The Role of Testing in Engineering Product Development Processes

Testing components, prototypes and products comprise essential, but time consuming and costly activities throughout the product development process particularly for complex iteratively designed products. The planning of testing is a critical challenge for these complex products for which market pressures demand shorter development times. A literature review identified that testing in the design process is a relatively under researched area. An extended case study in a diesel engine company was therefore conducted to explore how testing is integrated into the product development process and how different types of testing are planned across the stages of product development. The first part of this research study reports the empirical study. A framework resulting from this work is proposed which identifies the entities that characterise how testing should be planned. Motivated by needs of companies and research gaps identified in the literature review, the second part of this study focuses on three key problems for planning of testing in product development process: prioritisation of testing activities, scheduling of testing activities and managing the overlapping of testing and design activities. A method of integrating Quality Function Development (QFD) and Failure Modes and Effect Analysis (FMEA) for prioritising testing activities has been proposed, which can improve the current test prioritisation process of the company. A Multiple Domain Matrix (MDM) is created consisting of the components and associated tests of a product arranged in a format that allows the dependency and interrelationships between key parts and tests to be identified. This form of representation together with the proposed prioritisation method will improve the process of organising and scheduling the testing activities. The final study shows how virtual testing can mediate information flows between overlapping physical tests and (re)design and mitigate the risk associated with overlapping process. The study proposes a significant modification to the existing product development process configuration for design and testing. This reconfiguration makes explicit use of virtual testing which is an extension to Computer Aided Engineering. Virtual testing mirrors the testing process through modelling and simulation, as a distinct and significant activity. Virtual testing is used to (a) enhance and (b) replace some physical tests. Finally, this study assesses the costs and risks of overlaps and their amelioration through targeted virtual testing

LogPrompt: Prompt Engineering Towards Zero-Shot and Interpretable Log Analysis

Automated log analysis is crucial in modern software-intensive systems for ensuring reliability and resilience throughout software maintenance and engineering life cycles. Existing methods perform tasks such as log parsing and log anomaly detection by providing a single prediction value without interpretation. However, given the increasing volume of system events, the limited interpretability of analysis results hinders analysts' trust and their ability to take appropriate actions. Moreover, these methods require substantial in-domain training data, and their performance declines sharply (by up to 62.5%) in online scenarios involving unseen logs from new domains, a common occurrence due to rapid software updates. In this paper, we propose LogPrompt, a novel zero-shot and interpretable log analysis approach. LogPrompt employs large language models (LLMs) to perform zero-shot log analysis tasks via a suite of advanced prompt strategies tailored for log tasks, which enhances LLMs' performance by up to 107.5% compared with simple prompts. Experiments on nine publicly available evaluation datasets across two tasks demonstrate that LogPrompt, despite using no training data, outperforms existing approaches trained on thousands of logs by up to around 50%. We also conduct a human evaluation of LogPrompt's interpretability, with six practitioners possessing over 10 years of experience, who highly rated the generated content in terms of usefulness and readability (averagely 4.42/5). LogPrompt also exhibits remarkable compatibility with open-source and smaller-scale LLMs, making it flexible for practical deployment

Software Process Dynamics: Modeling, Simulation and Improvement

The aim of this chapter is to introduce the reader to the dynamics of the software process, the ways to represent and formalize it, and how it can be integrated with other techniques to facilitate, among other things, process improvement. In order to achieve this goal, different approaches of software process modeling and simulation will be introduced, analyzing their pros and cons. Then, continuous modeling will be used as the modeling approach to build software process models that work in the qualitative and quantitative fields, assessing the decision-making process and the software process improvement arena. The integration of this approach with current process assessment models (such as CMM), static and algorithmic models (such as traditional models used in the estimation process) and the design of a metrics collection program which is triggered by the actual process of model building will also be described in the chapter.Comisión Interministerial de Ciencia y Tecnología (CICYT) TIN2004-06689-C03-0

State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies

Recent digital advances have popularized predictive maintenance (PMx), offering enhanced efficiency, automation, accuracy, cost savings, and independence in maintenance. Yet, it continues to face numerous limitations such as poor explainability, sample inefficiency of data-driven methods, complexity of physics-based methods, and limited generalizability and scalability of knowledge-based methods. This paper proposes leveraging Digital Twins (DTs) to address these challenges and enable automated PMx adoption at larger scales. While we argue that DTs have this transformative potential, they have not yet reached the level of maturity needed to bridge these gaps in a standardized way. Without a standard definition for such evolution, this transformation lacks a solid foundation upon which to base its development. This paper provides a requirement-based roadmap supporting standardized PMx automation using DT technologies. A systematic approach comprising two primary stages is presented. First, we methodically identify the Informational Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a foundation from which any unified framework must emerge. Our approach to defining and using IRs and FRs to form the backbone of any PMx DT is supported by the track record of IRs and FRs being successfully used as blueprints in other areas, such as for product development within the software industry. Second, we conduct a thorough literature review spanning fields to determine the ways in which these IRs and FRs are currently being used within DTs, enabling us to point to the specific areas where further research is warranted to support the progress and maturation of requirement-based PMx DTs.Comment: (1)This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Assessing the accuracy of peak and cumulative low back analyses when human anthropometry is scaled in a virtual environment.

