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Automation Science and Engineering, IEEE Transactions on

Issue 1 • Date Jan. 2013

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  • Table of Contents

    Publication Year: 2013 , Page(s): C1
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  • IEEE Transactions on Automation Science and Engineering publication information

    Publication Year: 2013 , Page(s): C2
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  • Editorial: Automation in green manufacturing

    Publication Year: 2013 , Page(s): 1 - 4
    Cited by:  Papers (2)
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  • Virtual Battery: A Battery Simulation Framework for Electric Vehicles

    Publication Year: 2013 , Page(s): 5 - 15
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1941 KB) |  | HTML iconHTML  

    The battery is one of the most important components in electric vehicles. In this paper, a virtual battery model, which provides a framework of battery simulation for electric vehicles, is introduced. Using such a framework, we can model and simulate the performance of a battery during its usage, such as battery charge, discharge, and idle status, the impacts of internal and external temperature, the manufacturing quality on joints, the cell capacity and balance management, etc. Such a framework can provide a quantitative tool for design and manufacturing engineers to predict the battery performance, investigate the impacts of manufacturing process, and obtain feedback for improvement in battery design, control, and manufacturing processes. Note to Practitioners-Automotive battery manufacturing has become more and more important due to the need of alternative energy source to gasoline powered engines. Although substantial amount of attention has been paid to study both individual battery cells and the battery pack as a whole, a battery model which includes interactions of all its components (cells, joints, external inputs, etc.) is not available, and the impact of manufacturing quality on battery performance has not been investigated. In this paper, a virtual battery simulation framework is developed to evaluate battery performance under different circumstances, involving the issues of cell capacity, temperature, driving profile, the joint (manufacturing) quality, etc. Such a framework can help battery design and manufacturing engineers to evaluate battery performance, investigate the impacts of manufacturing practices, and provide feedback for improvement. View full abstract»

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  • Designing a Sustainable and Distributed Generation System for Semiconductor Wafer Fabs

    Publication Year: 2013 , Page(s): 16 - 26
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1616 KB) |  | HTML iconHTML  

    Driven by wind and solar photovoltaics technology, the power industry is shifting towards a distributed generation (DG) paradigm. A key challenge in deploying a renewable DG system is the power volatility. This study proposes a visionary energy concept and further presents a mathematical model that could help the large industry consumers adopt this new energy technology. The study seeks to design a grid-connected DG system that is capable of providing the necessary electricity for wafer fabs. Simulation-based optimization algorithm was applied to determine the equipment type and capacity aiming to minimize the DG lifecycle cost. The proposed method was demonstrated on fab facilitates located in three different regions in the US. View full abstract»

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  • Energy-Efficient Production Systems Through Schedule-Based Operations

    Publication Year: 2013 , Page(s): 27 - 37
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2316 KB) |  | HTML iconHTML  

    Control of production operations is considered as one of the most economical methods to improve energy efficiency in manufacturing systems. This paper investigates energy consumption reduction in production systems through effective scheduling of machine startup and shutdown. Specifically, we consider serial production lines with finite buffers and machines having Bernoulli reliability model. This machine reliability model is applicable in production situations, where the downtime is relatively short and comparable to machine cycle time (e.g., automotive paint shops and general assembly). In this paper, using transient analysis of the systems at hand, an analytical performance evaluation technique is developed for Bernoulli serial lines with time-dependent machine efficiencies. In addition, tradeoff between productivity and energy-efficiency in production systems is discussed and the energy-efficient production problem is formulated as a constrained optimization problem. The effects and practical implications of operations schedule are demonstrated using a numerical study on automotive paint shop operations. Note to Practitioners - This paper develops an effective analytical tool to evaluate the performance of production systems with time-varying parameters of machine reliability. Using this tool, production engineers and managers can predict the performance of the production systems in real-time with high accuracy. In addition, based on this tool, production operators can determine the machine startup and shutdown schedule based on the current status of the line and production requirement. Numerical experiments show that significant energy savings can be obtained by applying effective machine operations schedule. View full abstract»

