This paper describes an approach, conceptual framework, and software architecture for dynamic reconfiguration of the order picking system. The research and development project was sponsored by the Material Handling Research Center (MHRC), a National Science Foundation sponsored Cooperative Industry/University Research Center. The storage configuration is assumed to be an in-the-aisle order picking system in which stockkeeping units (SKUs) can occupy variable capacity storage locations and stock-splitting is allowed among zones (clusters). The product mix may include multiple product families with different life cycles, correlated demand within families and commonality of demand across families. 相似文献
This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.
A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system. 相似文献
As the result of vibration emission in air, a machine sound signal carries important information about the working condition
of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features
of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition
must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored
source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed
that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound
sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white
noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS
analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation
algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer
channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via
this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained
from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods . 相似文献
In this paper, genetic algorithm is used to help improve the tolerance of feedforward neural networks against an open fault. The proposed method does not explicitly add any redundancy to the network, nor does it modify the training algorithm. Experiments show that it may profit the fault tolerance as well as the generalisation ability of neural networks.相似文献
Response time (RT) of Networked Automation Systems (NAS) is affected by timing imperfections induced due to the network, computing and hardware components. Guaranteeing RT in the presence of such timing imperfections is essential for building dependable NAS, and to avoid costly upgrades after deployment in industries.This investigation proposes a methodology and work-flow that combines modelling, simulation, verification, experiments, and software tools to verify the RT of the NAS during the design, rather than after deployment. The RT evaluation work-flow has three phases: model building, modelling and verification. During the model building phase component reaction times are specified and their timing performance is measured by combining experiments with simulation. During the modelling phase, component based mathematical models that capture the network architecture and inter-connection are proposed. Composition of the component models gives the NAS model required for studying the RT performance on system level. Finally, in the verification step, the NAS formal models are abstracted as UPPAAL timed automata with their timing interfaces. To model timing interfaces, the action patterns, and their timing wrapper are proposed. The formal model of high level of abstraction is used to verify the total response time of the NAS where the reactions to be verified are specified using a subset of timed computation tree logic (TCTL) in UPPAAL model checker. The proposed approach is illustrated on an industrial steam boiler deployment. 相似文献