John O. Miller

The Use of Third-party Logistics Services by Large US Manufacturers, The 2000 Survey

This paper examines the findings of a survey of the chief logistics executives of Fortune 500 manufacturers concerning their use of third party logistics services (3PL). The survey determined that, as a group, their use of those services has reached an all-time high, as has the percentage of their logistics budgets being given to 3PL providers. The typical 3PL user identified in this survey uses a wide variety of those services and buys them from multiple providers. While many 3PL users also rely upon 3PL providers for information technology support, less than one-third of them use those providers to support their E-commerce initiatives. Users are generally well satisfied with the impact of 3PL services on their companies, and are most satisfied with the impact on logistics costs, logistics service levels, and customer service.

Efficient multinomial selection in simulation

Abstract : This report considers a simulation experiment consisting of v independent vector observations or replications across k systems, where in any given replication one and only one system is selected as the best performer (i.e., it wins) based on some performance measure. Each system has an unknown constant probability of winning in any replication and the numbers of wins for the individual systems follow a multinomial distribution. The classical multinomial selection procedure of Bechhofer, Elmaghraby, and Morse (Procedure BEM), prescribes a minimum number of replications, denoted as V*, 50 that the probability of correctly selecting the true best system meets or exceeds a prespecified probability. Assuming that larger is better, Procedure BEM selects as best the system having the largest value of the performance measure in more replications than any other system.

Applications of discrete event simulation modeling to military problems

The military is a big user of discrete event simulation models. The use of these models range from training and wargaming their constructive use in important military analyses. In this paper we discuss the uses of military simulation, the issues associated with military simulation to include categorizations of various types of military simulation. We then discuss three particular simulation studies undertaken with the Air Force Institute of Technologys Department of Operational Science focused on important Air Force and Army issues.

Application of agent based modelling to aircraft maintenance manning and sortie generation

Abstract This research develops an agent based simulation model for application to the sortie generation process, focusing on a single fighter aircraft unit. The simulation includes representations of each individual maintainer within the unit, along with supervisory agents that provide direction in the form of dynamic task prioritization and resource assignment. Using a high-fidelity depiction of each entity, an exploration of the effects of different mixes of skill levels and United States Air Force Specialty Codes (AFSCs) on sortie production is performed. Analysis is conducted using an experimental design with results presented demonstrating the effects of maintenance manning decisions on the Combat Mission Readiness (CMR) of a fighter unit.

Input modeling when simple models fail

A simulation model is composed of inputs and logic; the inputs represent the uncertainty or randomness in the system, while the logic determines how the system reacts to the uncertain elements. Simple input models, consisting of independent and identically distributed sequences of random variates from standard probability distributions, are included in every commercial simulation language. Software to fit these distributions to data is also available. In this tutorial we describe input models that are useful when simple models are not.

A multinomial selection procedure for evaluating pattern recognition algorithms

Abstract This paper introduces a multinomial selection problem (MSP) procedure as an alternative to classification accuracy and receiver operating characteristic analysis for evaluating competing pattern recognition algorithms. This new application of MSP demonstrates increased differentiation power over traditional classifier evaluation methods when applied to three “toy” problems of varying difficulty. The MSP procedure is also used to compare the performance of statistical classifiers and artificial neural networks on three real-world classification problems. The results provide confidence in the MSP procedure as a useful tool in distinguishing between competing classifiers and providing insights on the strength of conviction of a classifier.

Getting more from the data in a multinomial selection problem

We consider the problem of determining which of k simulated systems is most likely to be the best per former based on some objective performance measure. The standard experiment is to generate v in dependent vector observations (replications) across the k- systems. A classical multinomial selection pro cedure, BEM (Bechhofer, Elmaghraby, and Morse), prescribes a minimum number of replications so that the probability of correctly selecting the true best system meets or exceeds a prespecified probability. Assuming that larger is better, BEM selects as best the system having the largest value of the performance measure in more replications than any other. We propose using these same v replications across k systems to form vk pseudoreplications (no longer in dependent) that contain one observation from each system, and again select as best the system having the largest value of the performance measure in more pseudoreplications than any other. We expect that this new procedure, AVC (all vector comparisons), dominates BEM in the sense that AVC will never require more independent replications than DEM to meet a prespecified probability of correct selection. We present analytical and simulation results to show how AVC fares versus BEM for different underly ing distribution families, different numbers of populations and various values of v. We also present results for the closely related problem of estimating the probability that a specific system is the best.

A Methodology to Reduce Aerospace Ground Equipment Requirements for an Air Expeditionary Force

For many years the US military has maintained a significant overseas presence. Changes in the international political landscape has led to military reductions, particularly in this overseas military presence. To meet increased deployment demands from US-based stations the US Air Force is restructuring to accommodate an Expeditionary Aerospace Force (EAF) concept. As the United States Air Force evolves into an EAF using tailored combat force packages to meet specific threats, the requisite support functions for the deployed forces will garner increasing attention. We propose and examine a simulation-based methodology for examining options to reduce the amount of support equipment deployed with a tailored force. The simulation model is based on aircraft system failures and the ensuing maintenance actions. These maintenance actions drive the utilisation of aerospace ground equipment used to support aircraft maintenance. Support equipment deployment levels are re-examined using expected equipment utilisation rates while the risk to combat capability is quantified. Specific deployment support options examined include maintenance restrictions, just-in-time delivery of support equipment and the potential impact of proposed consolidated, or multifunction support equipment. Impacts on airlift requirements are estimated for each strategy examined.

Multivariate Analysis of a Simulated Prognostics and Health Management System for Military Aircraft Maintenance

The Air Force logistics operations system is, in general, reactive in nature, with unscheduled aircraft maintenance beginning with a signal for out of tolerance conditions from the aircraft, subsequent fault isolation procedures performed by a maintenance team, and the steps taken to repair or replace the faulty item. The Joint Strike Fighter (JSF) programme has been pursuing an autonomic logistics system (ALS) concept that changes this reactive process into a proactive one, with the employment of technologies such as prognostics and a distributed information network. This paper briefly describes a simulation model of a prognostics and health management (PHM) system employed as part of an ALS for a JSF-type aircraft. The simulation produces a large number of commonly used flight line measures of performance for aircraft availability and mission effectiveness. Multivariate statistical analysis of these outputs provides a means to assess the impact of a PHM system on aircraft productivity.

Methodologies for aggregating large hierarchical simulation models

This research investigates how aggregation is currently conducted for simulation of large systems. The focus is on the exploration of the different aggregation techniques for hierarchical lower-level (higher resolution) models into the next higher-level. We develop aggregation procedures between two simulation levels (e.g., aggregation of mission level models into a campaign level model) to address how much and what information needs to pass from the high-resolution to the low-resolution model in order to preserve statistical fidelity. We present a mathematical representation of the simulation model based on network theory and procedures for simulation aggregation that are logical and executable. The proposed process is a collection of various conventional statistical and aggregation techniques, but we present them in a coherent and systematic manner. Our desired real-world application for the developed simulation aggregation process is in the area of military combat. We show preliminary results as applied to a complex hierarchical flying training model. There is no best universal aggregation technique for different simulation models; however, the method developed here is a well-defined set of procedures for statistically sound simulation model aggregation.