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  • Opportunity Estimation for Real-Time Energy Control of Sustainable Manufacturing Systems

    Publication Year: 2013 , Page(s): 38 - 44
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (721 KB) |  | HTML iconHTML  

    Due to the complexity of modern manufacturing systems and the lack of optimal management of energy consumption, the energy efficiency of manufacturing systems in real industrial environment is much lower than designed level, which significantly increases operation cost, impedes company competitiveness in the global market, leads to high carbon dioxide emission, and results in destroyed environment and ecology. Compared with existing research efforts on energy management of single machine system in the literature, few works have been performed to study the opportunity for energy management of typical manufacturing systems with multiple machines and buffers. From the point-of-view of sustainability, considering stochastic factor and buffer utilization, this paper investigates the opportunity estimation for real-time energy control of typical multi-machine manufacturing systems without sacrificing system throughput. A numerical case study based on an automotive assembly line is used to illustrate the effectiveness and efficiency of the proposed method. View full abstract»

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  • Energy Reduction in a Pallet-Constrained Flow Shop Through On–Off Control of Idle Machines

    Publication Year: 2013 , Page(s): 45 - 56
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2129 KB) |  | HTML iconHTML  

    For flexible manufacturing systems, there are normally some durations in which a number of machines are idle and do not process any parts. Devising a control policy to turn off the idle machines and reduce their level of energy consumption is a significant contribution towards the green manufacturing paradigm. This paper addresses the design of such a control strategy for a closed-loop flow shop plant based on a one-loop pallet system. The main goal is to coordinate running of the machines and motion of pallets to gain the minimal energy consumption in idle machines, as well as to obtain the desired throughput for the plant. To fulfill this goal, first mathematical conditions, which economically characterize the on-off control for machines, are presented. Constrained to these conditions and the mathematical models describing the pallet system, a mixed integer nonlinear minimization problem with the energy monitor as the objective function is then developed. Provided that the problem computation time can be managed, the optimal control for the operation of the plant and the minimal energy consumption in the idle machines are computed. To deal with the time complexity, a linearized form of the model and a heuristic approach are introduced. These methods are applied to some examples of industrial size, and their impacts in practice are discussed and verified by using a discrete event simulation tool. View full abstract»

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  • High-Level Scheduling of Energy Optimal Trajectories

    Publication Year: 2013 , Page(s): 57 - 64
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (571 KB) |  | HTML iconHTML  

    The reduction of energy consumption is today addressed with great effort in manufacturing industry. In this paper, we improve upon a previously presented method for robotic system scheduling. By applying dynamic programming to existing trajectories, we generate new energy optimal trajectories that follow the same path but in a different execution time frame. With this new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. The minimum energy trajectories can then be used to derive a globally energy optimal schedule. A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time. View full abstract»

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  • A Network Flow Model for the Performance Evaluation and Design of Material Separation Systems For Recycling

    Publication Year: 2013 , Page(s): 65 - 75
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1440 KB) |  | HTML iconHTML  

    Interest in recycling has surged due to increasing material costs, environmental concerns over material production and disposal, and laws designed to improve material recycling rates. In response, recycling systems are becoming more complex as increasing material recovery is required from products with complicated material mixtures such as waste electrical and electronic equipment (WEEE) and ELVs. To increase performance and process complex material mixtures, separation systems are typically organized as highly integrated multistage systems. However, the problem of estimating the performance and designing multistage separation systems has rarely been tackled from a systems engineering perspective, resulting in poor integration and suboptimal configuration of industrial multistage separation systems. This paper presents a new approach to modeling, analyzing, and designing multistage separation systems to meet specified performance goals in terms of recovery/grade. Results can be used to generate maps of optimal system configurations for different requirements. The industrial benefits are illustrated by a real case study. View full abstract»

