodology and Techniques for Artefact Conception and Development

The purpose of this paper is to make a state of the art on probabilistic methodology and techniques for artefact conception and development. It is the 8th deliverable of the BIBA (Bayesian Inspired Brain and Artefacts) project. We first present the incompletness problem as the central difficulty that both living creatures and artefacts have to face: how can they perceive, infer, decide and act efficiently with incomplete and uncertain knowledge?. We then introduce a generic probabilistic formalism called Bayesian Programming. This formalism is then used to review the main probabilistic methodology and techniques. This review is organized in 3 parts: first the probabilistic models from Bayesian networks to Kalman filters and from sensor fusion to CAD systems, second the inference techniques and finally the learning and model acquisition and comparison methodologies. We conclude with the perspectives of the BIBA project as they rise from this state of the art