2,652 research outputs found

    An investigation into coordinate measuring machine task specific measurement uncertainty and automated conformance assessment of airfoil leading edge profiles

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    The growing demand for ever more greener aero engines has led to ever more challenging designs and higher quality products. An investigation into Coordinate Measuring Machine measurement uncertainty using physical measurements and virtual simulations revealed that there were several factors that can affect the measurement uncertainty of a specific task. Measurement uncertainty can be affected by temperature, form error and measurement strategy as well as Coordinate Measuring Machine specification. Furthermore the sensitivity of circular features size and position varied, when applying different substitute geometry algorithms was demonstrated. The Least Squares Circle algorithm was found to be more stable when compared with the Maximum Inscribed Circle and the Minimum Circumscribed Circle. In all experiments it was found that the standard deviation when applying Least Squares Circle was of smaller magnitude but similar trends when compared with Maximum Inscribed Circle and the Minimum Circumscribed Circle. A Virtual Coordinate Measuring Machine was evaluated by simulating physical measurement scenarios of different artefacts and different features. The results revealed good correlation between physical measurements uncertainty results and the virtual simulations. A novel methodology for the automated assessment of leading edge airfoil profiles was developed by extracting the curvature of airfoil leading edge, and the method lead to a patent where undesirable features such as flats or rapid changes in curvature could be identified and sentenced. A software package named Blade Inspect was developed in conjunction with Aachen (Fraunhoufer) University for the automated assessment and integrated with a shop floor execution system in a pre-production facility. The software used a curvature tolerancing method to sentence the leading edge profiles which aimed at removing the subjectivity associated with the manual vision inspection method. Initial trials in the pre-production facility showed that the software could sentence 200 profiles in 5 minutes successfully. This resulted in a significant improvement over the current manual visual inspection method which required 3 hours to assess the same number of leading edge profiles

    Assurance Benefits of ISO 26262 compliant Microcontrollers for safety-critical Avionics

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    The usage of complex Microcontroller Units (MCUs) in avionic systems constitutes a challenge in assuring their safety. They are not developed according to the development requirements accepted by the aerospace industry. These Commercial off-the-shelf (COTS) hardware components usually target other domains like the telecommunication branch. In the last years MCUs developed in compliance to the ISO 26262 have been released on the market for safety-related automotive applications. The avionic assurance process could profit from these safety MCUs. In this paper we present evaluation results based on the current assurance practice that demonstrates expected assurance activities benefit from ISO 26262 compliant MCUs.Comment: Submitted to SafeComp 2018: http://www.es.mdh.se/safecomp2018

    Data quality in health research: the development of methods to improve the assessment of temporal data quality in electronic health records

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    Background: Electronic health records (EHR) are increasingly used in medical research, but the prevalence of temporal artefacts that may bias study findings is not widely understood or reported. Furthermore, methods aimed at efficient and transparent assessment of temporal data quality in EHR datasets are unfortunately lacking. Methods: 7959 time series representing different measures of data quality were generated from eight different EHR data extracts covering activity between 1986-2019 at a large UK hospital group. These time series were visually inspected and annotated via a citizen-science crowd-sourcing platform, and consensus labels for the locations of all change points (i.e. places where the distribution of data values changed suddenly and unpredictably) were constructed using density-based clustering with noise. The crowd-sourced consensus labels were validated against labels produced by an experienced data scientist, and a diverse range of automated change point detection methods were assessed for accuracy against these consensus labels using a novel approximation to a binary classifier. Lastly, an R package was developed to facilitate assessment of temporal data quality in EHR datasets. Results: Over 2000 volunteers participated in the citizen-science project, performing 341,800 visual inspections of the time series. A total of 4477 distinct change points were identified across the eight data extracts, covering almost every year of data and virtually all data fields. Compared to expert labels, accuracy of crowd-sourced consensus labels identifying the locations of individual change points had high sensitivity 80.4% (95% CI 77.1, 83.3), specificity 99.8% (99.7, 99.8), positive predictive value (PPV) 84.5% (81.4, 87.2) and negative predictive value (NPV) 99.7% (99.6, 99.7). Automated change point detection methods failed to detect the crowd-sourced change points accurately, with maximum sensitivity 36.9% (35.2, 38.8), specificity 100% (100, 100), PPV 51.6% (49.4, 53.8), and NPV 99.9% (99.9, 99.9). Conclusions: This large study of real-world EHR found temporal artefacts occurred with very high frequency, which could impact findings from analyses using these data. Crowd-sourced labels of change points compared favourably to expert labels, but currently-available automated methods performed poorly at identifying such artefacts when compared to human visual inspection. To improve reproducibility and transparency of studies using EHRs, thorough visual assessment of temporal data quality should be conducted and reported, which can be assisted by tools such as the new daiquiri R package developed as part of this thesis

