NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Session 2457 Session 2457 MULTIMEDIA APPLICATION ON THE INTERNET C. Patrick Koelling*, John E. Kobza*, Tamie Veith*, Mario G. Beruvides+ *Virginia Polytechnic Institute and State University/+Texas Tech University Background In August 1995 the National Science Foundation, through SUCCEED (Southeastern University and College Coalition for Engineering Education), funded a project to develop and test a multimedia laboratory experience in work measurement and methods engineering. The primary purpose was to evaluate the efficacy of the multimedia vehicle compared to alternatives such as strictly text-based, standard multimedia, and simulation multimedia (Koelling and Ramsey, 1996). In August 1996 SUCCEED funded a project to move the aforementioned multimedia experience to the Internet through the World Wide Web. There are many obvious advantages to this distribution media, including ease of update, ease of distribution, version control, and the ability to acquire information on usage. Of course, disadvantages abound. Network traffic, immaturity of software, and other technology issues pose difficulties that must be overcome. This paper addresses our experience in moving the work measurement and methods engineering multimedia laboratory from the CD to the World Wide Web. The multimedia version was originally developed in Macromedia Director 4.0 (and later moved to Director 5.0) and was made accessible over the Internet by the use of Macromedia’s Shockwave technology. We explain issues relevant to moving to the Web and discuss data gathered through the experience in an attempt to compare the CD and Web technologies. The Multimedia Application The multimedia system in this research uses a combination of text, video, audio, graphics, and animation to present instructional material. The system was developed with Macromedia Director 4.0 on the Macintosh platform. The projector feature of Director allows each multimedia system to run as a stand-alone application. The multimedia system presents the material in a highly-structured manner, which has become a standard interface for instructional multimedia. Information is grouped under topics. A button for each topic is present at all times to allow quick access to each section of the program. After a topic button is chosen, the instructional information for the chosen section is presented in a large window. More information about the section can then be accessed through the use of a Next

An effective risk management procedure can counterbalance critical effects on supply chains. Computer applications, optimization and simulation techniques have been applied to improve the decision-making process. The purpose of this article is to analyze the role and contribution of simulation and optimization methods for the supply chain risk management approach. A systematic literature review process was performed, followed by discussions and analysis on the examined topic. The results revealed a key methodological disconnection involving risk management phases, simulation and optimization methods. Although the number of published papers on the topic has been significant, this gap highlights the limitations of several models to represent the dynamics and complexity of the risks in supply chains, particularly on real-world/real-time applications. Hybrid and flexible simulation-based optimization models for supply chain risk management could improve the decision-making process. In addition, gaps, a procedural framework, and future research directions are suggested aiming to develop new applications focused on simulation and optimization tools for risk mitigation proposes.

A maintenance optimization model is developed to maximize the net value of imperfect degradation-based maintenance by determining an optimal interval of condition monitoring and the degradation level after imperfect repairs. The proposed decision model intends to maximize the difference between the maintenance value and the expected total cost of maintenance during a life cycle. The value of maintenance depends on the expected life cycle length which positively affected by maintenance activities. The value-based strategy advocates applying more frequent monitoring. However, the optimal net value might be insensitive to the degradation level after repair. It implies the possibility of reaching the maximum value of maintenance even without the highest level of repairs.

The aim of this article is to analyze logistics risks from tools applied in risk management phases. A systematic literature review was the main research method. A sample of conference proceeding papers was formed from the IEEE Xplore Digital Library database. The core results show that mathematical modeling was the scientific method most applied by authors in literature. Logistics outsourcing was the primary topic, also identified as the central type of risk. Risk ranking indexes were employed as the main logistics risk measures. Multi-criteria methods, for instance, Fuzzy Comprehensive Evaluation and AHP were the focal tools applied, especially in the risk assessment phase. As a future research direction we suggest the combined use of simulation-based optimization to support the logistics risk management.

Monotonic fault progression is an important assumption for a number of prognostic models. This assumption can be violated through human intervention and self‐healing and result in non-monotonic degradation data which not only increases the uncertainty but also may cause model failure. Methods to analyze and handle non-monotonic degradation in repairable systems are practically nonexistent in the literature. In this research, we intend to consider repairable systems in which self‐healing is possible and human interventions are desirable. We presented a novel example of self-healing for fatigue cracks analyzed by acoustic emission. The aim of the present paper is to initiate a new research area on using non-monotonic measures in degradation-based prognostics. However, this research is not a review of trend analysis techniques, and therefore, there are more techniques to be considered or developed in future studies. In effect, trend analysis should be considered as an integral part of prognostics and health management. This study considers trend analysis for three classes of data, (1) prognostic parameters, (2) degradation waveform, and (3) multivariate data. A new form of crest factor is introduced for more effective waveform analysis of non-monotonic data. In addition, two algorithms are introduced to treat non-monotonic trend. The prognostic model used in this research does not produce results without treating non-monotonicity. These kinds of algorithm have promising potential to treat non-monotonicity and deal with arbitrary stationary noise in degradation data.

