Variables inspection for SPC‐quarantined production

When a control chart signals an out‐of‐control condition for a production process, it may be desirable to “quarantine” all units produced since the last in‐control SPC sample. This paper presents an efficient procedure for variables inspection of such “SPC quarantined” product. A Bayesian sequential inspection procedure is developed which determines whether the out of control production is of acceptable quality. By inspecting the units in reverse of the order in which they were produced, the procedure is also capable of detecting the point at which the process went out of control, thus eliminating the need to inspect units produced prior to the onset of the out of control condition. Numerical examples are presented, and the performance characteristics of the procedure are demonstrated using Monte Carlo simulation. © 2001 John Wiley & Sons, Inc. Naval Research Logistics 48: 159–171, 2001     

Combat modeling of remotely targeted vehicles and a battery against a moving target

This paper considers a combined system composed of multiple stand-by remotely piloted vehicles (RPVs) and a single battery against a single passive enemy target, where the target, if not killed, is allowed to change its location after each attack. The RPV has the duty to report on target acquisition, to confirm a target kill, and to pass information on any change in target location after each battery attack. The battery has the duty to attack the target on the basis of the target location information provided to it by the RPV. We develop a closed-form expression for the time-dependent state probabilities of the system, which can be used to compute several important combat measures of effectiveness, including (a) the time-varying mean and variance of the number of the RPVs being alive and of the surviving enemy target, (b) the mission success, mission failure, and combat draw probabilities, and (c) the mean and variance of the combat duration time. Illustrative numerical examples are solved for these combat measures, and sensitivity analyses are performed with respect to target acquisition time and target kill probability. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 645–667, 1998     

Scheduling stochastic jobs with asymmetric earliness and tardiness penalties

We consider a stochastic counterpart of the well-known earliness-tardiness scheduling problem with a common due date, in which n stochastic jobs are to be processed on a single machine. The processing times of the jobs are independent and normally distributed random variables with known means and known variances that are proportional to the means. The due dates of the jobs are random variables following a common probability distribution. The objective is to minimize the expectation of a weighted combination of the earliness penalty, the tardiness penalty, and the flow-time penalty. One of our main results is that an optimal sequence for the problem must be V-shaped with respect to the mean processing times. Other characterizations of the optimal solution are also established. Two algorithms are proposed, which can generate optimal or near-optimal solutions in pseudopolynomial time. The proposed algorithms are also extended to problems where processing times do not satisfy the assumption in the model above, and are evaluated when processing times follow different probability distributions, including general normal (without the proportional relation between variances and means), uniform, Laplace, and exponential. © 1997 John Wiley & Sons, Inc. Naval Research Logistics 44, 531–557, 1997.     

One- and two-sided sampling plans based on the exponential distribution

In this paper we examine the one- and two-sided sampling plans for the exponential distribution. Solutions are provided for several situations arising out of the assumptions on the knowledge of the parameters of the distribution. The values of the constants are tabled in the special case of p₁ = p₂ for the two-sided plans.     

Measuring defense conversion in Russian industry

This paper develops and implements a methodology for quantifying defense conversion in Russian manufacturing in the early 1990s. A two‐sector, three‐good model is employed to analyze the flows of resources from military to non‐military uses and applied to firm‐level survey data under alternative definitions of military production and the MIC. An aggregation framework is constructed to estimate the total quantity and change in Russian military production, the latter decomposed into intrafirm and intersectoral resource reallocation and overall industrial decline. Although there is evidence of substantial decline in military production, the data show little reallocation to productive civilian uses, neither within the MIC nor to other manufacturing sectors.     

Survival distributions in crossing fields containing clusters of mines with possible detection and uncertain activation or kill

The present paper presents an algorithm for the exact determination of survival distributions in crossing mine fields. The model under consideration considers clusters of mines, scattered at random in the field around specified aim points. The scatter distributions of the various clusters are assumed to be known The encounter process allows for a possible detection and destruction of the mines, for inactivation of the mines and for the possibility that an activated mine will not destroy the object. Recursive formulae for the determination of the survival probabilities of each object (tank) in a column of n crossing at the same path are given. The distribution of the number of survivors out of n objects in a column is also determined. Numerical examples are given.