Showing papers on "Fleet management published in 2006"
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TL;DR: This paper addresses the issue of how to exploit information about future events to improve decision making in a real-time setting with a strategy based on probabilistic knowledge about future request arrivals to better manage the fleet of vehicles.
Abstract: An important, but seldom investigated, issue in the field of dynamic vehicle routing and dispatching is how to exploit information about future events to improve decision making. In this paper, we address this issue in a real-time setting with a strategy based on probabilistic knowledge about future request arrivals to better manage the fleet of vehicles. More precisely, the new strategy introduces dummy customers (representing forecasted requests) in vehicle routes to provide a good coverage of the territory. This strategy is assessed through computational experiments performed in a simulated environment.
209 citations
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TL;DR: A probabilistic model is proposed that requires only the knowledge of the distribution of the demand over the service area and the quality of the service in terms of time windows associated of pickup and delivery nodes to be used.
Abstract: We study the problem of determining the number of vehicles needed to provide a demand responsive transit service with a predetermined quality for the user in terms of waiting time at the stops and maximum allowed detour. We propose a probabilistic model that requires only the knowledge of the distribution of the demand over the service area and the quality of the service in terms of time windows associated of pickup and delivery nodes. This methodology can be much more effective and straightforward compared to a simulation approach whenever detailed data on demand patterns are not available. Computational results under a fairly broad range of test problems show that our model can provide an estimation of the required size of the fleet in several different scenarios.
109 citations
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TL;DR: In this article, a deterministic dynamic program (DP) was proposed to solve the multiple-vehicle routing problem with split pick-ups (mVRPSP), where any supplier may be visited by more than one pickup.
Abstract: We consider a multiple-vehicle routing problem with split pick-ups (mVRPSP). This problem involves multiple suppliers, a single depot, and a fleet of identical capacity trucks responsible for delivering supplies from the suppliers to the depot. Any supplier may be visited by more than one truck, thus allowing split pick-ups. The problem is to determine, for each truck, which suppliers to visit and the size of loads to pick up so as to minimize the total transportation cost for the fleet, which depends on the number of trucks used and their routes. We develop a fundamentally new model for the mVRPSP, a deterministic dynamic program (DP). Although the most natural DP formulation results in a DP with uncountably-infinite state and action spaces, an optimality-invariance condition we establish leads to an equivalent DP with finite state and action spaces. This DP formulation leads to a new exact algorithm for solving the mVRPSP, based on a shortest path search algorithm, which is conceptually simple and easy to implement.
109 citations
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TL;DR: In this paper, a stochastic-demand scheduling model is proposed for inter-city bus operations in Taiwan, which incorporates the variations in daily passenger demand in actual operations to improve the performance of the proposed model.
Abstract: Vehicle fleet routing and timetable setting are essential to the enhancement of an inter-city bus carrier’s operating cost, profit, level of service and competitiveness in the market. In past research the average passenger demand has usually served as input in the production of the final fleet routes and timetables, meaning that stochastic disturbances arising from variations in daily passenger demand in actual operations are neglected. To incorporate the stochastic disturbances of daily passenger demands that occur in actual operations, in this research, we established a stochastic-demand scheduling model. We applied a simulation technique, coupled with link-based and path-based routing strategies, to develop two heuristic algorithms to solve the model. To evaluate the performance of the proposed model and the two solution algorithms, we developed an evaluation method. The test results, regarding a major Taiwan inter-city bus operation, were good, showing that the model and the solution algorithms could be useful in practice.
91 citations
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TL;DR: The results indicate that the proposed approach can significantly improve efficiency in the car rental business and under consideration of essential practical needs such as multi-period planning, a country-wide network, customized transportation relations, fleeting and defleeting, and car groups with partial substitutability.
