Developing and applying an integrated modular design methodology within a SME

Modularity within a product can bring advantages to the design process by facilitating enhanced design reuse, reduced lead times, decreased cost and higher levels of quality. While the benefits of modularity are becoming increasingly better known, at present it is usually left to the designers themselves to introduce modularity into products. Studies into modularity have shown that byimplementing 'formal' methods, further benefits can be made in terms of time, cost, quality and performance. Current approaches that have been proposed for the formal development of modular design methodologies fail to accurately represent knowledge that is inherently produced during design projects and fail to consider design from the different viewpoints of the development process. This work, built on previous work on modularity and design for reuse, aims to develop an integrated design methodology that will optimise the modules created through the design process and allow for modularity to be 'built-in' to product development from the initial stages. The methodology andassociated tools have been developed to provide an easy-to-use approach to modularity that has support for design rationales and company knowledge that aid in effective design decision making. The methodology, named GeMoCURE, provides an integrated total solution to modular design based on reuse of proven physical and knowledge modules. Its incremental nature allows for the optimalstructure to be maintained as the design progresses. A special focus has been on the application of this approach for Small to Medium Enterprises (SMEs), which are typically challenged by a lack of design human resources and expertise

Validation of purdue engineering shape benchmark clusters by crowdsourcing

The effective organization of CAD data archives is central to PLM and consequently content based retrieval of 2D drawings and 3D models is often seen as a "holy grail" for the industry. Given this context, it is not surprising that the vision of a "Google for shape", which enables engineers to search databases of 3D models for components similar in shape to a query part, has motivated numerous researchers to investigate algorithms for computing geometric similarity. Measuring the effectiveness of the many approaches proposed has in turn lead to the creation of benchmark datasets against which researchers can compare the performance of their search engines. However to be useful the datasets used to measure the effectiveness of 3D retrieval algorithms must not only define a collection of models, but also provide a canonical specification of their relative similarity. Because the objective of shape retrieval algorithms is (typically) to retrieve groups of objects that humans perceive as "similar" these benchmark similarity relationships have (by definition) to be manually determined through inspection

Emulation of modular manufacturing machines

A method for geometrically modelling and emulating modular machines based on the Universal Machine Control reference architecture is described. Geometric modelling is achieved through extensions to a proprietary robot simulation system. A library of modules consisting of 1, 2 or 3 degree of freedom manipulators is used to construct models of multi-degree of freedom distributed machines with appropriate kinematic characteristics. Logging of data from the real or emulated control handlers is then used to drive the geometric model. A case study of a printed circuit board assembly machine is used to demonstrate how this approach allows the investigation of machine performance before and during the building of the machine with real hardware elements

An intelligent task programming system for modular manufacturing machines

Modular manufacturing machines characterised by their configuration flexibility and low initial investment have increasingly gained more recognition as one of the flexible and responsive manufacturing machinery in current competitive manufacturing industry. Programming of a modular machine is a very important part of an entire machine design and simulation environment. This paper focuses on the programming issue of a modular machine design and simulation environment. A programming study is made of the features of modular machines in manufacturing, and a general systematic approach towards high level utilisation and control of modular machines is outlined. A three-level machine task programming approach within the simulation environment is described and finally an example task program and its execution in simulation environment is illustrated to demonstrate the system capability

Generalized approach to the modelling of modular machines

This paper describes a method of graphically simulating modular machines within a computer aided design environment. This forms part of a much larger Science and Engineering Research Council (SERC) funded programme aimed at advancing modern practices when designing and building manufacturing machines. A generalized approach to the synthesis of the generic features of various kinematic motion pairs is presented and prismatic and revolute motion primitives generalized in their functional and geometric aspects. A hierarchical ring and tree data structure has been designed and implemented to comprehensively represent these motion pairs and to simulate their performance. More complex modular manufacturing machines can be represented using information from a library of up to three degree of freedom motion modules. Seven two degree of freedom motion primitives and twelve three degree of freedom motion primitives with articulation configurations have been analyzed and included in the motion primitive library. The configuration of modular machines comprised of physically separate but logically connected distributed motion primitives are described. Examples of a two-finger industrial robot gripper and a three-finger industrial robot hand are used to demonstrate the general principles

