39 resultados para flexible manufacturing systems

em Deakin Research Online - Australia


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Computer modelling and simulation is an indispensable tool of the information age, used extensively in design, analysis, operations, decision-making, optimization, and education and training. Manufacturing, production and design relies upon simulation to develop efficient production systems and factories that produce quality products. Computer simulation allows scientists and engineers to understand and predict three-dimensional and time-dependent phenomena in science and engineering discipline. This talk will focus on challenges associated with modelling and simulation in the manufacturing sector and through a number of case studies highlights the benefits gained through the use of such technologies.

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The implementation of Kanban-based production control systems may be difficult in make-to-order environments such as job shops. The flexible manufacturing approach constitutes a promising solution to adapt the Kanban method to such environments. This paper presents an information flow modelling approach for specifying the operational planning and control functions of the Kanban-controlled shopfloor control system (KSCS) in a flexible manufacturing environment. By decomposing the KSCS control functionalities, we have created the system information flow model through the data flow diagrams of Structured Systems Analysis Methodology. The data flow diagrams serve effective system specifications for communicating the system operations to participants of different disciplines as well as the system model for the design and development of KSCS.

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Investigates the creation of a method for the connection and communication of commercial off the shelf discrete-event simulation packages for simulation models of manufacturing systems. Through this research a method to connect different commercial off the shelf discrete-event simulation packages was successfully developed facilitating parallel development of models and the creation of extremely large models.

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Factories of the Future will be distinguished by intelligent machines, automation, human factors integration and knowledge management. Modelling and simulation is recognised as a key enabling technology essential to economic, social and environmental sustainability of future manufacturing systems. This talk will explore the history, recent achievements and directions in modelling and simulation for 21st century factories and supply chains. A systems science approach is employed, from stakeholder engagement through participative modelling to self-tuning and self-assembling simulations. Our contributions lower the cost of the application of modelling and simulation to manufacturing processes, enabling real time planning, dynamic risk analysis, dashboards and 3D visualisation. This realisation of the virtual factory integrates human factors and decisions into the core technology platform. The implications to future manufacturing enterprises are explored through a series of case studies from aerospace, mining and small and medium manufacturing enterprises.

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INTRODUCTION. Additive manufacturing (AM) for various industries has been trailed, prototyped and used in limited production runs (Gibson, 2015). But considering additive manufacturing with metallic materials has been around for over 15 years the penetration into an industry such as cycling that values customisation and progressive design techniques has been quite limited. This case study looks at the potential of and why additive manufacturing has not progressed from concept development and prototyping into production and mainstream. Selective Laser Melting (SLM) additive manufacturing systems mainly use Stainless Steel 316 (SS316) and Titanium 6Al.4V (Ti64) as a baseline material; both these materials are extremely common in the custom and high volume bike industries. For the purposes of this article we will focus on smaller custom bike manufacturers who are typically more agile and open to high levels of customisation in their products. The study finds that whilst a high number of companies will experiment and prototype with additive manufacturing there is little evidence that the design and development process translates to ongoing production for sale to the consumer, this could be due to knowledge of design and fabrication techniques.

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The Operations Research (OR) community have defined many deterministic manufacturing control problems mainly focused on scheduling. Well-defined benchmark problems provide a mechanism for communication of the effectiveness of different optimization algorithms. Manufacturing problems within industry are stochastic and complex. Common features of these problems include: variable demand, machine part specific breakdown patterns, part machine specific process durations, continuous production, Finished Goods Inventory (FGI) buffers, bottleneck machines and limited production capacity. Discrete Event Simulation (DES) is a commonly used tool for studying manufacturing systems of realistic complexity. There are few reports of detail-rich benchmark problems for use within the simulation optimization community that are as complex as those faced by production managers. This work details an algorithm that can be used to create single and multistage production control problems. The reported software implementation of the algorithm generates text files in eXtensible Markup Language (XML) format that are easily edited and understood as well as being cross-platform compatible. The distribution and acceptance of benchmark problems generated with the algorithm would enable researchers working on simulation and optimization of manufacturing problems to effectively communicate results to benefit the field in general.

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Finite element (FE) modelling techniques have become a popular tool for exploring welding and clamping sequence dependence in sheet metal assemblies. In the current paper, the dimensional variability associated with different assembly clamping sequences is investigated with a FE contact modelling approach implemented in the commercial code Abaqus. A simplified channel section assembly consisting of a top hat and bottom plate is the case study investigated. Expected variation modes of bow and twist were used to simulate key variability sources in the main structural component under investigation; the top hat of the channel section. It was found that final assembly variability can change considerably depending on clamp sequence selection. It was also found that different clamp sequences can control particular modes of variation better than others, and that there is not one particular clamping sequence that is the best for containing all variation modes. An adaptable assembly process is therefore suggested, where given the shape of input components the best available clamping sequence is selected. Comparison of the performance of the proposed adaptable clamping sequence to traditional fixed clamping sequences shows improvements for the dimensional control of variability in non-rigid components. While introducing such a method in production would require inspection of each component being assembled and investigation of the alternative clamping sequences, given access to fast and detailed dimensional inspection technology such as optical coordinate measuring machines (OCMM's), the approach shows promise for future application.