This study addressed the effect of scaling subjects in a virtual reality environment when performing ergonomic evaluations for assembly automotive tasks. Ten male and ten female automotive employees participated in this study. Subjects were selected to fit into one of 4 anthropometric groups (n=5/group); 5th percentile female (5F), 50th percentile female (50F), 50th percentile male (50M), or 95th percentile male (95M). Each subject was asked to perform 3 automotive assembly tasks while interacting with a digital rendering of a vehicle in virtual reality. The subjects were represented in virtual reality as a human manikin (Classic Jack, UGS) whose actions were driven by their actual motions captured via motion tracking (EvaRT, MotionAnalysis). Each subject performed the tasks under 4 different conditions; in one condition, the subject appeared as their true size, and in the three other conditions, they were scaled to appear as the size of the other three subject groups. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 44-03, page: 1426. Thesis (M.H.K.)--University of Windsor (Canada), 2005

The Impact of Artificial Intelligence on Strategic and Operational Decision Making

openEffective decision making lies at the core of organizational success. In the era of digital transformation, businesses are increasingly adopting data-driven approaches to gain a competitive advantage. According to existing literature, Artificial Intelligence (AI) represents a significant advancement in this area, with the ability to analyze large volumes of data, identify patterns, make accurate predictions, and provide decision support to organizations. This study aims to explore the impact of AI technologies on different levels of organizational decision making. By separating these decisions into strategic and operational according to their properties, the study provides a more comprehensive understanding of the feasibility, current adoption rates, and barriers hindering AI implementation in organizational decision making

NASA/DOD Aerospace Knowledge Diffusion Research Project. Report 35: The use of computer networks in aerospace engineering

This research used survey research to explore and describe the use of computer networks by aerospace engineers. The study population included 2000 randomly selected U.S. aerospace engineers and scientists who subscribed to Aerospace Engineering. A total of 950 usable questionnaires were received by the cutoff date of July 1994. Study results contribute to existing knowledge about both computer network use and the nature of engineering work and communication. We found that 74 percent of mail survey respondents personally used computer networks. Electronic mail, file transfer, and remote login were the most widely used applications. Networks were used less often than face-to-face interactions in performing work tasks, but about equally with reading and telephone conversations, and more often than mail or fax. Network use was associated with a range of technical, organizational, and personal factors: lack of compatibility across systems, cost, inadequate access and training, and unwillingness to embrace new technologies and modes of work appear to discourage network use. The greatest positive impacts from networking appear to be increases in the amount of accurate and timely information available, better exchange of ideas across organizational boundaries, and enhanced work flexibility, efficiency, and quality. Involvement with classified or proprietary data and type of organizational structure did not distinguish network users from nonusers. The findings can be used by people involved in the design and implementation of networks in engineering communities to inform the development of more effective networking systems, services, and policies

A practice based learning environment for engineering students: Acquiring competencies for working on advanced manufacturing engineering

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.In this thesis the author describes the design and operation of a learning environment aimed at imparting technical, technological and managerial knowledge, developing understanding of the underlying issues and enhancing team work skills for an advanced technology future. He offers an analysis of learning, education and training and compares group work with individual tasks, presents a major case study and illustrates the features which distinguish the approach from role play, simulation and experiential learning. When staff at Brunel University were faced with the problem of teaching Computer Integrated Manufacturing (CIM) to engineering students on thin sandwich type undergraduate degree programmes the writer suggested the use of an approach he would later describe as 'practice based learning' or 'real life simulation'. The fourth year course in CIM is designed as a double option for the complementary undergraduate courses, Brunel Manufacturing Engineering (BME) and Special Engineering Programmes (SEP). It is an extension of the Manufacturing Design and Practice course in years one to three of the BME course and of the Design strand on SEP, both of which restrict students' work to the use of individual machine tools and stand alone computing facilities. A wide range of teaching methods is used on the CIM course, including lectures by course staff, presentations by experts and, as the major element, a large group project involving all the students on the course, organised in a management matrix, coordinated by the students and supported by the staff acting as experts. The students also undertake assignment work alongside the technical tasks, to focus their thinking and to improve written communication skills. While the course described cannot replace more than a small proportion of the more conventional lecture, laboratory and tutorial teaching on an engineering programme, it provides a setting where students can experiment and learn about their own strengths and weaknesses in a realistic situation and in the context of teamwork. It also offers a space where they can make quite serious mistakes without direct consequences to their careers. The experience of seven years leads the author to believe that advanced manufacturing technologies and the associated management techniques should be taught in a project based environment with clear and real targets and realistic constraints, offering students challenges to which they can only rise through close and creative team work. The management of task execution must be left largely in the students' own hands. A high level of "consultant" type support is essential though, allied to an assessment scheme which promises and ensures fair treatment of the individual. The different parts of the thesis will be relevant to readers depending on their interest and background. Chapter 1 sets the scene and outlines the approach taken. Following this broad outline of the scope of the dissertation the author places Computer Integrated Manufacturing in a wider context in chapter 2, by providing an introduction to the underlying issues of computer integration and human factors. He puts forward a case for new approaches to the education and training of engineers and managers who will be working in Computer Integrated Manufacturing and Advanced Manufacturing Environments in general. Chapter 3 is devoted to the management of projects while chapter 4 is used to question the role of the engineer. Chapters 5 and 6 provide an introduction to theories of knowledge, teaching, learning and motivation. Chapters 7 and 8 are devoted to particular aspects of engineering education, while chapter 9 reviews the approach used at Brunel University. The topical issues of competence and its relevance to engineering education is discussed in chapter 10, leading into chapters 11 and 12 which deal with aspects of the CIM course. Chapters 13 and 14 are devoted to case-studies and particular tools. The key question of assessment of a practice oriented and team based course is addressed in chapter 15, followed by an evaluation of the CIM process and its application to engineering education of a full time nature which is included in chapters 17 and 18.Funding was obtained from The General Electric Company Prize 1993: Manufacturing Systems Engineering