Abstract: Logistics management in the car rental business involves short-term decisions about the transportation and deployment of cars with regard to optimizing fleet utilization while maintaining a high service level. We model and solve this problem by means of minimum cost network flow optimization under consideration of essential practical needs such as multi-period planning, a country-wide network, customized transportation relations, fleeting and defleeting, and car groups with partial substitutability. Experiments were conducted on substantial real-world data, using a simulation model to assess optimization results for different scenarios. The results indicate that the proposed approach can significantly improve efficiency.
89 citations
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TL;DR: In this paper, Caramia et al. presented the results of adapting this algorithm to the dynamic pickup and delivery vehicle routing problem with several time windows, where waiting times of vehicles are admitted.
Abstract: In 2001, Caramia and his coauthors introduced a very fast and efficient heuristic for rooting a fleet of vehicles for dynamic combined pickup and delivery services [Caramia, M., Italiano, G.F., Oriolo, G., Pacifici, A., Perugia, A., 2001. Routing a fleet of vehicles for dynamic combined pickup and delivery services. In: Proceedings of the Symposium on Operation Research 2001, Springer-Verlag, Berlin/Heidelberg, pp. 3–8.]. The authors assume that every client names a stretch-factor that denotes the maximal relative deviation from the shortest path between pickup and delivery point. Waiting times are not allowed. As these assumptions are not very realistic, this paper now presents the results of adapting this algorithm to the dynamic pickup and delivery vehicle routing problem with several time windows. Waiting times of vehicles are admitted. Moreover, the computational results are considerably improved by local search techniques making use of free computational capacity.
89 citations
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14 Sep 2006TL;DR: In this article, a fleet management system for remotely monitoring a vehicle is disclosed in one embodiment, which includes a data receiver and a display, which is configured to wirelessly receive information from the vehicle.
Abstract: A fleet management system for remotely monitoring a vehicle is disclosed in one embodiment. The fleet management system includes a data receiver and a display. The data receiver is configured to wirelessly receive information from the vehicle. That information includes a location for the vehicle. The display is configured to present a planned route configured for the vehicle before travel and a driven route of the vehicle. The driven route is determined from the information from the vehicle. The planned route and driven route are displayed simultaneously.
78 citations
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13 Jun 2006TL;DR: Construction Equipment Management for Engineers, Estimators, and Construction Managers, Second Edition has been extensively rewritten to not only bring it up to date with the state of current practice, but also to serve as a textbook for university courses in construction engineering and management.
Abstract: Construction Equipment Management for Engineers, Estimators, and Construction Managers, Second Edition has been extensively rewritten to not only bring it up to date with the state of current practice, but also to serve as a textbook for university courses in construction engineering and management.
The authors advanced the previous edition’s practical, hands-on approach and added material on the future of construction equipment fleet management, which they believe will require a new technology-based skillset to maximize the cost-effectiveness of construction equipment operations. As such, the book covers the latest construction equipment technologies.
Features:
Examines emergent technologies in the field, including automated machine guidance systems, intelligent compaction operations, and equipment-related civil integrated management tools.
Provides information on how to reduce an equipment fleet’s environmental impact, decreasing greenhouse gas emissions through enhanced equipment management and optimization practices.
Discusses estimating equipment ownership, operating costs, economic life and optimal replacement timing.
Demonstrates how to maximize profit by determining the optimum equipment mix and estimating productivity.
Illustrates the use of production-based linear scheduling and stochastic simulations to maximize project cost and schedule certainty.
This new edition will serve as an essential textbook for students as well as a valuable reference for a wide range of professionals within the construction, architecture, and engineering industries.
73 citations
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23 Jan 2006TL;DR: In this article, a performance indicator is calculated using data elements associated with at least two of the three data sets and an actionable metric is reported, based upon the performance indicator.
Abstract: Monitoring an actionable metric associated with a fleet is disclosed. A first data set is received that includes fleet management data for the fleet. A second data set is received that includes field service data associated with the fleet. A third data set is received that includes vehicle diagnostic data and/or vehicle positioning data. A performance indicator is calculated using data elements associated with at least two of the three data sets. An actionable metric is reported, based upon the performance indicator.