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Traditional optimisation methods are incapable of capturing the complexity of today's dynamic manufacturing systems. A new methodology, integrating simulation models and intelligent learning agents, was successfully applied to identify solutions to a fundamental scheduling problem. The robustness of this approach was then demonstrated through a series of real-world industrial applications.

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Nurses are the largest group of healthcare professionals in hospitals providing 24-hour care to patients. Hence, nurses are pivotal in coordinating and communicating patient care information in the complex network of healthcare professionals, services and other care processes. Yet, despite nurses' central role in health care delivery, intelligent systems have historically rarely been designed around nurses' operational needs. This could explain the poor integration of technologies into nursing work processes and consequent rejection by nursing professionals. The complex nature of acute care delivery in hospitals and the frequently interrupted patterns of nursing work suggest that nurses require flexible intelligent systems that can support and adapt to their variable workflow patterns. This study is designed to explore nurses' initial reactions to a new intelligent operational planning and support tool (IOPST) for acute healthcare. The following reports on the first stage of a longitudinal project to use an innovative approach involving nurses in the development of the IOPST; from conceptualization to implementation.

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Virtual reality systems are becoming a must for product and process design, training practices and ergonomic analysis in many manufacturing industries. The automotive sector is considered to be the leader in applying virtual reality (VR) solutions for real-world, non-trivial, problems. Although, a number of commercial 3D engineering tools for digital mockups exist, most of them lack intuitive direct manipulation of the digital mockups. The majority of these 3D engineering tools are constrained to the interaction mainly with rigid objects which is just half the story. To bridge this gap, we have developed a haptics interface for modelling and simulation of flexible objects. The graphical and haptic user interface developed allows the creation of multiple one dimensional (1D) flexible objects, such as hoses, cables and harnesses. The user is required to provide the mechanical properties of the material such as Young's modulus, Poisson's ratio, material density, damping factors, as well as dimensional properties such as length, and inner and outer diameters of the flexible object. Flexilution solver is employed to estimate and simulate the dynamic behaviour of flexible objects in response to external user interaction, whereas Nvidia's generic physics engine is used to simulate the behaviour of rigid objects. A generic communication interface is developed to accommodate a variety of devices without the reconfiguration of the simulation platform.

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This article describes the manufacturing and characterisation of plano-convex miniaturised lenses using a CO2 laser engraving process in PMMA substrates. The technique allows for lenses to be fabricated rapidly and in a reproducible manner at depths of over 200 µm and for lens diameters of more than 3 mm. Experimental characterisation of the lens focal lengths shows good correlation with theory. The plano-convex lenses have been successfully embedded into capillary microfluidic systems alongside planar microlenses, allowing for a significant reduction of ancillary optics without a loss of detection sensitivity when performing fluorescence measurements. Such technology provides a significant step forward towards the portability of fluorescence- or luminescence-based systems for biological/chemical analysis.

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Laser micro-machining offers a versatile tool for the rapid manufacturing of polymeric microfluidics systems, with a typical turn-around-time in the order of minutes. However, the chaotic nature of the thermal evaporative ablation process can yield a significant number of defects in the surface of the manufactured microchannels, in the form of residual condensed material. In this work we have investigated the use of solvent evaporation by which to not only laminate bond the laser machined structures but to remove a significant number of the defect formed by the condensation of residual polymer. Results are presented of the surface profiling of the bonded channel structures and demonstrations of the bonding of the microchips to produce autonomous capillary microchannels.

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To provide managers with a critical insight into the management of new technology, this paper uses a case study research strategy to examine the technology management experiences of a leading UK manufacturing organization during its adoption of a vendor-supplied Manufacturing Resource Planning information system.

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In most agent-based systems, different middle agents are employed to increase their flexibility. However, there are still three issues remain unsolved. In centralized architecture with single middle agent, the middle agent itself is a bottleneck and suffers from single point failure; middle agents in distributed architecture lack capability of dynamic organization of agents; The reliability is not strong because of the single point failure and lack of effective architecture. We introduce a platform with ring architectural model to solve all above problems. In the platform, multiple middle agents are dynamically supported for solving the first problem. For solving the second problem, middle agents dynamically manage the registration and cancellation of service provider agents and application teams, each of which includes a set of closely interacting requester agents to complete an independent task. Redundancy middle agent technique is proposed for solving the third problem. All middle agents are of the feature of proliferation and self-cancellation according to the sensory inputs from their environment. For organizing the middle agents effectively, a ring architectural model is proposed. We demonstrate the applicability of the platform by its application and present experimental evidence that the platform is flexible and robust.