117 research outputs found
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A multi-agent architecture for plug and produce on an industrial assembly platform
YesModern manufacturing companies face increased pressures to adapt to shorter product life cycles and the need to reconfigure more frequently their production systems to offer new product variants. This paper proposes a new multi-agent architecture utilising âplug and produceâ principles for configuration and reconfiguration of production systems with minimum human intervention. A new decision-making approach for system reconfiguration based on tasks re-allocation is presented using goal driven methods. The application of the proposed architecture is described with a number of architectural views and its deployment is illustrated using a validation scenario implemented on an industrial assembly platform. The proposed methodology provides an innovative application of a multi-agent control environment and architecture with the objective of significantly reducing the time for deployment and ramp-up of small footprint assembly systems.The reported research has been part of the EU FP7 research project âPRIME
Function-behaviour-structure model for modular assembly equipment
Reconfigurable modular manufacturing systems provide a solution to manage current challenges of dynamic, customer driven markets. Powerful methods are needed for rapid configuration of system. This research focuses on the ontological definition of modular assembly device domain knowledge which builds the foundation for such methods. In this word formal representations will be defined based on linked models of functions, behaviour and structure of the equipment modules. The method will be discussed using an illustrative example
High precision self-alignment using liquid surface tension for additively manufactured micro components
Self-assembly of components using liquid surface tension is an attractive alternative to traditional robotic pick-and-place as it offers high assembly accuracy for coarse initial part placement. One of the key requirements of this method is the containment of the liquid within a designated binding site. This paper looks to expand the applications of self-assembly and investigates the use of topographical structures applied to 3D printed micro components for self-assembly using liquid surface tension. An analysis of the effect of edge geometry on liquid contact angle was conducted. A range of binding sites were produced with varying edge geometries, 45-135°, and for a variety of site shapes and sizes, 0.4 - 1 mm in diameter, and 0.5 x 0.5 â 1 x 1 mm square. Liquid water droplets were applied to the structures and contact angles measured. Significant increases in contact angle were observed, up to 158°, compared to 70° for droplets on planar surfaces, demonstrating the ability of these binding sites to successfully pin the triple contact line at the boundary. Three challenging self-assembly cases were examined, 1) linear initial component misplacement >0.5 mm, 2) angular misplacement of components, 3)
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misplacement of droplet. Across all three assembly cases the lowest misalignments in final component position, as well as highest repeatability, were observed for structures with actual edge geometries <90° (excluding 45° nominal), where the mean magnitude of misalignment was found to be 31 Όm with 14 Όm standard deviation
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Prioritising low cost digital solutions required by manufacturing SMEs: A shoestring approach
This paper establishes a reference set of those low cost digital solutions needed by small and medium sized manufacturers â SMEs â and proposes a method for determining development priorities using input from reference groups of SMEs. The paper describes the approach taken to identifying and classifying common digital solutions used in manufacturing and the results from a series of workshops in which company representatives prioritise different solution types to help guide developments
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Modular reconfiguration of flexible production systems using machine learning and performance estimates
YesThis paper presents an agent-based framework for reconfiguring modular assembly
systems using machine learning and system performance estimates based on previous
reconfigurations. During a reconfiguration, system integrators and engineers make changes to
the machine to meet new production requirements by increasing capacity or manufacturing
new product variants. The framework provides a method for automatically evaluating these
changes in terms of impact on the performance of the production system, and building a
knowledge base. Such knowledge is used to support future reconfigurations by recommending
changes that are likely to improve the performance based on previous reconfigurations. The
agent architecture of the framework has two levels, one for individual assembly stations and
one for the entire production line. Knowledge bases of changes are built and utilised at both
levels using machine learning and performance estimates. A prototype implementation of the
proposed framework has been evaluated on an assembly production system in an industrial
scenario. Preliminary results show that framework helps to reduce the time and resources
required to complete a system reconfiguration and reach the desired production objectives.This work was supported by the SURE Research Projects Fund of the University of Bradford and the European Commission [grant agreement n. 314762]
Virtual ergonomics and time optimization of a railway coach assembly line
The recent drive towards timely multiple product realizations has caused most Manufacturing Enterprises (MEs) to develop more flexible assembly lines supported by better manufacturing design and planning. The aim of this work is to develop a methodology which will support feasibility analyses of assembly tasks, in order to simulate either a manufacturing process or a single work-cell in which digital human models act. The methodology has been applied in a case study relating to a railway industry. Simulations were applied to help standardize the methodology and suggest new solutions for realizing ergonomic and efficient assembly processes in the railway industry
The integrated use of enterprise and system dynamics modelling techniques in manufacturing enterprises
Enterprise modelling (EM) techniques support manufacturing process (re) engineering by capturing âas-isâ processes and based on perceived outputs, support the design of âto-beâ process models capable of meeting manufacturing systems requirements. On the other hand, system dynamics (SD) modelling tools are used extensively for policy analysis and modelling aspects of dynamics which impact on businesses. In this paper, the use of EM and SD modelling techniques has been integrated to facilitate qualitative and quantitative reasoning about the structures and behaviours of processes and resource systems used by a Manufacturing Enterprise (ME) during the production of composite bearings
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Digital manufacturing on a shoestring: Low cost digital solutions for SMEs
One of the key findings in a number of recent studies has been that small and medium sized manufacturers (SMEs) have been slow in adopting digital solutions within their organisations. Cost is understood to be one of the key barriers to adoption. Digital Manufacturing on a Shoestring is an approach to increasing the digital capabilities of SMEs via a series of low cost solutions. The programme proposes using off-the-shelf, (possibly non-industrial) components and software to address a companyâs (digital) solution needs, adding capabilities one step at a time with minimal a priori infrastructure required. This paper will introduce the Digital Manufacturing on a Shoestring programme as a whole and demonstrate the way in which it addresses the need for low cost digital solutions for SME Manufacturers. It will discuss challenges associated with integrating low cost technologies into industrial solutions and the style of IT architectures best suited for integrating such solutions into industrial environments
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