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Looks at the use of the JOBSCOPE software system by a company involved in the design of systems used in the manufacture of jet engines and aircraft landing gear. Notes the advantages of the system relating to its manufacturing and financial packages and reports on the training programme available for companies choosing to install the system.

Despite continual and growing concerns over the productivity and even the long‐term survival of the UK’s manufacturing industry, it is worth recognising that there still seems to be a strength when it comes to engineering innovation and excellence. A factor yet again highlighted by the broad scope of the finalists for the 2001 MacRobert Award. Initiated in 1969, the Award, Britain’s most prestigious annual prize for engineering, recognises projects that demonstrate the successful development of innovative and ground‐breaking ideas in engineering.

Traditional procedures in flat pattern design of aircraft sheet metal parts are generally based on technicians' personal idea and experiences which can cause unwanted inconsistency and errors. The main objective of this paper is to present an automated system for decreasing the time and increasing the accuracy in providing templates used in aircraft sheet metal parts manufacturing.

The paper discusses the software (Developer) which is able to receive 2D drawing of a part and create the flat pattern template after applying the necessary changes. The system is also capable of supplying other components of sheet metal part template such as support, tooling hole, and lightening hole. AutoLISP has been used as a tool for internal access to a commercial software such as AutoCAD. An interface has been written by Visual Basic for Application (VBA) to enable the user easily to apply the subroutines related to the software system.

Several algorithms have been developed and the necessary subroutines have been written in an integrated user‐friendly package. To clarify the process and its application, an application example is demonstrated.

The paper can provide automatically components that are not originally provided in other commercial software. It also has the ability to calculate spring‐back and provide unfold drawing. The known standard templates can also be created.

The purpose of this paper is to present the application of the neural-based estimation method, Neural-Gauss-Newton (NGN), using the real flight data of a small unmanned aerial vehicle (UAV).

The UAVs in general are lighter in weight and their flight is usually influenced by the atmospheric winds because of their relatively lower cruise speeds. During the presence of the atmospheric winds, the aerodynamic forces and moments get modified significantly and the accurate mathematical modelling of the same is highly challenging. This modelling inaccuracy during parameter estimation is routinely treated as the process noise. Furthermore, because of the limited dimensions of the small UAVs, the measurements are usually influenced by the disturbances caused by other subsystems. To handle these measurement and process noises, the estimation methods based on neural networks have been found reliable in the manned aircrafts.

Six sets of compatible longitudinal flight data of the designed UAV have been chosen to estimate the parameters using the NGN method. The consistency in the estimates is verified from the obtained mean and the standard deviation and the same has been validated by the proof-of-match exercise. It is evident from the results that the NGN method was able to perform on a par with the conventional maximum likelihood method.

This is a partial outcome of the research carried out in estimating parameters from the UAVs.