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Till Albert presents a machine learning based approach to harnessing information contained in big data from different media sources such as patents, scientific publications, or the internet. He shows how this information can be used for automated maturity evaluation of yet unknown technologies. Elaborate patent based indicators contain very useful information on technological aspects of maturity but lack for others such as social, economic, ecological, or political factors. The approach presented in this book is able to incorporate these other factors and provide a firm basis for robust technology maturity and speed of maturity evaluation.
Technology maturity: What is it, and why is it important? For more than ten years, the Government Accountability Office (GAO) has criticized federal agencies for a history of cost and schedule overruns on a significant portion of their procurement programs. GAO has repeatedly reported that the use of immature technologies in programs is a primary cause for these overruns. In spite of these repeated reports, the problems in government procurement have not improved. In fact, recent reports indicate that the problems are getting worse. One cause of this worsening situation might be that, while GAO identified lack of technology maturity as a problem, they did not tell how to measure technology maturity, or conversely, its lack. This groundbreaking work attempts to fill this gap by examining the current state of technology maturity measurement, pointing out strengths and weaknesses of available measures, and proposing a complete technology maturity assessment as a potential solution. The book also includes a discussion of risk during technology development.
The issue presented in these briefing charts is technology maturity at program initiation is a measure of acquisition program risk and a predictor of program success. Measuring technology maturity requires a multi-dimensional perspective.
This report provides guidance on how to assign a technology readiness level (TRL). The method proposed assists in assigning TRLs through a series of questions that focus on a set of unambiguous maturation metrics. This method is slightly biased towards the environment and approach to technology maturation at Sandia National Laboratories where customers and suppliers are in very close proximity to one another, allowing for supplier-customer interactions at a very early stage in technology development. The hope is that this report can serve as a practical guide to anyone trying to understand the maturity of a specific technology. Risk is reduced in system acquisition by selecting mature technologies for inclusion in system development. TRLs are used to assess the maturity of evolving technologies and therefore become part of an overall risk reduction strategy in system development.
This book presents a selection of the best papers given at the XXIV International Conference on Industrial Engineering and Industrial Management. The conference is promoted by ADINGOR (Asociación para el Desarrollo de la Ingeniería de Organización) and organized by the Universidad Politécnica de Madrid and the Universidad Carlos III de Madrid. It took place at the Universidad Carlos III de Madrid (Leganés, Spain) in July 2020. Ensuring Sustainability embodies the latest advances in research and cutting-edge analyses of real case studies in industrial engineering and operations management from diverse international contexts. It also identifies business applications for the latest findings and innovations in operations management and the decision sciences.
Foreword by: James W. Bilbro Technology maturity: What is it, and why is it important? For more than ten years, the Government Accountability Office (GAO) has criticized federal agencies for a history of cost and schedule overruns on a significant portion of their procurement programs. GAO has repeatedly reported that the use of immature technologies in programs is a primary cause for these overruns. In spite of these repeated reports, the problems in government procurement have not improved. In fact, recent reports indicate that the problems are getting worse. One cause of this worsening situation might be that, while GAO identified lack of technology maturity as a problem, they did not tell how to measure technology maturity, or conversely, its lack. This groundbreaking work attempts to fill this gap by examining the current state of technology maturity measurement, pointing out strengths and weaknesses of available measures, and proposing a complete technology maturity assessment as a potential solution. The book also includes a discussion of risk during technology development.
Measuring the Digital Transformation: A Roadmap for the Future provides new insights into the state of the digital transformation by mapping indicators across a range of areas – from education and innovation, to trade and economic and social outcomes – against current digital policy issues, as presented in Going Digital: Shaping Policies, Improving Lives.
It is important to evaluate and understand the state-of-art technologies to position our research and invest our energy and resources in more effective ways. Unfortunately, no systematic approach has been introduced to evaluate the maturity of technologies except a few models such as Redwine/Riddle's model (Redwine and Riddle, 1985), which does not contain a significant concept, "goals" of technologies. A new goal-oriented, technology maturity evaluation model has been proposed in this present study. The model aids to measure how a technology meets the goal of the technology along with a well-defined procedure. The model has applied to evaluate the maturity of the requirements specification technology as a case study. The results showed that this approach promoted effectiveness of measuring the technology maturity and understanding the state-of-art technology.
In 2006, the cumulative cost growth in DoD¿s portfolio of 96 major defense acquisition programs was $296 billion and the average delay in delivering promised capabilities to the warfighter was 22 months. These are very poor outcomes. The auditor has used metrics to review the mgmt. and health of these programs from within the framework of best practices. This testimony discusses: (1) ¿knowledge metrics,¿ used to determine how well programs manage tech., design, and manufacturing risks; (2) outcome metrics -- concerning cost, schedule, and capability -- that serve as ¿health indicators¿ of how well programs are being executed in terms of predicted outcomes; and (3) the prerequisites that must be met in order for a program¿s plans and goals to be realistic.