Suneung Ahn

Modeling lateral transshipments in multiechelon repairable-item inventory systems with finite repair channels

This article concerns the problem of determining the optimal spare inventory level for a multiechelon repairable-item inventory system, which has several bases and a central depot. When an item fails, the failed item is replaced immediately if a spare is available at the base. If there is no spare item available at the base, it is requested as a lateral transshipment to another base that has a spare in stock. If an item is not available from any of the bases, the item is backordered until a spare becomes available. We propose a model to describe the behavior of the system and develop an algorithm to find the spare inventory level at each base, which minimizes the total expected cost of the system. The algorithm is illustrated using examples of various sizes.

On Determination of the Preventive Maintenance Interval Guaranteeing System Availability Under a Periodic Maintenance Policy

In order for an engineering system to maintain a certain level of availability, preventive maintenance actions are commonly performed. This paper deals with the analysis for determining the optimum frequency to perform preventive maintenance actions for a system exhibiting a linearly increasing hazard rate and a constant repair rate. Under a periodic maintenance policy, as long as a predetermined availability is guaranteed, the time interval between preventive maintenance actions incurring the minimal maintenance cost is selected. Considering both the maintenance cost and system availability, guidelines for determining the maintenance time interval are presented. Simple examples are also provided to illustrate these ideas.

A Bayesian decision model based on expected utility and uncertainty risk

Abstract Risk is caused by the uncertainty of state of nature and a decision maker’s selection, and the result may appear to be an unfavorable outcome. Therefore, a decision maker wants to maximize an expected return with minimal risk exposures. In this paper, we propose an expected utility and uncertainty risk (EU–UR) model based on the reference prior, which extends the classical decision model under uncertainty. The EU–UR model is made by making a compromise between measures of expected utility and uncertainty. The model is empirically validated by applying to the Levy’s case and the Allais paradox.

A multiple replenishment contract with ARIMA demand processes

This paper is concerned with a multiple replenishment contract with a purchase price discount in a supply chain. The chain is composed of one supplier, one buyer and consumers for a product. The replenishment contract is based upon the well-known (s, Q) policy, but allows us to contract replenishments at a future time with a price discount. Owing to the larger forecast error of future demand, the buyer should keep a higher level of safety stock to provide the same level of service as the usual (s, Q) policy. However, the buyer can reduce his purchase cost by ordering a larger quantity at a discounted price. Hence, there exists a trade-off between the price discount and the inventory holding cost. For the ARIMA demand processes, we present a model for the contract and an algorithm to find the number of the future replenishments. Computational experiments show that the algorithm finds the global optimum solution very quickly.

Analysis of Acoustic Emission Signals During Laser Spot Welding of SS304 Stainless Steel

In this article, an in-process monitoring scheme for a pulsed Nd:YAG laser spot welding (LSW) is presented. Acoustic emission (AE) was selected for the feedback signal, and the AE data during LSW were sampled and analyzed for varying process conditions such as laser power and pulse duration. In the analysis, possible AE generation sources such as melting and solidification mechanism during welding were investigated using both the time- and frequency-domain signal processings. The results, which show close relationships between LSW and AE signals, were adopted in the feature (input) selection of a back-propagation artificial neural network, to predict the weldability of stainless steel sheets. Processed outputs agree well with LSW experimental data, which confirms the usefulness of the proposed scheme.

A Low Phase Noise Octa-Phase LC VCO for Multi-band Direct Conversion Receiver

This paper presents an octa-phase LC VCO for a multi-band direct conversion receiver. To obtain the octa-phase signal and low phase noise characteristic, four identical LC VCOs are connected by using series coupling transistors. For a multi-band application, a band tuning circuit that is composed of a switch capacitor circuit and two MOS varactors is proposed. Using two varactors, the VCO can be immune to process variation of the oscillation frequency. Designed in 0.18 mum CMOS technology, the VCO consumes 9.52 mA current from 1.8 V supply voltage and operates with a frequency band from 885 MHz to 1.342 GHz (41% tuning range). As driving sub-harmonic mixer, the proposed VCO covers three standards: cdma2000 1x (1.84 ~ 1.87 GHz), WCDMA (2.11 ~ 2.17 GHz), WiBro (2.3 ~ 2.4 GHz). The simulated phase noise is -107 dBc, -133 dBc, and -155 dBc at 100 kHz, 1 MHz, and 10 MHz offset frequency for cdma2000 1x, WCDMA, and WiBro respectively.

PROBABILISTIC PREDICTION OF BURR PATTERNS OF 1045 CARBON STEEL IN FACE MILLING

Face milling burrs in ductile materials such as 1045 carbon steel exhibit three distinct burr patterns: uniform, wavy, and secondary burrs. It is found that the three burr patterns are dependent on the in-plane exit angle, undeformed chip ratio, and undeformed chip area at the exit stage of cut. Empirical equations, representing the burr transition curves from the uniform to wavy burr and wavy to secondary burr, are found. Based on the empirical relationships, a probabilistic model, in which the operational Bayesian modeling approach is adopted to include the empirical equations, is derived for burr prediction.