Monitoring coordinate measuring machines by calibrated parts

Coordinate measuring machines (CMM) are essential for quality assurance and production control in modern manufacturing. Due to the necessity of assuring traceability during the use of CMM, interim checks with calibrated objects carried out periodically. For this purpose usually special artefacts like standardized ball plates, hole plates, ball bars or step gages are measured. Measuring calibrated series parts would be more advantageous. Applying the substitution method of ISO 15530-3: 2000 such parts can be used. It is less cost intensive and less time consuming than measuring expensive special standardized objects in special programmed measurement routines. Moreover, the measurement results can directly compare with the calibration values; thus, direct information on systematic measurement deviations and uncertainty of the measured features are available. The paper describes a procedure for monitoring horizontal-arm CMMs with calibrated sheet metal series parts

Traceable profilometry with a 3D nanopositioning unit and zero indicating sensors in compensation method

Conventional 3D profilers suffer in their traceability and accuracy from nonlinearities of the 1D sensor (optical or tactile) and different measuring principles in the scanning plane compared to the sensor axis. These problems can be overcome using a traceable calibrated 3D positioning device combined with a probing system of negligible measuring range in compensation method. Drawback: reduced dynamics, because of the necessity of accelerated movement of the object to be measured in z-direction for compensating its varying height. Sensors with negligible measuring range to be used for this approach are an optical fixed focus sensor (SIOS GmbH, Germany) and a self-made scanning tunneling sensor without piezo scanner. The integration into the nanopositioning device is made according to a multisensor CMM with fixed and known positions of the sensors with respect to the machine coordinate system giving the possibility of using one sensor's data for navigating the other one. Main applications can be seen in measurement tasks where outstanding accuracy outrivals the need of high measurement speed, e.g. the calibration of step height and pitch standards for profilometry and also for SPM

Stochastic and epistemic uncertainty propagation in LCA

Purpose: When performing uncertainty propagation, most LCA practitioners choose to represent uncertainties by single probability distributions and to propagate them using stochastic methods. However the selection of single probability distributions appears often arbitrary when faced with scarce information or expert judgement (epistemic uncertainty). Possibility theory has been developed over the last decades to address this problem. The objective of this study is to present a methodology that combines probability and possibility theories to represent stochastic and epistemic uncertainties in a consistent manner and apply it to LCA. A case study is used to show the uncertainty propagation performed with the proposed method and compare it to propagation performed using probability and possibility theories alone. Methods: Basic knowledge on the probability theory is first recalled, followed by a detailed description of hal-00811827, version 1- 11 Apr 2013 epistemic uncertainty representation using fuzzy intervals. The propagation methods used are the Monte Carlo analysis for probability distribution and an optimisation on alpha-cuts for fuzzy intervals. The proposed method (noted IRS) generalizes the process of random sampling to probability distributions as well as fuzzy intervals, thus making the simultaneous use of both representations possible

A Reliable Method of Minimum Zone Evaluation of Cylindricity and Conicity from Coordinate Measurement Data

The form error evaluation of cylinders and cones is very important in precision coordinate metrology. The solution of the traditional least squares technique is prone to over-estimation, as a result unnecessary rejections may be caused. This paper proposes a reliable algorithm to calculate the minimum zone form errors of cylinders and cones, called a hybrid particle swarm optimization-differential evolution algorithm. The optimization is conducted in two stages, so that the program can hold a fast convergence rate, while effectively avoiding local minima. Experimental results demonstrate that the proposed algorithm can obtain very accurate and stable results for the calculation of cylindricity and conicity

Industrial applications of computed tomography

The number of industrial applications of Computed Tomography (CT) is large and rapidly increasing. After a brief market overview, the paper gives a survey of state of the art and upcoming CT technologies, covering types of CT systems, scanning capabilities, and technological advances. The paper contains a survey of application examples from the manufacturing industry as well as from other industries, e.g., electrical and electronic devices, inhomogeneous materials, and from the food industry. Challenges as well as major national and international coordinated activities in the field of industrial CT are also presented