An optimization model is developed to minimize the total cost of imperfect degradation-based maintenance by determining an optimal interval of condition monitoring and the degradation level after imperfect preventive repairs. The decision model is based on a novel cost model that considers functional relationship between the expected degradation reduction and the cost of preventive repairs. The decision model is applied to simulated vibration signals with a variety of specifications of cost values and degradation model parameters. This study has initiated a new area for the research of cost effective maintenance strategies. The results clearly indicate the significance of the proposed model and the decision variables under the objective of minimal cost. For instance, the results indicate direct relationship between the optimal length of monitoring interval and the monitoring cost. However, longer monitoring interval increases the risk of failure, and therefore, more degradation reduction is needed. By increasing the slope of cumulative degradation, the cost effective strategy advocates taking more frequent monitoring. The optimal degradation level after each preventive repair is not so sensitive to the change in the degradation slope due to the uncertainty associated with degradation patterns.

Practicable life extension of engineering systems would be a remarkable application of prognostics. Although considerable research has been devoted to developing prognostics algorithms, rather less attention has been paid to post-prognostic issues such as maintenance decision making. This research investigates the use of prognostic data to mobilize the potential residual life. In this respect, a multi-objective optimization model is presented for a typical power generation unit. This model proves the ability of prognostic models to balance between power generation and life extension. The results of the optimization models quantitatively indicated that maximizing the service life of bearings requires lower shaft speed and longer maintenance time.

This paper investigates the problem of allocating aviation security baggage screening devices across a set of airports. Prior to boarding an aircraft, passengers are divided into classes based on a passenger prescreening system that measures their perceived risk levels, which results in each passenger's baggage being screened by one or more security procedures. An explosive screening device allocation model is formulated to assign both the type of and number of devices to each class at each airport such that the total security is maximized subject to budget, resource, and throughput constraints. A Lagrangian relaxation is used to compute an upper bound for this objective function. Three heuristics, based on information from the Lagrangian relaxation, are proposed for addressing this model. Computational results are provided for several randomly generated problems, to provide insight into the effectiveness of the heuristics.

Methods to improve deterrence in aviation security screening systems provide added value in their operation and performance. A mathematical tool is introduced to optimally allocate security resources, design effective deterrence procedures, and identify where emphasis should be placed to achieve the most effective deterrence. A continuous-time Markov chain is used to model terrorist behavior within the aviation security environment. The resulting nine-state Markov chain model addresses three levels of behavior, three levels of expertise, and three levels of inactivity. Optimization is used to identify parameter values that minimize terrorist activity. The focus application for this approach is aviation security, though the modeling methodology introduced can be used in any area of security or law enforcement.

Electronic assembly operations are vital to industries such as telecommunications, computers and consumer electronics. This paper presents a constraint analysis methodology for planning and improving electronic assembly operations that draws on concepts from queueing theory, simulation and production planning. The proposed methodology identifies the operational bottleneck and predicts the utilization, throughput and lead time of the assembly line. It also quantifies the relationship between yields and utilization for the assembly operations. A case study is presented that applies the methodology at an Ericsson, Inc., telecommunications equipment assembly facility. The constraint analysis methodology provided valuable decision support as the managers of Ericsson evaluated the costs and benefits of additional production capacity. Although the focus of this paper is electronic assembly operations, the methodology can be applied to general flow line assembly systems with feedback loops for test and rework under dedicated high-volume production.

The Transportation Security Administration believes selective screening of aviation passengers may result in better security at airports in the United States. Under selective screening, passengers are prescreened using passenger information to determine the degree of risk that each passenger poses). This degree of risk is then used to determine the amount of security resources appropriate for that passenger. How to determine this degree of risk and the information that should be used are controversial topics, as evidenced by the large amounts of discussion concerning CAPPS and Secure Flight. This paper examines selective checked baggage screening systems that use a prescreening system and two types of baggage screening devices, one to screen checked baggage of passengers perceived as lower-risk and the other to screen checked baggage of passengers perceived as higher-risk. This paper reports a cost-benefit analysis of such selective checked baggage screening systems. The analysis is performed for several scenarios that consider various levels of accuracy of prescreening systems in assessing passenger risk. The results indicate that the accuracy of the prescreening system in assessing passenger risk is more important for reducing the number of successful attacks than the effectiveness of the checked baggage screening devices at detecting threats when few passengers are classified as higher-risk. Moreover, several selective screening scenarios are identified that may be preferable to current checked baggage screening strategies.