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  • Assembly Strategies for Remanufacturing Systems With Variable Quality Returns

    Publication Year: 2013 , Page(s): 76 - 85
    Cited by:  Papers (1)
    Multimedia
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    This paper studies optimal policy for modular product reassembly within a remanufacturing setting where a firm receives product returns with variable quality and reassembles products of multiple classes to customer orders. High-quality modules are allowed to substitute for low-quality modules during reassembly to provide the remanufacturing system with flexibility such that shortage in lower quality modules can be smoothed out by higher quality module inventories. We formulate the problem as a Markov decision process and characterize the structure of the optimal control policy. In particular, we show that the optimal reassembly and substitution follow a state-dependent threshold-based control policy. We also establish the structural properties of the thresholds. Using numerical experimentation, we study how system performance is influenced by key cost parameters including unit holding cost, unit assembly cost and shortage penalty cost. Finally, we compare the optimal policy with an exhaustive reassembly policy and show that there is great benefit in module substitution and threshold-based assembly control. View full abstract»

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  • A Modeling Approach to Analyze Variability of Remanufacturing Process Routing

    Publication Year: 2013 , Page(s): 86 - 98
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2148 KB) |  | HTML iconHTML  

    Remanufacturing is a practice of growing importance due to increasing environmental awareness and regulations. However, little research focuses on stochastic remanufacturing process routings (RPR). This paper presents an analytical method, where four Graphical Evaluation and Review Technique (GERT)-based RPR models are proposed to mathematically represent and analyze the variability of remanufacturing task sequences. In particular, with the method, the probability of individual processes being taken in a remanufacturing system and the time associated with them can be efficiently determined. The proposed method is demonstrated through the remanufacturing of used lathe spindles and telephones, and verified by Arena simulation. Numerical experiments that investigate the relationships between RPR dynamics and other system parameters (such as inventory control for due-time performance and time buffer size for bottleneck control) are included. View full abstract»

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  • Carbon Footprint and the Management of Supply Chains: Insights From Simple Models

    Publication Year: 2013 , Page(s): 99 - 116
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1803 KB) |  | HTML iconHTML  

    Using relatively simple and widely used models, we illustrate how carbon emission concerns could be integrated into operational decision-making with regard to procurement, production, and inventory management. We show how, by associating carbon emission parameters with various decision variables, traditional models can be modified to support decision-making that accounts for both cost and carbon footprint. We examine how the values of these parameters as well as the parameters of regulatory emission control policies affect cost and emissions. We use the models to study the extent to which carbon reduction requirements can be addressed by operational adjustments, as an alternative (or a supplement) to costly investments in carbon-reducing technologies. We also use the models to investigate the impact of collaboration among firms within the same supply chain on their costs and carbon emissions and study the incentives firms might have in seeking such cooperation. We provide a series of insights that highlight the impact of operational decisions on carbon emissions and the importance of operational models in evaluating the impact of different regulatory policies and in assessing the benefits of investments in more carbon efficient technologies. Note to Practitioners-Firms worldwide, responding to the threat of government legislation or to concerns raised by their own consumers or shareholders, are undertaking initiatives to reduce their carbon footprint. It is the conventional thinking that such initiatives will require either capital investments or a switch to more expensive sources of energy or input material. In this paper, we show that firms could effectively reduce their carbon emissions without significantly increasing their costs by making only operational adjustments and by collaborating with other members of their supply chain. We describe optimization models that can be used by firms to support operational decision making and supply chain collaboration, whil- taking into account carbon emissions. We analyze the effect of different emission regulations, including strict emission caps, taxes on emissions, cap-and-offset, and cap-and-trade, on supply chain management decisions. In particular, we show that the presence of emission regulation can significantly increase the value of supply chain collaboration. View full abstract»

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  • A Simulation-Based Tool for Energy Efficient Building Design for a Class of Manufacturing Plants

    Publication Year: 2013 , Page(s): 117 - 123
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (748 KB) |  | HTML iconHTML  