The development of a rule based expert system to automate the digital analysis of condition monitoring parameters captured on rolling element bearings subjected to simulated failure

This synopsis provides a brief summary of the development of a rule based expert system to diagnose bearing failure. Firstly it covers the proposal of a generic, expert system based industrial condition monitoring system. It then discusses in more detail the development of a specific aspect ofthe system, viz. the analysis of rolling element bearing condition. The bearing test rig and data capture system are described, followed by primary research to define the bearing analysis solution space. This includes the use of vibration parameters, measured and derived operating conditions and the bearing running condition. It then explains the development of rulebases for the three analysis tasks of detection, diagnosis and prognosis. Included is a discussion on techniques used to normalise and adjust the vibration parameters to allow analysis under any operating conditions. Finally the synopsis is concluded with a discussion on the performance of the system and contributions made to the developing field of condition monitoring using expert systems

Optimization of Safety Control System for Civil Infrastructure Construction Projects

Labor-intensive repetitive activities are common in civil construction projects. Construction workers are prone to developing musculoskeletal disorders-related injuries while performing such tasks. The government regulatory agency provides minimum safety requirement guidelines to the construction industry that might not be sufficient to prevent accidents and injuries in a construction site. Also, the regulations do not provide insight into what can be done beyond the mandatory requirements to maximize safety and underscore the level of safety that can be attained and sustained on a site. The research addresses the aforestated problem in three stages: (i) identification of theoretical maximum attainable level of safety, safety frontier, (ii) identification of underlying system inefficiencies and operational inefficiencies, and (iii) identification of achievable level of safety, sustainable safety. The research proposes a novel approach to identify the safety frontier by kinetic analysis of the human body while performing labor-intensive repetitive tasks. The task is a combination of different unique actions, which further involve several movements. For identifying a safe working procedure, each movement frame needs to be analyzed to compute the joint stress. Multiple instances of repetitive tasks can then be analyzed to identify unique actions exerting minimum stress on joints. The safety frontier is a combination of such unique actions. For this, the research proposes to track the skeletal positional data of workers performing different repetitive tasks. Unique actions involved in all tasks were identified for each movement frame. For this, several machine learning techniques were implemented. Moreover, the inverse dynamics principle was used to compute the stress induced by essential joints. In addition to the inverse dynamics principle, several machine learning algorithms were implemented to predict lower back moments. Then, the safety frontier was computed, combining the unique actions exerting minimum stress to the joints. Furthermore, the research conducted a questionnaire survey with construction experts to identify the factors affecting system inefficiencies that are not under the control of the project management team and operational inefficiencies that are under control. Then, the sustainable safety was computed by adding system inefficiencies to the safety frontier and removing operational inefficiencies from observed safety. The research validated the applicability of the proposed methodology in a real construction site. The application of random forest classifier, one-vs-rest classifier, and support vector machine approach were validated with high accuracy (\u3e95%). Similarly, random forest regressor, lasso regression, gradient boosting evaluation, stacking regression, and deep neural network were explored to predict the lower back moment. Random forest regressor and deep neural network predicted the lower back moment with an explained variance of 0.582 and 0.700, respectively. The computed safety frontier and sustainable safety can potentially facilitate the construction sector to improve safety strategies by providing a higher safety benchmark for monitoring, including the ability to monitor postural safety in real-time. Moreover, different industrial sectors such as manufacturing and agriculture can implement the similar approach to identify safe working postures for any labor-intensive repetitive task