Geometric reasoning via internet crowdsourcing

The ability to interpret and reason about shapes is a peculiarly human capability that has proven difficult to reproduce algorithmically. So despite the fact that geometric modeling technology has made significant advances in the representation, display and modification of shapes, there have only been incremental advances in geometric reasoning. For example, although today's CAD systems can confidently identify isolated cylindrical holes, they struggle with more ambiguous tasks such as the identification of partial symmetries or similarities in arbitrary geometries. Even well defined problems such as 2D shape nesting or 3D packing generally resist elegant solution and rely instead on brute force explorations of a subset of the many possible solutions. Identifying economic ways to solving such problems would result in significant productivity gains across a wide range of industrial applications. The authors hypothesize that Internet Crowdsourcing might provide a pragmatic way of removing many geometric reasoning bottlenecks.This paper reports the results of experiments conducted with Amazon's mTurk site and designed to determine the feasibility of using Internet Crowdsourcing to carry out geometric reasoning tasks as well as establish some benchmark data for the quality, speed and costs of using this approach.After describing the general architecture and terminology of the mTurk Crowdsourcing system, the paper details the implementation and results of the following three investigations; 1) the identification of "Canonical" viewpoints for individual shapes, 2) the quantification of "similarity" relationships with-in collections of 3D models and 3) the efficient packing of 2D Strips into rectangular areas. The paper concludes with a discussion of the possibilities and limitations of the approach

Supervised and non-supervised AE data classification of nanomodified CFRP during DCB tests

Aim of the paper is to use acoustic emissions to study the effect of electrospun nylon 6,6 Nanofibrous mat on carbon-epoxy composites during Double Cantilever beam (DCB) tests. In order to recognize the effect of the nanofibres and to detect different damage mechanisms, k-means clustering of acoustic emission signals applied to rise time, count, energy, duration and amplitude of the events is used. Supervised neural network (NN) is then applied to verify clustered signals. Results showed that clustered acoustic emission signals are a reliable tool to detect different damage mechanisms; neural network showed the method has a 99% of accuracy

A new approach to modularity in product development – utilising assembly sequence knowledge

This article describes an approach dedicated to routine design of “highly productive” modular product ranges incorporating principles of functional analysis, Design For Assembly (DFA), and techniques from modelling and simulation of multi-physics applied to parametric CAD models. The paper focuses on techniques of assembly sequence generation based on modules identified, and module parameters identification and rule generation. This methodology entitled Functional And Robust Design (FARD) aims to take into account the modularity of product ranges while considering DFA constraints. It takes into consideration of the functions of a product and its assembly constraints in the early stages of the design process simultaneously. An experimental case study on a pneumatic scraper is presented to illustrate the effectiveness of the methodology. This paper focuses on the functional design and the DFA part of the proposed methodology

Geometric Reasoning With a Virtual Workforce (Crowdsourcing for CAD/CAM)

This paper reports the initial results of employing a commercial Crowdsourcing (aka Micro-outsourcing) service to provide geometric analysis of complex 3D models of mechanical components. Although Crowdsourcing sites (which distribute browser based tasks to potentially large numbers of anonymous workers on the Internet) are well established for image analysis and text manipulation there is little academic work on the effectiveness or limitations of the approach. The work reported here describes the initial results of using Crowdsourcing to determine the 'best' canonical, or characteristic, views of complex 3D models of engineering components. The results suggest that the approach is a cheap, fast and effective method of solving what is a computationally difficult problem

EGAM Induced by Energetic-electrons and Nonlinear Interactions among EGAM, BAEs and Tearing Modes in a Toroidal Plasma

In this letter, it is reported that the first experimental results are associated with the GAM induced by energetic electrons (eEGAM) in HL-2A Ohmic plasma. The energetic-electrons are generated by parallel electric fields during magnetic reconnection associated with tearing mode (TM). The eEGAM localizes in the core plasma, i.e. in the vicinity of q=2 surface, and is very different from one excited by the drift-wave turbulence in the edge plasma. The analysis indicated that the eEGAM is provided with the magnetic components, whose intensities depend on the poloidal angles, and its mode numbers are jm/nj=2/0. Further, there exist intense nonlinear interactions among eEGAM, BAEs and strong tearing modes (TMs). These new findings shed light on the underlying physics mechanism for the excitation of the low frequency (LF) Alfv\'enic and acoustic uctuations.Comment: 5 pages,4 figure