    Flexible Views for View-based Model-driven Development

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    Modern software development faces the problem of fragmentation of information across heterogeneous artefacts in different modelling and programming languages. In this dissertation, the Vitruvius approach for view-based engineering is presented. Flexible views offer a compact definition of user-specific views on software systems, and can be defined the novel ModelJoin language. The process is supported by a change metamodel for metamodel evolution and change impact analysis

    Quality assessment technique for ubiquitous software and middleware

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    The new paradigm of computing or information systems is ubiquitous computing systems. The technology-oriented issues of ubiquitous computing systems have made researchers pay much attention to the feasibility study of the technologies rather than building quality assurance indices or guidelines. In this context, measuring quality is the key to developing high-quality ubiquitous computing products. For this reason, various quality models have been defined, adopted and enhanced over the years, for example, the need for one recognised standard quality model (ISO/IEC 9126) is the result of a consensus for a software quality model on three levels: characteristics, sub-characteristics, and metrics. However, it is very much unlikely that this scheme will be directly applicable to ubiquitous computing environments which are considerably different to conventional software, trailing a big concern which is being given to reformulate existing methods, and especially to elaborate new assessment techniques for ubiquitous computing environments. This paper selects appropriate quality characteristics for the ubiquitous computing environment, which can be used as the quality target for both ubiquitous computing product evaluation processes ad development processes. Further, each of the quality characteristics has been expanded with evaluation questions and metrics, in some cases with measures. In addition, this quality model has been applied to the industrial setting of the ubiquitous computing environment. These have revealed that while the approach was sound, there are some parts to be more developed in the future

    Towards Understanding and Applying Security Assurance Cases for Automotive Systems

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    Security Assurance Cases (SAC) are structured bodies of arguments and evidence used to reason about security properties of a certain artefact.SAC are gaining focus in the automotive domain as the need for security assurance is growing due to software becoming a main part of vehicles. Market demands for new services and products in the domain require connectivity, and hence, raise security concerns. Regulators and standardisation bodies started recently to require a structured for security assurance of products in the automotive domain, and automotive companies started, hence, to study ways to create and maintain these cases, as well as adopting them in their current way of working.In order to facilitate the adoption of SAC in the automotive domain, we created CASCADE, an approach for creating SAC which have integrated quality assurance and are compliant with the requirements of ISO/SAE-21434, the upcoming cybersecurity standard for automotive systems.CASCADE was created by conducting design science research study in two iterative cycles. The design decisions of CASCADE are based on insights from a qualitative research study which includes a workshop, a survey, and one-to-one interviews, done in collaboration with our industrial partners about the needs and drivers of work in SAC in industry, and a systematic literature review in which we identified gaps between the industrial needs and the state of the art.The evaluation of CASCADE was done with help of security experts from a large automotive OEM. It showed that CASCADE is suitable for integration in industrial product development processes. Additionally, our results show that the elements of CASCADE align well with respect to the way of working at the company, and has the potential to scale to cover the requirements and needs of the company with its large organization and complex products

    TOWARDS SMART MANUFACTURING: COMPLIANCE MONITORING FOR COMPUTATIONAL AUDITING

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    Manufacturers operating in international markets are faced with complex rules and regulations that must be complied with in order to trade successfully. A general phenomenon among international enterprises is that, when they are conducting business across borders, their internal information systems fail to interface well with systems or platforms built specially for compliance reports. This leads to inventory mismatch and results in other types of problems, such as delay of goods delivery or incorrect duty payment. One of the main difficulties in fully integrating information systems arises from the highly flexible and volatile nature of manufacturing processes, which would need highly customizable and adaptive information systems. Currently, there is a lack of systematic method to monitor compliance within flexible multinational manufacturing processes and supply chains. Moreover, improper operations could hamper compliance even normal business processes. In order to have well integrated systems as well as timely detection and mitigation of compliance faults, data processing tools are needed to identify and diagnose inconsistencies in manufacturing and inventory management. This research aims to innovate accounting information systems by designing a framework with the application of process mining and engineering techniques in computational auditing. An in-depth case study is conducted for research validation

    Property Satisfiability Analysis for Product Lines of Modelling Languages

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    © 2022 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Software engineering uses models throughout most phases of the development process. Models are defined using modelling languages. To make these languages applicable to a wider set of scenarios and customizable to specific needs, researchers have proposed using product lines to specify modelling language variants. However, there is currently a lack of efficient techniques for ensuring correctness with respect to properties of the models accepted by a set of language variants. This may prevent detecting problematic combinations of language variants that produce undesired effects at the model level. To attack this problem, we first present a classification of instantiability properties for language product lines. Then, we propose a novel approach to lifting the satisfiability checking of model properties of individual language variants, to the product line level. Finally, we report on an implementation of our proposal in the Merlin tool, and demonstrate the efficiency gains of our lifted analysis method compared to an enumerative analysis of each individual language variantThis work has been funded by the Spanish Ministry of Science (RTI2018-095255-B-I00), the R&D programme of Madrid (P2018/TCS-4314), and by NSERC. We thank the anonymous referees for their useful comment
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