This paper surveys the coupon collector’s waiting time problem with random sample sizes and equally likely balls. Consider an urn containing m red balls. For each draw, a random number of balls are removed from the urn. The group of removed balls is painted white and returned to the urn. Several approaches to addressing this problem are discussed, including a Markov chain approach to compute the distribution and expected value of the number of draws required for the urn to contain j white balls given that it currently contains i white balls. As a special case, E [ N ], the expected number of draws until all the balls are white given that all are currently red is also obtained.

The events of September 11, 2001 will forever affect the lives of all those who observed their consequences. These events have changed the way in which people live and carry on their everyday affairs. These events also ignited the engineering community in general, and the industrial engineering community in particular, to refocus their energy to address problems that impact our nation’s safety, security, and well-being. This focused issue on homeland security reports several examples of how industrial engineering and operations research modeling and analysis techniques are being used to secure our nation’s borders, our transportation airspace system, our nation’s nuclear materials stockpiles, and the many critical infrastructures that support our social and economic foundations, and hence, impact the well-being of our citizens. Eight papers are included in this special issue, which span these vital and important areas of concern. Two papers consider issues surrounding interdiction. In the paper “Models for Nuclear Smuggling Interdiction,” Morton, Pan and Saeger introduce two stochastic network interdiction models for thwarting nuclear smuggling. In their first model, the smuggler travels through a transportation network on a path that maximizes the probability of evading detection, and the interdictor installs radiation sensors to minimize that evasion probability. In their second model, the interdictor and smuggler can have differing perceptions of these network parameters. Both models also consider the important special case in which the sensors can only be installed at border crossings of a single country. In a more general setting, the paper “Algorithms for Discrete and Continuous Multicommodity Flow Network Interdiction Problems,” by Lim and Smith, considers a network interdiction problem on a multicommodity flow network, where an attacker disables a set of network arcs so as to minimize the maximum profit that can be obtained from shipping commodities through the network. They examine problems in which interdiction must be discrete and in which interdiction can be continuous. They illustrate their models on a set of randomly generated test data. Several papers address the area of critical infrastructure support. In the paper “Allocation and Reallocation of Ambulances to Casualty Clusters in a Disaster Relief Operation,” Gong and Batta study ambulance allocation and reallocation models for a post-disaster relief operation. They consider allocating the correct number of ambulances to each cluster at the beginning of the rescue process, and formulate a method to determine the completion time for each cluster. They also analyze the ambulance reallocation problem on the basis of a discrete time policy. Jia, Ordonez and Dessouky study the problem of locating emergency medical service facilities to cope with large-scale emergencies. Their paper, “A Modeling Framework for Facility Location of Medical Services for Large-Scale Emergencies,” considers several strategies for deploying medical supplies to respond to low frequency, high impact events. The framework this research presents accounts for uncertainty in demand and geographical effects. Small examples based on the Los Angeles area are presented. In the paper, “Toward Modeling and Simulation of Critical National Infrastructure Interdependencies,” Min, Beyler, Brown, Son and Jones propose a modeling and analysis framework that considers the interdependencies between an integrated system of economic and physical infrastructures. They integrate individual infrastructure models together using system dynamics, functional models, and nonlinear optimization algorithms. An illustrative example is provided that demonstrates the technique using realistic models of the individual component infrastructures currently under development by government agencies, private industry, and academia. In the paper, “Integer Programming Models and Analysis for a Multilevel Passenger Screening Problem,” McLay, Jacobson and Kobza introduce the Multilevel Passenger

Designing effective aviation security systems has become a problem of national interest and concern. Passenger prescreening is an important component of aviation security. Effectively using passenger prescreening information to develop screening strategies can be quite challenging. Moreover, it can be difficult to measure the effectiveness of such systems after they are in place. To address these issues, this paper introduces the Multilevel Passenger Screening Problem (MPSP). In MPSP, a set of classes are available for screening passengers, each of which corresponds to several device types for passenger screening, where each device type has an associated capacity and passengers are differentiated by their perceived risk levels. The objective of MPSP is to use prescreening information to determine the passenger assignments that maximize the total security subject to capacity and assignment constraints. MPSP is illustrated with examples that incorporate flight schedule and passenger volume data extracted from the Official Airline Guide.

