All Access to FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF. Free Download FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF or Read FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF on The Most Popular Online PDFLAB. Only Register an Account to DownloadFAILURE MODE AND EFFECTS ANALYSIS FMEA PDF. Online PDF Related to FAILURE MODE AND EFFECTS ANALYSIS FMEA . Get Access FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF and Download FAILURE MODE AND EFFECTS ANALYSIS FMEA PDF for Free.

Failure Mode and Effects Analysis (FMEA)

Knowledge sharing mechanisms and techniques in project teams

This paper describes recent approaches using text-mining to automatically profile and extract arguments from legal cases. We outline some of the background context and motivations. We then turn to consider issues related to the construction and composition of corpora of legal cases. We show how a Context-Free Grammar can be used to extract arguments, and how ontologies and Natural Language Processing can identify complex information such as case factors and participant roles. Together the results bring us closer to automatic identification of legal arguments.

/pdf/approaches-to-text-mining-arguments-from-legal-cases-334rqwh7da.pdf

Approaches to text mining arguments from legal cases

Improving the quality of software demands quality controls since the very beginning of the development process, i.e., requirements capture and writing. Automating quality metrics may entail considerable savings, as opposed to tedious, manually performed evaluations. We present some indicators for measuring quality in textual requirements, as well as a tool that computes quality measures in a fully automated way. We want to emphasize that the final goal must be measure to improve. Reducing quality management to the acquisition of a numerical evaluation would crash against the strong opposition of requirements engineers themselves, who would not see in the measurement process the aid of a counselor, but a policeman mechanism of penalties. To avoid this, quality indicators must first of all point out concrete defects and provide suggestions for improvement. The final result will not only be an improvement in the quality of requirements, but also an improvement in the writing skills of requirements engineers.

A framework to measure and improve the quality of textual requirements

Requirements are informal and semi-formal descriptions of the expected behavior of a complex system from the viewpoints of its stakeholders (customers, users, operators, designers, and engineers). However, for the purpose of design, testing, and verification for critical systems, we can transform requirements into formal models that can be analyzed automatically. ARSENAL is a framework and methodology for systematically transforming natural language (NL) requirements into analyzable formal models and logic specifications. These models can be analyzed for consistency and implementability. The ARSENAL methodology is specialized to individual domains, but the approach is general enough to be adapted to new domains.

ARSENAL: Automatic Requirements Specification Extraction from Natural Language

Requirements for a Metamodel to Facilitate Knowledge Sharing between Project Stakeholders

Requirements engineering is crucial to the success of the system engineering process. Unfortunately, while current generation tools provide good support to requirements capture, they offer only modest assistance for cognitive tasks such as requirements assessment. This paper opens by introducing the attributes needed to define a requirement and the qualities of good requirements and requirements sets. An argument is then presented for the inclusion of artificial intelligence to perform requirements analysis and this is followed by a review of intelligent requirement analysis tools identifying the need for enhancements. From this basis, the paper describes the architecture of an intelligent requirements elicitation and assessment assistant that is currently under construction.

4.3.3 An Architecture for an Intelligent Requirements Elicitation and Assessment Assistant

Poor requirements have been cited as a major cause of project failures and cost and schedule overruns in the acquisition of Defence and information systems for at least 15 years. Yet in all this time, academia has not been able to alleviate the problem through traditional teaching techniques. Moreover the commercially available requirements tools manage sets of requirements but do not provide the capability to determine if a requirement is good or bad. This paper summarizes the concept behind a research programme to determine a metric for the goodness of a requirement that could be used in industry and the classroom as well as being built into a software tool. Background

A Proposed Research Programme for Determining a Metric for a Good Requirement

This paper proposes a new generation Computer Enhanced Systems Engineering (CESE) tool known as an Operations Concept Harbinger (OCH). The OCH is the result of the application of information management technology to solving the problem of poorly implemented re-quirements engineering, in particular poorly written and articulated requirements as well as the effect of changing requirements for both single systems and Systems of Systems. The OCH thus bridges the gap between the soft systems methodologies used in the early phases of the system development life cycle and the hard systems methodologies used in the construc-tion of a system. The OCH may be thought of as a multimedia Operations Concept Document that also contains measures of effectiveness for each operational scenario. The paper also de-scribes the experiences of prototyping the OCH for a Force Level Systems Engineering appli-cation. INTRODUCTION We are living in an age of transitions. One of these is the transition from hardware-based systems to software-based systems. While Information Technology (IT) n- uderpins the civilization in the early years of the 21

Introducing a Next Generation Computer Enhanced Systems Engineering Tool: The Operations Concept Harbinger

Development of transport infrastructure has significant challenges including acquisition lag, phased evolution, multiple disparate stakeholders and environment-specific issues. The Asset Standards Authority (ASA) at Tf NSW is introducing MBSE to address these challenges. Instrumental to the introduction is the development of a framework that structures the available data and provides guidance and traceability between the data sets. This framework combines the enterprise-level drivers with the lower level drivers such as standards to outline a generic conceptual design for a transport system. This conceptual design is then used to guide future system development. The outcome is future project information based on greater, enduring understanding of the transport system.

/pdf/case-study-a-model-based-systems-engineering-mbse-framework-2en2z8wwwo.pdf

William Scott

Papers

Requirements for a Metamodel to Facilitate Knowledge Sharing between Project Stakeholders

4.3.3 An Architecture for an Intelligent Requirements Elicitation and Assessment Assistant

A Proposed Research Programme for Determining a Metric for a Good Requirement

Introducing a Next Generation Computer Enhanced Systems Engineering Tool: The Operations Concept Harbinger

Case Study: A Model Based Systems Engineering (MBSE) Framework for Characterising Transportation Systems Over the Full Life Cycle