70 citations
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TL;DR: The proposed solution approach is based on the decomposition of this problem in three simpler sub-problems associated to each of the costs considered above, which will help solve the fleet management problem in container trucking industry.
60 citations
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TL;DR: In this article, a three-step local search algorithm based on a probabilistic variable neighborhood search is presented for the vehicle routing problem with a heterogeneous fleet of vehicles and soft time windows (VRPHESTW).
Abstract: A three-step local search algorithm based on a probabilistic variable neighborhood search is presented for the vehicle routing problem with a heterogeneous fleet of vehicles and soft time windows (VRPHESTW). A generation mechanism based on a greedy randomized adaptive search procedure, a diversification procedure using an extinctive selection evolution strategy, and a postoptimization method based on a threshold algorithm with restarts are considered to solve the problem. The results show the convenience of using an economic objective function to analyze the influence of the changes in the economic environment on the transportation average profit of vehicle routing problems. Near real-world vehicle routing problems need (1) an economic objective function to measure the quality of the solutions as well as (2) an appropriate guide function, which may be different from the economic objective function, for each heuristic method and for each economic scenario.
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24 Jul 2006
TL;DR: In this paper, a discrete event simulation can be applied to assess the first order requirements for integrated vehicle health management (IVHM) implementation on systems and an example of a performance improvement illustrated from a simulation run using notional system and scenario data.
Abstract: Support requirements and health management are significant operational drivers on large military weapons systems and large commercial aircraft. The integration of health management into the up-front design of these systems should include a detailed benefit analysis that includes all of the benefactors of operational performance that a truly integrated health management system can bring. These benefactors are the Original Equipment Manufacturers (OEMs), the mission operators, command/control elements, fleet management, and maintenance operations. Each of these functional areas has unique processes that can be identified and measured. The performance improvement on a system can be evaluated before design dollars are ever committed or contracts signed. By identifying the processes, measures of effectiveness (MOE), and input drivers, a discrete event simulation can be applied to assess the first order requirements for Integrated Vehicle Health Management (IVHM) implementation on systems. Some of the basic input approaches are discussed, as well as an example of a performance improvement illustrated from a simulation run using notional system and scenario data. This type of analysis enables a larger business case to be developed to aid designers and planners in their decisions of how to implement IVHM. This paper describes some of the initial approaches to modeling the above problems as part of the on going effort to develop a simulation to assess IVHM.
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03 Dec 2006TL;DR: This paper presents an innovative methodology that combines simulation, data mining, and knowledge-based techniques to determine the near- and long-term impacts of candidate aircraft engine maintenance decisions, particularly in terms of life-cycle cost and operational availability.
Abstract: This paper presents an innovative methodology that combines simulation, data mining, and knowledge-based techniques to determine the near- and long-term impacts of candidate aircraft engine maintenance decisions, particularly in terms of life-cycle cost (LCC) and operational availability. Simulation output is subjected to data mining analysis to understand system behavior in terms of subsystem interactions and the factors influencing life-cycle metrics. The insights obtained through this exercise are then encapsulated as policies and guidelines supporting better life-cycle asset ownership decision-making.
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TL;DR: An exact mixed-integer linear programming model, as well as a heuristic solution approach based on mathematical programming, are presented that produces realistic solutions arising from a trade-off between profits and homogeneity and solves large-scale instances in short times with very small optimality gaps.
Abstract: Given the flight schedule of an airline, the fleet assignment problem consists of determining the aircraft type to assign to each flight leg in order to maximize the total expected profits while satisfying aircraft routing and availability constraints. The profit for a leg is a function of the leg’s stochastic passenger demand, the capacity of the aircraft assigned to the leg, and the aircraft operational costs. This paper considers the weekly fleet assignment problem in the case where homogeneity of aircraft type is sought over legs sharing the same flight number. Homogeneity allows, among other things, easier ground service planning. An exact mixed-integer linear programming model, as well as a heuristic solution approach based on mathematical programming, are presented. Computational results obtained on Air Canada instances involving up to 4400 flight legs are reported. The system produces realistic solutions arising from a trade-off between profits and homogeneity, and solves large-scale instances in short times with very small optimality gaps.