Passenger prescreening is a critical component of aviation security systems. This paper introduces the Multilevel Allocation Problem (MAP), which models the screening of passengers and baggage in a multilevel aviation security system. A passenger is screened by one of several classes, each of which corresponds to a set of procedures using security screening devices, where passengers are differentiated by their perceived risk levels. Each class is defined in terms of its fixed cost (the overhead costs), its marginal cost (the additional cost to screen a passenger), and its security level. The objective of MAP is to assign each passenger to a class such that the total security is maximized subject to passenger assignments and budget constraints. This paper shows that MAP is NP-hard and introduces a Greedy heuristic that obtains approximate solutions to MAP that use no more than two classes. Examples are constructed using data extracted from the Official Airline Guide. Analysis of the examples suggests that fewer security classes for passenger screening may be more effective and that using passenger risk information can lead to more effective security screening strategies. (c) 2006 Wiley Periodicals, Inc.

The terrorist attacks of September 11, 2001 have resulted in dramatic changes in aviation security. As of early 2003, an estimated 1,100 explosive detection systems (EDS) and 6,000 explosive trace detection machines (ETD) have been deployed to ensure 100% checked baggage screening at all commercial airports throughout the United States. The prohibitive costs associated with deploying and operating such devices is a serious issue for the Transportation Security Administration. This article evaluates the cost effectiveness of the explosive detection technologies currently deployed to screen checked baggage as well as new technologies that could be used in the future. Both single‐device and two‐device systems are considered. In particular, the expected annual direct cost of using these devices for 100% checked baggage screening under various scenarios is obtained and the tradeoffs between using single‐ and two‐device strategies are studied. The expected number of successful threats under the different checked baggage screening scenarios with 100% checked baggage screening is also obtained. Lastly, a risk‐based screening strategy proposed in the literature is analyzed. The results reported suggest that for the existing security setup, with current device costs and probability parameters, single‐device systems are less costly and have fewer expected number of successful threats than two‐device systems due to the way the second device affects the alarm or clear decision. The risk‐based approach is found to have the potential to significantly improve security. The cost model introduced provides an effective tool for the execution of cost‐benefit analyses of alternative device configurations for aviation‐checked baggage security screening.

This paper analyses checked baggage screening strategies that incorporate the effects of deterrence on explosive detection systems (EDSs) deployed at airports. Cost models for these strategies are presented that incorporate the cost of purchasing, operating, and maintaining an EDS, the number of checked bags available to be screened, and the numbers of selectees and non-selectees checked bags actually screened over a one-year period. The model also includes the effect of deterrence on the level of threat at an airport. The cost models provide a quantitative tool to assess the strategy of 100% screening of all checked bags, as set forth by the USA Aviation and Transportation Security Act. Comparing the expected direct cost per expected prevented attack to the expected cost of an aviation terrorist incident provides an indication of the cost effectiveness of 100% checked bag screening.

Aviation security is an important problem of national interest and concern. Baggage screening security devices and operations at airports throughout the United States provide an important defense against terrorist actions targeted at commercial aircraft. Determining where to deploy such devices, and how to best use them can be quite challenging. This paper presents NP-complete decision problems concerning the deployment and utilization of baggage screening security devices. These problems incorporate three different deployment performance measures: uncovered baggage segments, uncovered flight segments, and uncovered passenger segments. Integer programming models are formulated to address optimization versions of these problems and to identify optimal baggage screening security device deployments (i.e., determine the number and type of baggage screening security devices that should be placed at different airports, and determining which baggage should be screened with such devices). The models are illustrated with an example that incorporates data extracted from the Official Airline Guide (OAG).

In the aftermath of the tragic events of 11 September 2001, numerous changes have been made to aviation security policy and operations throughout the nation's airports. The allocation and utilization of checked baggage screening devices is a critical component in aviation security systems. This paper formulates problems that model multiple sets of flights originating from multiple stations (e.g., airports, terminals), where the objective is to optimize a baggage screening performance measure subject to a finite amount of resources. These measures include uncovered flight segments (UFS) and uncovered passenger segments (UPS). Three types of multiple station security problems are identified and their computational complexity is established. The problems are illustrated on two examples that use data extracted from the Official Airline Guide. The examples indicate that the problems can provide widely varying solutions based on the type of performance measure used and the restrictions imposed by the security device allocations. Moreover, the examples suggest that the allocations based on the UFS measure also provide reasonable solutions with respect to the UPS measure; however, the reverse may not be the case. This suggests that the UFS measure may provide more robust screening device allocations. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2005.