عنوان

Conceptual Framework for adapting Technical Performance Measurement Methodology for Early Stage Research and Development Projects

Number

TL49625

.Language of Text, Soundtrack etc

انگلیسی

Title Proper

Conceptual Framework for adapting Technical Performance Measurement Methodology for Early Stage Research and Development Projects

General Material Designation

[Thesis]

First Statement of Responsibility

Ross E. Agee

Subsequent Statement of Responsibility

Eggstaff, Justin; Islam, Muhammed

Name of Publisher, Distributor, etc.

The George Washington University

Date of Publication, Distribution, etc.

2018

Specific Material Designation and Extent of Item

101

Text of Note

Committee members: Eggstaff, Justin; Islam, Muhammed; Mazzuchi, Thomas A.; Sarkani, Shahram; Strack, Otto E.

Text of Note

Place of publication: United States, Ann Arbor; ISBN=978-0-355-43040-0

Dissertation or thesis details and type of degree

D.Engr.

Discipline of degree

Engineering Management

Body granting the degree

The George Washington University

Text preceding or following the note

2018

Text of Note

Early stage research and development (R&D) projects, programs, or efforts are characterized by a high degree of uncertainty. In the public sector, these efforts are defined as those with technology readiness levels up to 4. Both project management and systems engineering cultures proliferate throughout the public sector. Project management traditionally uses earned value management system to track the progress of its projects. Systems engineers apply Technical Performance Measurement methodology (TPM) to R&D efforts to monitor progress of quality factors with respect to those efforts. Both of these methods have numerous alternative implementations, and both strive to provide risk management indicators and insight into future performance. This paper discusses a conceptual framework for monitoring early stage R&D by altering a TPM method. By quantifying and monitoring the "learning" or technical uncertainty toward the project goal, early stage R&D is given a measurement for technical progress. Learning values are determined using pairwise comparisons of R&D activities that contribute to learning. How the effort increases learning, or degrades uncertainty, over time serves as the baseline for performance management. In order to predict future performance, the learning baseline is regressed in linear segments. Using simulated project status, those predictions are shown to have acceptable uncertainty by validating against prediction intervals.

Management; Engineering

Subject Term

Applied sciences;Social sciences;Innovation management;Performance management;Public sector;Research and development;Technology maturation

Siddiqui, Niloufer Aamina

Eggstaff, Justin; Islam, Muhammed

Subdivision

Engineering Management

The George Washington University

Call Number

1969120233; 10636922

Electronic name

p

[Thesis]

276903

a

Y