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Unless the U.S. commercial aircraft fleet is maintained with high reliability, we cannot be assured of flight safety with an ageing fleet. Maintenance depends upon inspection to be effective, thus the reliability of aircraft inspection is of paramount importance to safety. To provide baseline data on the current inspection activities of commercial aircraft, a task analysis of inspection by commercial carriers was undertaken as part of the Federal Aviation Administration's National Ageing Aircraft Research Program (NAARP). This paper describes the Task Analysis methodology developed, typical results, and some human-system mismatches detected.

Milling is one of the most widely used metal removal processes. The number of decision parameters involved in the milling operation makes the experimental estimation of tool life equations very difficult. Optimal metal removal rate has been modelledindependently of the cutter path selectedfor the operation. However,the choosing of the proper cutter path might significantly reduce the total tool travel and thereforealso reduce the tool wear due to the reduction in the tool engagement with the job.With the widespread application of robotics in industry, robots are also being used to automate the grinding process. Robotized grinding of flat polygonal surfacesis one such application where the tool path is similar to facemillingof like surfaces. Thus optimizing the total tool path during NC face milling/robotized grinding remains an important problem.A mathematical model representing the total tool path on an N -sided convex polygonal surface has been developed. The stair-case type of tool path has been considered. The resulting formulation is complex and cannot be solved using standard analytic or numeric methods. An algorithm has been proposed to find an optimal solution using the above model, by enumerating over tool sweep angles between0°and 180°. This algorithm can be easilycoded and run on a PC, Finally a detailed example is given explaining the application of this algorithm. IntroductionMilling is one of the most widely used metal removal processes. The number of decision parameters involved in the milling operation makes the experimental estimation of tool life equations very difficult. Milling is an intermittent cutting operation. The rate of wear of milling tools may run from four to fifty times higher than the rate that one might expect in a continuous cutting operation like turning. The wear in milling is primarily dominated by the speed. However several other factors also influence the endurance of milling cutters. Adequate combinations of exit and entry angles of the tool also influence tool wear (Lat et al. 1978). Mathematical models for milling process optimization have been developed by many people (Yellowley et al. 1978). However these models cannot be generalized but are limited to specific applications. Chang et al. (1982) have developed a model that identifies four primary control variables such as cutter traverse rate, depth of cut, spindle rotation speed, cutter diameter and number of teeth.Though the optimal metal removal rate has been modelled independently of the cutter path selected for the operation, the choosing of the proper cutter path might significantly reduce the total tool travel and in consequence also reduce the tool wear

Airworthiness of the civil fleet is dependent upon the ability of inspectors to identify conditions for repair. As this is primarily a visual activity, the issue of training for visual inspection is critical. The inspection training literature has little detailed advice in this area, so in response to this need, a series of simulator experiments was undertaken for the development of improved training programs. This article briefly reviews each experiment and summarizes the results. Key conclusions drawn from each experiment are then used to demonstrate how they can be applied to enhance training for inspection tasks. © 1997 John Wiley & Sons, Inc.

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