Discrepancies of materials, tools, and factory environments, as well as human intervention, make variation an integral part of the manufacturing process of any component. In particular, the assembly of large volume, aerospace parts is an area where significant levels of form and dimensional variation are encountered. Corrective actions can usually be taken to reduce the defects, when the sources and levels of variation are known. For the unknown dimensional and form variations, a tolerancing strategy is typically put in place in order to minimize the effects of production inconsistencies related to geometric dimensions. This generates a challenging problem for the automation of the corresponding manufacturing and assembly processes. Metrology is becoming a major contributor to being able to predict, in real time, the automated assembly problems related to the dimensional variation of parts and assemblies. This is done by continuously measuring dimensions and coordinate points, focusing on the product's key characteristics. In this paper, a number of metrology focused activities for large-volume aerospace products, including their implementation and application in the automation of manufacturing and assembly processes, are reviewed. This is done by using a case study approach within the assembly of large-volume aircraft wing structures.

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This paper shows how the angular uncertainties can be determined for a rotary-laser automatic theodolite of the type used in (indoor-GPS) iGPS networks. Initially, the fundamental physics of the rotating head device is used to propagate uncertainties using Monte Carlo simulation. This theoretical element of the study shows how the angular uncertainty is affected by internal parameters, the actual values of which are estimated. Experiments are then carried out to determine the actual uncertainty in the azimuth angle. Results are presented that show that uncertainty decreases with sampling duration. Other significant findings are that uncertainty is relatively constant throughout the working volume and that the uncertainty value is not dependent on the size of the reference angle.

Key characteristics (KCs) play a significant role in product lifecycle management (PLM) and in collaborative and global product development. Over the last decade, KCs methodologies and tools have been studied and practiced in several domains of the product lifecycle, and many world-class companies have introduced KCs considerations into their product development practices. However, there has been no systematic survey of KCs techniques, methodologies, and practices in this respect. This paper aims to give a comprehensive survey of KCs methodologies, and practices from the perspective of enterprise integration and PLM. The paper firstly presents a holistic framework of KCs methodologies and practices through the product lifecycle, and summarizes the fundamentals of KCs including their definition and classification, KC flowdown, and the identification and selection of KCs. A review of the KCs methods and practices in the product lifecycle is then presented, particularly in engineering design, manufacturing planning, production and testing as well as information and knowledge management respectively. Finally, the problems and challenges for future research on KCs techniques are discussed.

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