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TL;DR: An enumeration algorithm based on dynamic programming for optimally solving the fleet management problem in underground mines, that takes into account the displacement modes of the vehicles and makes sure that these vehicles move forward when they arrive at their service point.
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TL;DR: In this paper, the authors present a case analysis of a car rental company in the US state of Florida, showing that the hierarchical nature of the decision process of fleet management at car rental companies can be exploited to maximize yield by matching capacity to current and projected demand.
Abstract: Fleet management at car rental companies aims to maximise yield by matching capacity to current and projected demand. This is accomplished via three decision-making phases. The first phase involves the grouping of car rental locations into pools, allowing car rental locations within a pool to share a fleet of vehicles. In the second phase, the types and quantities of vehicles to be acquired and returned to the car manufacturer and the geographical redistribution of vehicles among pools over the long-term planning horizon are defined for each pool. The final phase involves the daily operations in which the deployment of the fleet within each pool among its locations is defined. In this paper, we address all three phases as we encountered them in a major US car rental company. We develop appropriate solution methodologies for all three phases taking into account the hierarchical nature of the decision process. Finally, the application of the entire methodology is exhibited via a case analysis for the state of Florida.
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TL;DR: In this paper, a heuristic for yield management over two flights with swappable aircraft is proposed, where the swap decision depends on demand realization on the two flights and is made at a predetermined time prior to departure.
Abstract: As a practical form of demand driven dispatch at some major airlines in North America, cockpit compatible aircraft of different capacities are paired in the fleet assignment for a possible future swap on the two involved flights. They are paired in such a way that the swap does not affect their aircraft routings on other legs. The swap decision depends on demand realization on the two flights and is made at a predetermined time prior to departure. Yield management on the two flights is studied in this paper. We begin by studying a base problem in which at a certain time before departure, the assignment on a flight is subject to change with a fixed probability. The base problem extends the threshold policy into the case where future capacity is uncertain. Secondly, we propose a heuristic for yield management over two flights with swappable aircraft by repeatedly updating the swap probability as demand unfolds. Our numerical result shows that this policy significantly enhances the airline’s capability to increase revenue under demand driven dispatch. In addition, the base problem may shed lights on derivation of optimal yield management policy in irregular operational settings where final capacity assignment is independent of yield management policy.
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TL;DR: This paper presents a preemptive goal programming model for multi-objective cross-border logistics problem, in which three objectives are optimized hierarchically and described a framework for incorporating decision-makers' opinions for determination of goal priorities and target values.
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09 Oct 2006
TL;DR: An algorithm based on queuing theory is proposed for dynamic fleet management of cybercars, which can respond to random requests, and demonstrated the effectiveness of the proposed algorithm.
Abstract: One of the major issues in intelligent transportation system (ITS) is fleet management. This paper proposed a dynamic fleet management algorithm for cybercars, which are road vehicles with fully automated capabilities. A fleet of such vehicles forms a transportation system called CTS (cybernetic transportation system), for passengers or goods. This paper presented an architecture for CTS' operation and fleet management. An algorithm based on queuing theory is proposed for dynamic fleet management of cybercars, which can respond to random requests. Simulation experiments demonstrated the effectiveness of the proposed algorithm
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TL;DR: A stochastic model for the dynamic fleet management problem with random travel times is presented and it is shown how to approximate the value function in a tractable manner under this new high-dimensional state variable.
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TL;DR: In this paper, the authors applied an objective and probabilistic method to a vehicle dataset collected by the DuPage County Forest Preserve District ((DCFPD), in the state of Illinois.
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TL;DR: In this paper, the authors discuss the design and development of regional truckload delivery fleets in support of random over-the-road delivery networks of continental scale and present a detailed set of simulation models to evaluate various possible configurations of regional driving fleets.