    This paper explores energy efficient building design for manufacturing plants. Many efforts have been directed into the field of building design optimization concerning building energy performance, but most of the studies focus on residential buildings or public buildings. Very limited research results studying plants buildings have been reported. However, plants buildings have certain unique features that make the design problem more challenging. Furthermore, the approaches presented in the current publications could not guarantee the performance of their designs if the computation capacity is limited. This paper attempts to address these two issues. First, an EnergyPlus-integrated overall energy consumption estimation framework is developed for a class of manufacturing plants, where the environmental conditions would not affect the energy consumption of the production processes. Based on that, the building design problem for this type of manufacturing plants is formulated as a stochastic programming problem concerning uncertainties arising from the future weather conditions and energy prices, where seasonal production scheduling optimizing is incorporated when estimating the performance of building designs. Second, Ordinal Optimization (OO) method is introduced to solve the problem so as to quantitatively guarantee a high probability of finding satisfactory designs while reducing the computation burden. A numerical example is provided, showing our solution method performs effectively in finding a satisfactory design. View full abstract»

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  • Fault Diagnosis Using an Enhanced Relevance Vector Machine (RVM) for Partially Diagnosable Multistation Assembly Processes

    Publication Year: 2013 , Page(s): 124 - 136
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (938 KB) |  | HTML iconHTML  

    Dimensional integrity has a significant impact on the quality of the final products in multistation assembly processes. A large body of research work in fault diagnosis has been proposed to identify the root causes of the large dimensional variations on products. These methods are based on a linear relationship between the dimensional measurements of the products and the possible process errors, and assume that the number of measurements is greater than that of process errors. However, in practice, the number of measurements is often less than that of process errors due to economical considerations. This brings a substantial challenge to the fault diagnosis in multistation assembly processes since the problem becomes solving an underdetermined system. In order to tackle this challenge, a fault diagnosis methodology is proposed by integrating the state space model with the enhanced relevance vector machine (RVM) to identify the process faults through the sparse estimate of the variance change of the process errors. The results of case studies demonstrate that the proposed methodology can identify process faults successfully. View full abstract»

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  • Correct-by-Construction and Optimal Synthesis of Beacon-Enabled ZigBee Network

    Publication Year: 2013 , Page(s): 137 - 144
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (740 KB) |  | HTML iconHTML  

    In this paper we develop a formal approach for the synthesis of a cost-effective and correct-by-construction communication network (focusing on ZigBee wireless networks) subject to a set of end-to-end communication constraints of latency, bandwidth and error-rate, together with the constraints of the network protocols and the desired geographical placement of the network. We also develop a software platform to implement the proposed approach for network synthesis, and apply it to a practical wireless network synthesis for centralized as well as distributed estimation application. View full abstract»

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  • Scheduling Cluster Tools With Ready Time Constraints for Consecutive Small Lots

    Publication Year: 2013 , Page(s): 145 - 159
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3306 KB) |  | HTML iconHTML  

    In the semiconductor manufacturing industry, the lot size currently tends to be extremely small, even being only 5-8 wafers, whereas conventional lots have 25 identical wafers. The smaller lot size is made because customers demand extremely small lots, and the number of chips in a large 300 mm wafer has increased. Cyclic scheduling is not applicable for such small lot production because the number of identical work cycles accounts for a small proportion of scheduling as compared to the lengths of the starting and closing transient periods. We therefore examine a new noncyclic scheduling problem of cluster tools for small lot production that considers ready time constraints on the chambers and the robot. The ready times are the epochs when the resources are freed from processing the preceding lot. To solve the scheduling problem, we develop a Petri net model which is a graphical and mathematical method for discrete event dynamic systems. Based on the Petri net model, we also develop a mixed integer programming (MIP) model and a branch and bound (B&B) algorithm for determining an optimal schedule. The B&B algorithm solves lots with up to 25 wafers and eight wafers within 500 s for a single-armed cluster tool and a dual-armed cluster tool, respectively, when three process steps are considered. Therefore, we propose an approximation method for the dual-armed cluster tool that schedules only the first few wafers with the B&B algorithm and the succeeding wafers with a well-known cyclic sequence. From experiments, we conclude that the difference between the approximation method and an optimal makespan is less than 1%. The methods we propose can be used for general noncyclic scheduling problems that can be modeled by Petri nets. View full abstract»

