Systems analysis for planning of air fleets and maintenance facilities

The high cost and extraordinary demands made on sophisticated air defence systems, pose hard challenges to the managers and engineers who plan the operation and maintenance of such systems. This paper presents a study aimed at developing simulation and systems analysis techniques for the effective planning and efficient operation of small fleets of aircraft, typical of the air force of a developing country. We consider an important aspect of fleet management: the problem of resource allocation for achieving prescribed operational effectiveness of the fleet. At this stage, we consider a single flying-base, where the operationally ready aircraft are stationed, and a repair-depot, where the planes are overhauled. An important measure of operational effectiveness is ‘ availability ’, which may be defined as the expected fraction of the fleet fit for use at a given instant. The tour of aircraft in a flying-base, repair-depot system through a cycle of ‘ operationally ready ’ and ‘ scheduled overhaul ’ phases is represented first by a deterministic flow process and then by a cyclic queuing process. Initially the steady-state availability at the flying-base is computed under the assumptions of Poisson arrivals, exponential service times and an equivalent singleserver repair-depot. This analysis also brings out the effect of fleet size on availability. It defines a ‘ small ’ fleet essentially in terms of the important ‘ traffic ’ parameter of service rate/maximum arrival rate.A simulation model of the system has been developed using GPSS to study sensitivity to distributional assumptions, to validate the principal assumptions of the analytical model such as the single-server assumption and to obtain confidence intervals for the statistical parameters of interest.

A GIS (geographical information system)-based spatial data mining approach for optimal location and capacity planning of distributed biomass power generation facilities: A case study of Tumkur district, India

This paper primarily intends to develop a GIS (geographical information system)-based data mining approach for optimally selecting the locations and determining installed capacities for setting up distributed biomass power generation systems in the context of decentralized energy planning for rural regions. The optimal locations within a cluster of villages are obtained by matching the installed capacity needed with the demand for power, minimizing the cost of transportation of biomass from dispersed sources to power generation system, and cost of distribution of electricity from the power generation system to demand centers or villages. The methodology was validated by using it for developing an optimal plan for implementing distributed biomass-based power systems for meeting the rural electricity needs of Tumkur district in India consisting of 2700 villages. The approach uses a k-medoid clustering algorithm to divide the total region into clusters of villages and locate biomass power generation systems at the medoids. The optimal value of k is determined iteratively by running the algorithm for the entire search space for different values of k along with demand-supply matching constraints. The optimal value of the k is chosen such that it minimizes the total cost of system installation, costs of transportation of biomass, and transmission and distribution. A smaller region, consisting of 293 villages was selected to study the sensitivity of the results to varying demand and supply parameters. The results of clustering are represented on a GIS map for the region.