Task Specific Uncertainty in Coordinate Measurement

Task specific uncertainty is the measurement uncertainty associated with the measurement of a specific feature using a specific measurement plan. This paper surveys techniques developed to model and estimate task specific uncertainty for coordinate measuring systems, primarily coordinate measuring machines using contacting probes. Sources of uncertainty are also reviewed

Inference on errors in industrial parts: Kriging and variogram versus geometrical product specifications standard

This article focuses on the inference on the errors in manufactured parts controlled by using measurements devices. The characterization of the part surface topographies is core in several applications. A broad set of properties (tribological, optical, biological, mechanical, etc.) depends on the micro- and macrogeometry of the parts. Moreover, parts usually show typical deterministic geometric deviation pattern, referred to as manufacturing signatures, due to the specific manufacturing processes and process setup parameters adopted for their production. In several situations, the measurements may also be affected by systematic errors due to the measurement process, that might be caused, for example, by a poor part alignment during the measurement process. Measurement techniques and characterization methods have been standardized in the International Standard ISO 25178, defining parameters characterizing the surface topography and supplying methods and formula adapt to deal with this issue computationally. In the present article, we consider a type of spatial dependence between measured values at different points that suggest the use of the variogram to identify patterns in the parts. We offer a comparison, based on a real set of measures, between the latter approach and the conventional as a test of the efficient performance of our findings

Quality and inspection of machining operations: Review of condition monitoring and CMM inspection techniques 2000 to present

In order to consistently produce quality parts, many aspects of the manufacturing process must be carefully monitored, controlled, and measured. The methods and techniques by which to accomplish these tasks has been the focus of numerous studies in recent years. With the rapid advances in computing technology, the complexity and overhead that can be feasibly incorporated in any developed technique has dramatically improved. Thus, techniques that would have been impractical for implementation just a few years ago can now be realistically applied. This rapid growth has resulted in a wealth of new capabilities for improving part and process quality and reliability. In this paper, overviews of recent advances that apply to machining are presented. Moreover, due to the relative significance of two particular machining aspects, this review focuses specifically on research publications pertaining to using tool condition monitoring and coordinate measurement machines to improve the machining process. Tool condition has a direct effect on part quality and is discussed first. The application of tool condition monitoring as it applies to turning, drilling, milling, and grinding is presented. The subsequent section provides recommendations for future research opportunities. The ensuing section focuses on the use of coordinate measuring machines in conjunction with machining and is subdivided with respect to integration with machining tools, inspection planning and efficiency, advanced controller feedback, machine error compensation, and on-line tool calibration, in that specific order and concludes with recommendations regarding where future needs remain

Manufacturing and characterization of similar to foam steel components processed through selective laser melting

The growing interest from the industry for lightweight metal components has driven the development of processes that would allow creating lightweight high melting point metals as steels, able to guarantee mechanical characteristics superior to existing foam (typically aluminium), without penalizing one of the characteristics that cell structures have: lightness. Conventional manufacturing methods, such as casting, however, face difficulty in making complex periodic steel structures with designed shape and size and volume fraction. This study evaluates the manufacturability and performance of lightweight 17–4 PH steel components with spherical porosity fabricated via selective laser melting (SLM). Samples were designed and fabricated with the purpose to produce a structure similar to foam. Built samples were characterized in terms of dimensional accuracy, mechanical strength under compression and energy absorbed per unit mass. The designed structures have a designed relative density or volume fraction ranging between 31.1 and 32.8%

Race-track modelling and variability in RTM for advanced composites structures

The Resin Transfer Moulding (RTM) process is one of the most common manufacturing routes for composites. The challenge in the present work is to be able to predict the flow behaviour in order to manufacture advanced composites truss structures. To that end, there is a lack of an advanced simulation tool capable to predict void formations for the manufacture of three dimensional, multi-layer woven textile composites like the Advanced Composites Truss Structure (ACTS) generic node TSB-funded project that is presented in this thesis. Industrial experience has shown that during mould filling, due to race-tracking and stochastic variability in the material properties, the filling patterns and arising cycle times are rarely the same between a given set of apparently identical mouldings. The objectives of this thesis were 2D, 3D racetrack prediction of textile reinforcements for RTM processes and 3D variability prediction at the component scale. A model that predicts the resin rich zone along a component edge was developed for this purpose. The issue of 2D, 3D racetrack prediction was firstly investigated along a 90° edge for three different geometry, architectures and material preforms, on a generic composite node 3D. Variability was also investigated through the same CAD model with the use of the FE/CV technique. A novel numerical approach for 3D FE CAD modelling was developed in order to predict race-tracking and variability for advanced composites structures. A stochastic analysis technique was developed to account for the effect of node variability during the fabrication process by RTM. The study based on this technique provided important insights into flow filling variations, voidage formation and optimization on a generic advanced composite truss structure. The model developed from this work can be used to account for the effects of race-tracking and variability on any other composite component at the macroscale level. The predicted race-track and variability data can complement experimental data in order to enhance flow simulations at the component scale