No / The purpose of this study was to assess the accuracy of digital radiographs and hence their effectiveness in templating. The methodology involved a retrospective study of post operative radiographs of patients with hemiarthroplasty of the hip. Three observers made observations blinded to each other¿s measurements. A statistical analysis of the data highlights magnification varying from 6 to 31 percent. There is a statistically significant relationship between the size of the error (size measured on radiograph minus implant size, i.e. magnification) and the implant size (p = 0.005) but the percentage error (error/implant size x 100) is independent of implant size (p = 0.505). It is our impression that digital radiographs and templating on the digital radiographs should not be considered a precise process.

The formulated study is focused on the analysis and quantification of the accuracy–parameters related to the abrasive process. The scope of the mentioned study deals with the identification of the abrasive process, technological influence and accuracy–parameters of abrading surfaces. In the final part of this study, there is a practical sample described with respect to the technological influence on the resulting accuracy–parameters of the abrasive process.

Published Article / Spin casting is widely used as a batch manufacturing process for decorative products. In the process, moulds are filled by taking advantage of the centrifugal effect, which is used to increase the pressure within the moulds, resulting in more detailed products. In this study, we analyse the different parameters that could affect the casting of mechanical parts through spin casting. Through this study, the user will be guided in the selection of parameters that will result in a certain degree of accuracy. The parameters were determined by performing numerous experiments using zinc alloy and tin-based pewter as casting materials. Results were obtained by casting approximately 15 000 parts in various positions, and at various clamping pressures, rotational speeds and temperatures in both the mould and the material. The experiments were undertaken by varying one parameter at a time, and with each set parameter repeated once, resulting in 100 test pieces per parameter for evaluation. From the results obtained, a series of critical factors and parameters, which are driven by part characteristics or features, has been studied. Contrary to following a modelling approach, the research was conducted following an action-research approach, with planned activities, but where actual results have defined the follow-up procedures. These guidelines will help industrial users ensure the accuracy of parts produced by spin casting. Also, since this project attempted to create a database of results that can be applied in future, it furthermore implies that the data created for the first time can be used in a numerical modelling approach in further / follow-up research. No such data was available from any previous research.

ITC/USA 2010 Conference Proceedings / The Forty-Sixth Annual International Telemetering Conference and Technical Exhibition / October 25-28, 2010 / Town and Country Resort & Convention Center, San Diego, California / This document is focused on the examination of the tracking angular error due to the radio refraction for the target in low altitude of less than 5km and in low elevation angle. The real measured data using the GPS and the tracking systems of C- and S-band frequency in NARO Space centre, Korea are used for the analysis. The analysis shows couple of conclusions on the radio refraction effects; there are angular errors due to the radio refraction which is not to be neglected comparing the accuracy of the tracking system but to be considered for the precise measurement of the target position. Also, the refraction errors are dependent on the target altitude, but not on the frequency.

ITC/USA 2005 Conference Proceedings / The Forty-First Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2005 / Riviera Hotel & Convention Center, Las Vegas, Nevada / There are increasing demands, particularly from government agencies, to perform uncertainty analysis in order to assign accuracy bounds to telemetered data from environmental measuring transducers (pressure, acceleration, force, strain, temperature, etc.). Several requirements must be fulfilled before measurement uncertainty analysis is justified. These requirements include good measurement system design practices such as adequate low- and high-frequency response and data-sampling rates, appropriate anti-aliasing filter selection^(1), proper grounding and shielding, and many more. In addition, there are applications (e.g., flight test) in which the environment of the transducer varies with time and/or location. In these applications, it is a requisite that data-validation be performed to establish that an individual transducer responds only to the environmental stimulus that it is intended to measure. Without this validation component designed into the telemetry system, assigned accuracy bounds can be totally meaningless. This paper presents examples and describes techniques for data validation of signals from environmental measuring transducers.

Inventory management is an important part of a good functioning logistic. Nearly all the literature on optimal inventory management uses criteria of cost minimization and profit maximization. To have a well functioning forecasting system it is important to have a balance in the inventory. But, it exist different factors that can results in uncertainties and difficulties to maintain this balance. One important factor is the customers’ demand. Over half of the stocked items are in stock to prevent irregular orders and an uncertainty demand. The customers’ demand can be categorized into four categories: Smooth, Erratic, Intermittent and Lumpy. Items with a lumpy demand i.e. the items that are both intermittent and erratic are the hardest to manage and to forecast. The reason for this is that the quantity and demand for these items varies a lot. These items may also have periods of zero demand. Because of this, it is a challenge for companies to forecast these items. It is hard to manage the random values that appear at random intervals and leaving many periods with zero demand. Due to the lumpy demand, an ongoing problem for most organization is the inaccuracy of forecasts. It is almost impossible to predict exact forecasts. It does not matter how good the forecasts are or how complex the forecast techniques are, the instability of the markets confirm that the forecasts always will be wrong and that errors therefore always will exist. Therefore, we need to accept this but still work with this issue to keep the errors as minimal and small as possible. The purpose with measuring forecast errors is to identify single random errors and systematic errors that show if the forecast systematically is too high or too low. To calculate the forecast errors and measure the forecast accuracy also helps to dimensioning how large the safety stock should be and control that the forecast errors are within acceptable error margins. The research questions answered in this master thesis are: How should one calculate forecast accuracy for stocked items with a lumpy demand? How do companies measure forecast accuracy for stocked items with a lumpy demand, which are the differences between the methods? What kind of information do one need to apply these methods? To collect data and answer the research questions, a literature study have been made to compare how different researchers and authors write about this specific topic. Two different types of case studies have also been made. Firstly, a benchmarking process was made to compare how different companies work with this issue. And secondly, a case study in form of a hypothesis test was been made to test the hypothesis based on the analysis from the literature review and the benchmarking process. The analysis of the hypothesis test finally generated a conclusion that shows that a combination of the measurements WAPE, Weighted Absolute Forecast Error, and CFE, Cumulative Forecast Error, is a solution to calculate forecast accuracy for items with a lumpy demand. The keywords that have been used to search for scientific papers are: lumpy demand, forecast accuracy, forecasting, forecast error.

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