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  • Finite Bisimulation of Reactive Untimed Infinite State Systems Modeled as Automata With Variables

    Publication Year: 2013 , Page(s): 160 - 170
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (653 KB) |  | HTML iconHTML  

    Some discrete-event systems such as software are typically infinite state systems, and a commonly used technique for performing formal analysis such as automated verification is based on their finite abstractions. In this paper, we consider a model for reactive untimed infinite state systems called input-output extended finite automaton (I/O-EFA), which is an automaton extended with discrete variables such as inputs, outputs, and data. Using I/O-EFA as a model many value-passing processes can be represented by finite graphs. We study the problem of finding a finite abstraction that is bisimilar to a given I/O-EFA. We present a sufficient condition under which the underlying transition system of an I/O-EFA admits a finite bisimilar quotient. We then identify a class of I/O-EFAs for which a partition satisfying our sufficient condition can be constructed by inspecting the structure of the given I/O-EFA. We also identify a lower bound abstraction (that is coarser than any finite bisimilar abstraction), and present an iterative refinement algorithm whose termination guarantees the existence of a finite bisimilar abstraction. The results are illustrated through examples that model reactive software. View full abstract»

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  • Calibration of Stochastic Computer Models Using Stochastic Approximation Methods

    Publication Year: 2013 , Page(s): 171 - 186
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2614 KB) |  | HTML iconHTML  

    Computer models are widely used to simulate real processes. Within the computer model, there always exist some parameters which are unobservable in the real process but need to be specified in the model. The procedure to adjust these unknown parameters in order to fit the model to observed data and improve predictive capability is known as calibration. Practically, calibration is typically done manually. In this paper, we propose an effective and efficient algorithm based on the stochastic approximation (SA) approach that can be easily automated. We first demonstrate the feasibility of applying stochastic approximation to stochastic computer model calibration and apply it to three stochastic simulation models. We compare our proposed SA approach with another direct calibration search method, the genetic algorithm. The results indicate that our proposed SA approach performs equally as well in terms of accuracy and significantly better in terms of computational search time. We further consider the calibration parameter uncertainty in the subsequent application of the calibrated model and propose an approach to quantify it using asymptotic approximations. View full abstract»

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  • I-Detectability of Discrete-Event Systems

    Publication Year: 2013 , Page(s): 187 - 196
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (678 KB) |  | HTML iconHTML  

    State estimation has always been important in discrete-event systems. There are two types of state estimation problems in discrete-event systems: one is to determine the initial state of the system and the other is to determine the current state of the system. In this paper, we investigate the initial state estimation problem. We formulate initial state estimation problem as I-detectability. A discrete-event system is strongly I-detectable if we can determine the initial state of the system after a finite number of event observations for all trajectories of the system. It is weakly I-detectable if we can determine the initial state of the system for some trajectories of the system. We construct I-observer to analyze strong and weak I-detectability and construct I-detector to check strong I-detectability. For some applications, strong I-detectability is required but not satisfied; hence we investigated how to control a system to achieve strong I-detectability if needed. If there exists a controllable, observable, and strongly I-detectable sublanguage, then we say the system is closed-loop strongly I-detectable. We derive an effective algorithm to check whether a system is closed-loop strongly I-detectable. The algorithm can also calculate a controllable, observable, and strongly I-detectable sublanguage if the system is closed-loop strongly I-detectable. View full abstract»

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  • A Petri Net and Extended Genetic Algorithm Combined Scheduling Method for Wafer Fabrication

