Cost analysis and extension of a simple maintenance-scheduling heuristic

Practitioners of maintenance scheduling sometimes use a simple analytic formula, derived based on inspection scheduling, as a heuristic to determine the length of the preventive maintenance period. The sensitivity of this heuristic solution is analyzed and the cost penalties are calculated compared to the exact solution that utilizes the lifetime distribution in the derivation of the optimal preventive maintenance period. A simple extension of the heuristic is suggested to improve the approximation with a slightly increased computational effort. The sensitivity and cost analysis of the improved heuristic are discussed as well. © 1994 John Wiley & Sons, Inc.     

Preserving defense technologies: A strategy for economic conversion†

This paper presents a model for converting legacy defense production facilities into private‐sector economic resources. Specifically, this paper will examine as a case study the first successful conversion of a former U.S. Department of Energy nuclear weapons production installation, including reasons for its success, its costs and benefits, and lessons for public policy. It is envisioned that this model may be useful for mitigating local economic hardship resulting from defense “downsizing” and for privatizing production capacities critical for national defense.     

How should modeling and simulation be used to support defense acquisition?

This paper investigates the potential for modeling and simulation to contribute to new defense system development, by increasing the productivity of traditional R&D in developing system‐specific technology. Building on a previous optimal control model of defense system R&D, it shows that (1) the optimal use of modeling is related in a natural way to that of traditional R&D, and (2) both have similar optimal profiles over time. Simulated results based on limited historical data suggest that optimal use of modeling could increase the rate of growth in system‐specific technology significantly.     

Vapor-phase decomposition of dimethyl methylphosphonate (DMMP), a sarin surrogate,in presence of metal oxides

Chemical warfare agents (CWA) are stockpiled in large quantities across the globe. Agents stored in inaccessible facilities need to be destroyed rapidly without dispersing the compounds to surrounding areas. Metal-based energetic formulations are used in such prompt defeat applications to rapidly decompose the CWA by generating a high temperature environment. An alternate, and possibly a more effective decomposition pathway could be provided by chemicidal action of aerosolized condensed combustion products, which typically consist of metal oxides. Toxic fumes that escape the high tem-perature blast zone can be neutralized by smoke generated during combustion, depending on the par-ticle size, surface characteristics, chemical properties, and concentration of this smoke. This review considers relevant experimental and modeling studies quantifying decomposition of CWA comprising organophosphorus compounds and their surrogates on the surface of various metal oxides. Dimethyl methylphosphonate (DMMP), a sarine surrogate, was used most commonly for such experiments. Many reported efforts focused on the mechanisms of adsorption of DMMP to various metal oxides and initial reaction steps cleaving various bonds from the chemisorbed molecules. For selected oxides, these ex-periments were supported by quantum-mechanical calculations. In other studies, the capacity of oxide surfaces to adsorb and decompose DMMP was quantified. In most cases, porous catalysts were used although limited experimental data are available for aerosolized nonporous oxide particles. The reported experimental data applicable to scenarios involving prompt decomposition of CWA are summarized. It is noted that information is lacking describing respective heterogeneous reaction kinetics. Preliminary estimates of aerosolized smoke particle concentrations required to destroy CWA are made considering gas phase diffusion rates and reported values of the oxide capacity to decompose CWA or their surrogates.     

Computer software development: Quality attributes,measurements, and metrics

Software metrics try to identify, define, and assign various indices of merit that can support the quantitative comparisons and evaluations of software in all phases of its life cycle. This article is a state-of-the-art and state-of-the-practice review of literature related to software quality measurements and metrics.     

Likelihood estimation for generalized mixed exponential distributions

The class of functions expressed as linear (not necessarily convex) combinations of negative exponential functions is dense in the set of all square integrable functions on the nonnegative reals. Because of this and resultant mathematical properties, linear combinations of exponential densities have excellent potential for wide application in stochastic modeling. This work documents the development and testing of a practical procedure for maximum-likelihood estimation for these generalized exponential mixtures. The algorithm offered for the problem is of the Jacobi type and guarantees that the result will provide a legitimate probability function of the prescribed type. Extensive testing has been performed and results are very favorable: convergence is rapid and the use of computer resources rather limited.     

Confidence intervals for ranked means

Suppose that observations from populations π₁, …, π_k (k ≥ 1) are normally distributed with unknown means μ₁., μ_k, respectively, and a common known variance σ². Let μ_[1] μ … ≤ μ_[k] denote the ranked means. We take n independent observations from each population, denote the sample mean of the n observation from π₁ by X _i (i = 1, …, k), and define the ranked sample means X _[1] ≤ … ≤ X _[k]. The problem of confidence interval estimation of μ₍₁₎, …,μ_[k] is stated and related to previous work (Section 1). The following results are obtained (Section 2). For i = 1, …, k and any γ(0 < γ < 1) an upper confidence interval for μ_[i] with minimal probability of coverage γ is (? ∞, X _[i]+ h) with h = (σ/n^1/2) Φ^?1(γ^1/k-i+1), where Φ(·) is the standard normal cdf. A lower confidence interval for μ_[i] with minimal probability of coverage γ is (X _i[i] – g, + ∞) with g = (σ/n^1/2) Φ^?1(γ^1/i). For the upper confidence interval on μ_[i] the maximal probability of coverage is 1– [1 – γ^1/k-i+1]ⁱ, while for the lower confidence interval on μ_[i] the maximal probability of coverage is 1–[1– γ^1/i] ^k-i+¹. Thus the maximal overprotection can always be calculated. The overprotection is tabled for k = 2, 3. These results extend to certain translation parameter families. It is proven that, under a bounded completeness condition, a monotone upper confidence interval h(X ₁, …, X _k) for μ_[i] with probability of coverage γ(0 < γ < 1) for all μ = (μ_[1], …,μ_[k]), does not exist.     

MAD: Mathematical analysis of downtime

The MAD model presents a mathematic treatment of the relationship between aircraft reliability and maintainability, system manning and inspection policies, scheduling and sortie length, and aircraft downtime. Log normal distributions are postulated for subsystem repair times and simultaneous repair of malfunctions is assumed. The aircraft downtime for maintenance is computed with the distribution of the largest of k log normal distributions. Waiting time for maintenance men is calculated either by using a multiple-channel queuing model or by generating the distribution of the number of maintenance men required and comparing this to the number of men available to determine the probability of waiting at each inspection.