Microwave Communication to Moving Parts Inside Machines

Cables to moving parts on a linear actuator in production machines, such as pick-and-place machines, are a source of unreliability owing to the possible breaking of a cable. They further reduce the positioning precision of the actuator owing to additional forces. Slotted waveguide systems for rail vehicles based on 2.4 GHz transmission frequency are well known, but transmitters/receivers and waveguides are bulky. The paper reports on the reduction in size of the equipment, adapted to 5.8 GHz using a commercial off-the-shelf RadioLan communication module. Further, the efficient termination of the wave-guide and a new way to reduce standing-wave effects is also discussed.     

Spare parts inventory management with demand lead times and rationing

We study an inventory system that consists of two demand classes. The orders in the first class need to be satisfied immediately, whereas the orders in the second class are to be filled in a given demand lead time. The two classes are also of different criticality. For this system, we propose a policy that rations the non-critical orders. Under a one-for-one replenishment policy with backordering and for Poisson demand arrivals for both classes, we first derive expressions for the service levels of both classes. The service level for the critical class is an approximation, whereas the service level for the non-critical class is exact. We then conduct a computational study to show that our approximation works reasonably, the benefits of rationing can be substantial, and the incorporation of demand lead time provides more value when the demand class with demand lead time is the critical class. The research is motivated by the spare parts service system of a major capital equipment manufacturer that faces two types of demand. For this company, the critical down orders need to be satisfied immediately, while the less critical maintenance orders can be satisfied after a fixed demand lead time. We conduct a case study with 64 representative parts and show that significant savings (as much as 14% on inventory on hand) are possible through incorporation of demand lead times and rationing.     

基于聚类算法实现信号盲分类

本文解决了信号处理、工业控制等领域存在的非平稳信号盲分类问题。在聚类中广泛应用的K-Means算法及其它基于中心的聚类算法有两个共同的缺陷-需要预先确定类数目且随机初始化中心引起性能不稳定。本文提出的算法较好地解决了这两个问题，提高了算法稳定性，实现了非平稳信号盲分类。提取非平稳信号的小波系数作为聚类的样本空间，分析聚类结果的统计偏差以估计类的数目，采用调和均值准则进行分类。最后给出的仿真结果表明本文提出的方法较传统的K-Means算法明显降低分类错误率。     

A fuzzy clustering algorithm enhancing local model interpretability

In this work, simple modifications on the cost index of particular local-model fuzzy clustering algorithms are proposed in order to improve the readability of the resulting models. The final goal is simultaneously providing local linear models (reasonably close to the plant’s Jacobian) and clustering in the input space so that desirable characteristics (regarding final model accuracy, and convexity and smoothness of the cluster membership functions) are improved with respect to other proposals in literature. Some examples illustrate the proposed approach.     

注塑件熔接缝结构,性能评价及影响因素

文章介绍了熔接缝形成的原因，接缝类型，接缝外观和断口形态特征以及接缝性能评价方法。分析了接缝类型，塑料材料性质，工艺参数和其它因素对接缝性能的影响。     

Software for dynamic reconfigurable order picking systems

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.     

Discrete-time spare ordering policy with randomized lead times and discounting

The paper considers a generalized discrete‐time order‐replacement model for a single unit system, which is subject to random failure when in operation. Two types of discrete randomized lead times are considered for a spare unit; one is for regular (preventive) order and another is for expedited (emergency) order. The model is formulated based on the discounted cost criterion. The underlying two‐dimensional optimization problem is reduced to a simple one‐dimensional one and then the optimal ordering policy for the spare unit is characterized under two extreme conditions: (i) unlimited inventory time and (ii) zero inventory time for the spare unit. A numerical example is used to determine the optimal spare‐ordering policy numerically and to examine the sensitivity of the model parameters.     

Non-redundant data clustering

Data clustering is a popular approach for automatically finding classes, concepts, or groups of patterns. In practice, this discovery process should avoid redundancies with existing knowledge about class structures or groupings, and reveal novel, previously unknown aspects of the data. In order to deal with this problem, we present an extension of the information bottleneck framework, called coordinated conditional information bottleneck, which takes negative relevance information into account by maximizing a conditional mutual information score subject to constraints. Algorithmically, one can apply an alternating optimization scheme that can be used in conjunction with different types of numeric and non-numeric attributes. We discuss extensions of the technique to the tasks of semi-supervised classification and enumeration of successive non-redundant clusterings. We present experimental results for applications in text mining and computer vision.     

Simulation and optimization of tool-life in manufacturing centers

This paper presents the development of an optimization and a computer-simulation model to evaluate the process plans of a manufacturing center by analyzing the effect of tool failure on system performance. The GPSS/PC simulation program that is used in this study has been built with variables, functions and matrices so that many experiments could be conducted with the model. Sensitivity analysis is presented and the developed model has proven to be useful in determining optimum sequencing of parts for various operating policies.     

Pressure infiltration of boron nitride preforms with molten aluminum

The infiltration of compacted cubic BN (cBN) with molten aluminum has been investigated as a potential route for a cheap and easy method of manufacturing cBN/metal composites. CBN compacts have been infiltrated with molten Al at a temperature between 670 and 800 °C and pressure of 15 MPa in vacuum. At these temperatures no pronounced interactions between hexagonal and cubic BN with Al was observed, allowing the complete infiltration of cBN with 12 μm mean grain size. After infiltration at 800 °C, the temperature was increased without pressure to convert aluminum into borides and AlN. The hardness of the resulting materials depends on the content of hexagonal, cubic BN and the rate of conversion of Al into borides and AlN. The infiltration height of less than 1 mm obtained from infiltrating the 3 μm cBN powder green compacts gave a hardness of 22.0 ± 0.6 GPa after heat treatment.