534 research outputs found

    Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

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    Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

    Production Scheduling

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    Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

    Enhanced integrated modelling approach to reconfiguring manufacturing enterprises

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    Dynamism and uncertainty are real challenges for present day manufacturing enterprises (MEs). Reasons include: an increasing demand for customisation, reduced time to market, shortened product life cycles and globalisation. MEs can reduce competitive pressure by becoming reconfigurable and change-capable. However, modern manufacturing philosophies, including agile and lean, must complement the application of reconfigurable manufacturing paradigms. Choosing and applying the best philosophies and techniques is very difficult as most MEs deploy complex and unique configurations of processes and resource systems, and seek economies of scope and scale in respect of changing and distinctive product flows. It follows that systematic methods of achieving model driven reconfiguration and interoperation of component based manufacturing systems are required to design, engineer and change future MEs. This thesis, titled Enhanced Integrated Modelling Approach to Reconfiguring Manufacturing Enterprises , introduces the development and prototyping a model-driven environment for the design, engineering, optimisation and control of the reconfiguration of MEs with an embedded capability to handle various types of change. The thesis describes a novel systematic approach, namely enhanced integrated modelling approach (EIMA), in which coherent sets of integrated models are created that facilitates the engineering of MEs especially their production planning and control (PPC) systems. The developed environment supports the engineering of common types of strategic, tactical and operational processes found in many MEs. The EIMA is centred on the ISO standardised CIMOSA process modelling approach. Early study led to the development of simulation models during which various CIMOSA shortcomings were observed, especially in its support for aspects of ME dynamism. A need was raised to structure and create semantically enriched models hence forming an enhanced integrated modelling environment. The thesis also presents three industrial case examples: (1) Ford Motor Company; (2) Bradgate Furniture Manufacturing Company; and (3) ACM Bearings Company. In order to understand the system prior to realisation of any PPC strategy, multiple process segments of any target organisation need to be modelled. Coherent multi-perspective case study models are presented that have facilitated process reengineering and associated resource system configuration. Such models have a capability to enable PPC decision making processes in support of the reconfiguration of MEs. During these case studies, capabilities of a number of software tools were exploited such as Arena®, Simul8®, Plant Simulation®, MS Visio®, and MS Excel®. Case study results demonstrated effectiveness of the concepts related to the EIMA. The research has resulted in new contributions to knowledge in terms of new understandings, concepts and methods in following ways: (1) a structured model driven integrated approach to the design, optimisation and control of future reconfiguration of MEs. The EIMA is an enriched and generic process modelling approach with capability to represent both static and dynamic aspects of an ME; and (2) example application cases showing benefits in terms of reduction in lead time, cost and resource load and in terms of improved responsiveness of processes and resource systems with a special focus on PPC; (3) identification and industrial application of a new key performance indicator (KPI) known as P3C the measuring and monitoring of which can aid in enhancing reconfigurability and responsiveness of MEs; and (4) an enriched modelling concept framework (E-MUNE) to capture requirements of static and dynamic aspects of MEs where the conceptual framework has the capability to be extended and modified according to the requirements. The thesis outlines key areas outlining a need for future research into integrated modelling approaches, interoperation and updating mechanisms of partial models in support of the reconfiguration of MEs

    The co-incident flow of work pieces and cutting tools in a restricted category of flexible machining cells

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    The work reported in this thesis describes research carried out into the detailed design and operation of Flexible Machining Cells (FMC) incorporating automated work and tool flow, dual flow. Three modes of cell management are considered for dual flow cells, where the author examines both their operational and economic performance. A framework is defined for investigating these dual flow cells, and a structured approach providing a novel and detailed modelling capability is described. The question of how this approach compares to single flow modelling and the additional or alternative requirements for dual flow modelling is examined via the following key areas; the specification of material handling requirements, tool transportation and issue and finally, the control required to examine the interaction between the two flows operating concurrently. The framework is tested for its industrial applicability via an industrial case study. A major aim of this study is to examine the view that a hybrid cell management strategy, competitive management, could outperform the other strategies examined. The aim of this methodology is to provide a solution for the control of FMCs. Emphasis is placed on the ease of control and how the loading and control rules selection can maximise economic enhancement of a cells performance

    Model-driven performance analysis of rule-based domain specific visual models

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    Context: Domain-Specific Visual Languages (DSVLs) play a crucial role in Model-Driven Engineering (MDE). Most DSVLs already allow the specification of the structure and behavior of systems. However, there is also an increasing need to model, simulate and reason about their non-functional properties. In particular, QoS usage and management constraints (performance, reliability, etc.) are essential characteristics of any non-trivial system. Objective: Very few DSVLs currently offer support for modeling these kinds of properties. And those which do, tend to require skilled knowledge of specialized notations, which clashes with the intuitive nature of DSVLs. In this paper we present an alternative approach to specify QoS properties in a high-level and platform-independent manner. Method: We propose the use of special objects (observers) that can be added to the graphical specification of a system for describing and monitoring some of its non-functional properties. Results: Observers allow extending the global state of the system with the variables that the designer wants to analyze, being able to capture the performance properties of interest. A performance evaluation tool has also been developed as a proof of concept for the proposal. Conclusion: The results show how non-functional properties can be specified in DSVLs using observers, and how the performance of systems specified in this way can be evaluated in a flexible and effective way.Ministerio de Ciencia e Innovación TIN2008-031087Ministerio de Ciencia e Innovación TIN2011-2379

    Developing manufacturing control software: A survey and critique

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    The complexity and diversity of manufacturing software and the need to adapt this software to the frequent changes in the production requirements necessitate the use of a systematic approach to developing this software. The software life-cycle model (Royce, 1970) that consists of specifying the requirements of a software system, designing, implementing, testing, and evolving this software can be followed when developing large portions of manufacturing software. However, the presence of hardware devices in these systems and the high costs of acquiring and operating hardware devices further complicate the manufacturing software development process and require that the functionality of this software be extended to incorporate simulation and prototyping.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45542/1/10696_2005_Article_BF01328739.pd

    On the Use of Queueing Petri Nets for Modeling and Performance Analysis of Distributed Systems

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    Predictive performance models are used increasingly throughout the phases of the software engineering lifecycle of distributed systems. However, as systems grow in size and complex-ity, building models that accurately capture the different aspects of their behavior becomes a more and more challenging task. The challenge stems from the limited model expressivenes

    An agile and adaptive holonic architecture for manufacturing control

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    Tese de doutoramento. Engenharia Electrotécnica e de Computadores. 2004. Faculdade de Engenharia. Universidade do Port

    Resource-aware business process management : analysis and support

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