Abstract: In this paper, the authors discuss the design and development of regional truckload delivery fleets in support of random over-the-road delivery networks of continental scale. A detailed set of simulation models are developed to evaluate various possible configurations of regional driving fleets. The results of experimentation with these models are presented. The paper includes a discussion of various factors of interest in designing regional fleets and ultimately evaluates and recommends several possible fleet configurations in North America.
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IBM1
TL;DR: The optimization component of a decision support system developed for a sedan service provider is presented, which assists supervisors and dispatchers in scheduling driver shifts and routing the fleet throughout the day to satisfy customer demands within tight time windows.
Abstract: We present the optimization component of a decision support system developed for a sedan service provider. The system assists supervisors and dispatchers in scheduling driver shifts and routing the fleet throughout the day to satisfy customer demands within tight time windows. We periodically take a snapshot of the dynamic data and formulate an integer program, which we solve to near optimality using column generation. Although the data snapshot is stale by the time a solution is computed, we are able to solve the integer program quickly enough that the solution can be adopted after minor modifications are made by a fast local-search heuristic. The system described in this paper is currently in use and has improved the provider's productivity significantly.
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01 Jan 2006
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05 Jun 2006
TL;DR: This work proposes patterns to re-express requirements-based service queries using classes of solution service, to increase the likelihood of discovering relevant services from service registries.
Abstract: Developing service-centric applications will require developers to discover candidate services during requirements processes. However such discovery is challenging due to the ontological mismatch between requirement and service descriptions. We propose patterns to re-express requirements-based service queries using classes of solution service, to increase the likelihood of discovering relevant services from service registries. We report a prototype pattern language developed for service-based vehicle fleet management, and demonstrate its use with an example.
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01 Sep 2006TL;DR: This paper describes how the already developed fleet management and remote sensing technologies can be merged together to form an efficient disaster management system.
Abstract: Organizations and individuals have been facing disasters globally and locally since hundreds of years. Increasing number of natural disasters has demonstrated the paramount importance of the natural hazards subject for the protection of environment and the citizens. Now more than ever, designing an efficient traffic system, moving vast amounts of helping goods quickly and safely across great distances is one of our most pressing needs. Satellite navigation systems are changing the way in which we travel from place to place whether by land, sea or air and whether in remote areas or through congested city streets. Global positioning system (GPS) and its role in advanced transportation projects is inseparable and become a synonym. The management and operations of vehicles and giving real-time information to users that will lead to cost-effective and satisfied service to passengers is possible nowadays using a GPS based vehicle navigation system and communication via remote sensing. This paper describes how the already developed fleet management and remote sensing technologies can be merged together to form an efficient disaster management system.
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01 Jan 2006TL;DR: Prognosis-based asset management can go a long way towards reversing the operating cost trend of the United States Air Force, Navy and Army aircraft fleet as mentioned in this paper, which will allow the services to reach cost of ownership entitlement as well as achieve significant safety and readiness improvements.