    Publication Year: 2013 , Page(s): 197 - 204
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1148 KB) |  | HTML iconHTML  

    As one of the most complicated manufacturing processes, semiconductor manufacturing consists of four steps, wafer sort, wafer fabrication, assembly, and testing. Among them, wafer fabrication is the most costly, complex, and time consuming step. Its operation management and optimization are challenging modeling and scheduling researchers. To address its modeling issue, a hierarchical colored timed Petri net (HCTPN) is proposed, which can be used to describe various states, behavior and substructures of a wafer fabrication system. To address its scheduling issue, intelligent algorithms are introduced to the proposed HCTPN. An extended genetic algorithm (EGA) embedded scheduling strategy over HCTPN is studied to optimize the combination of scheduling policies. The combined approach can conduct more efficient search with better scheduling performance. At last, a real case is presented to illustrate the results. Based on comparing simulation results of different scheduling strategies, the HCTPN and EGA combined scheduling is proved to be valid and efficient. View full abstract»

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  • An Approximate Solution for Semi-Open Queueing Network Model of an Autonomous Vehicle Storage and Retrieval System

    Publication Year: 2013 , Page(s): 205 - 215
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (870 KB) |  | HTML iconHTML  

    We present an analytical model for an autonomous vehicle storage and retrieval system (AVS/RS). The system is modeled as a semi-open queueing network (SOQN). An SOQN consists of customers, a secondary resource and servers. Each arriving customer is paired with the secondary resource. The two visit the set of servers required by the customer in the specified sequence. In the context of an AVS/RS, storage/retrieval (S/R) transactions are customers and the autonomous vehicles are the secondary resources. If an S/R transaction requires a vertical movement, it uses a lift. The lifts and horizontal travel times to and from a storage space are modeled as servers. First, we define all possible scenarios for storage and retrieval transactions and their occurrence probabilities. Second, we derive general travel times of vehicles and lifts by considering all possible locations of the two devices based on the predefined storage and retrieval scenarios, defined in step 1. Third, each scenario is modeled as a customer type and these customer classes are aggregated into a single class. Thus, we model the system as a single-class, multiple-server, SOQN. Finally , we solve the SOQN using an approximate method and obtain the performance measures. We apply the method to analyze a warehouse in France that utilizes AVS/RS. View full abstract»

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  • Visual Control of an Automatic Manipulation System by Microscope and Pneumatic Actuator

    Publication Year: 2013 , Page(s): 215 - 218
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (651 KB) |  | HTML iconHTML  

    This paper presents an automatic manipulation system consisting of microscope and pneumatic actuator. Through image captured by microscope with a CCD camera, the position between the probe and the object can be calculated in the image plane. A visual fuzzy controller is designed to improve the precision of a nonlinear pneumatic manipulator. From the experimental results, the position error of the system is below 1 pixel. The system can be applied to puncture fish embryo. View full abstract»

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  • Requirement-Based Bidding Language for Agent-Based Scheduling

    Publication Year: 2013 , Page(s): 219 - 223
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (421 KB) |  | HTML iconHTML  

    This paper presents a requirement-based bidding language for agent-based scheduling. The language allows agents to attach their valuations directly to scheduling performance requirements. Compared with general bidding languages, the proposed one reduces agents' valuation and system's communication complexities. In addition, it results in efficient winner determination problem models. Experimental results show that the requirement-based language exhibits superior winner determination performance in terms of problem-solving speed and scalability. View full abstract»

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  • Open Access

    Publication Year: 2013 , Page(s): 224
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    Freely Available from IEEE

Aims & Scope

T-ASE will publish foundational research on Automation: scientific methods and technologies that improve efficiency, productivity, quality, and reliability, specifically for methods, machines, and systems operating in structured environments over long periods, and the explicit structuring of environments.

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Meet Our Editors

Editor-in-Chief
Ken Goldberg
University of California, Berkeley