Abstract: A serious operational cost trend threatens the future technical preeminence of the United States DoD. Increasing readiness costs are severely impacting acquisition of new aircraft, which translates to an increase in the average age of the United States Air Force, Navy and Army aircraft fleet. As time marches on, this undesirable trend will become more and more difficult to overcome. It would be unwise to expect congress to increase the defense budget in the near future to overcome this dilemma. Hence, as the current aircraft fleets continue to age this problem will only get worse. A revolutionary paradigm shift must take place to reverse the aircraft sustainment demand for funding. Prognosis based asset management can go a long way towards reversing the operating cost trend. When applied to aircraft engines, prognosis based asset management may allow the services to reach cost of ownership entitlement as well as achieve significant safety and readiness improvements. This revolutionary change in engine management will employ condition (or state) based component lifing and inspections (verses the current hard time inspections limits). Instead of operating to fixed intervals, based on engine health, the component will dictate when the optimal inspection should occur. In other words, a sensor will determine when the engine needs to be inspected. This includes all nondestructive evaluation, borescope activities, component replacement and depot maintenance work. The concept of engine health management (EHM) has been an interesting topic for several years. The Navy explored prognosis and mechanical diagnostics in the early 70’s for the F-8 and A-7 applications (1). Various limitations such as engine controller, storage, limited computing capacity / capabilities have prevented this from moving forward. Significant advances in both computing power and sensor technology now make it possible to obtain real time engine information and to make EHM a reality on an engine-by-engine basis. Obtaining flight-by-flight usage parameter information will provide the foundation for robust diagnostics as well as engine prognostics and allow real time fault tree analysis and near real time damage accumulation calculations. Once this information is available, engine prognosis can provide predictive capability for the health of engine components, appropriate inspection intervals and maintenance activities providing a substantial long-range cost avoidance opportunity for the DoD sustainment budget. Current fleet management capability is constrained by uncertainty in the current state of the individual aircraft engines. The ability to sense or measure the damage state of an individual part is limited at best. Further, specific part operational severity is not captured with the current lifing process, hence many components are not operating to their life entitlement because the life is based on fleet weighted average missions. Unlike the fixed interval inspections currently being performed, precise assessment is required for condition-based lifing. The key considerations in this new assessment process are 1) the fidelity of the analysis tools and 2) the definition of the boundary conditions (or environmental conditions used by the analysis tools) 3) improved understanding of diagnostics and engine faults and a better troubleshooting tool.Copyright © 2006 by ASME
01 Jan 2006
TL;DR: In this paper, the authors describe a way to determine heavy vehicle suspension dynamics using an on-board mass measurement system and describe two low cost testing methods to determine shock absorber health.
Abstract: The purpose of this paper is to describe a way to determine heavy vehicle suspension dynamics using an on-board mass measurement system. This paper expands on previous work by the authors and describes two low cost testing methods to determine shock absorber health using an on-board mass measurement system. These tests involved the simple processes of driving over a 48 mm pipe and driving the vehicle over normal, uneven roads. The two measurements used to show that heavy vehicle suspensions are road friendly are the damping ratio and the damped free vibration frequency. On-board mass measurement systems are increasingly prevalent on the heavy vehicle fleet but their use is primarily for fleet management purposes or jurisdictional monitoring. More value could be derived from on-board mass measurement systems by using them to determine the health of road-friendly suspensions. This might be achieved without the expense and inconvenience of taking the truck off the road for testing. By the use of a few simple analytical tools, transport operators and fleet managers have an opportunity to monitor the health status of heavy vehicle suspensions.
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IBM1
TL;DR: In this article, the concept of metrology tool fleet management is presented and a comprehensive discussion of requirements and solutions concerning the metrology tools fleet management concept will launch efforts in coordinating the comprehensive solutions needed between suppliers and tool owners, and some recommendations are made regarding long term solutions to needs with respect to integrating fleet management into manufacturing fab systems.
Abstract: Managing a fleet of metrology tools is becoming an extremely daunting task. This is especially so in manufacturing lines where it is not unusual to have many tools in the fleet and a very large mix of product and technologies. It is this large mix of product and technologies which pushes the number of recipes created into the thousands. Combine the large number of recipes with a poorly calibrated, monitoring and managed fleet of tools and productivity can be negatively impacted many ways. In this paper, these productivity detractors are explained in more detail to help understand the numerous ways a fleet of metrology tools can negatively impact the productivity of the manufacturing and development lines. In the pursuit of reducing metrology tool induced productivity detractors, the concept of metrology tool fleet management is presented. Categories of fleet management are also introduced along with a comprehensive discussion of requirements. It is hoped that this discussion of requirements and solutions concerning the metrology tool fleet management concept will launch efforts in coordinating the comprehensive solutions needed between suppliers and tool owners. Some recommendations are made regarding long term solutions to needs with respect to integrating fleet management into manufacturing fab systems.