Rapid Learning and Knowledge-Gap Closure During the Conceptual Design Phase – Rapid R&D

• Main Authors: Charles J. Camarda, Stephen J. Scotti, Iivari Kunttu, Antti Perttula
• Format: Article
• Language: English
• Published: Carleton University 2020-03-01
• Series: Technology Innovation Management Review
• Subjects: knowledge gaps; r&d; rapid product development; set-based design
• Online Access: https://timreview.ca/timreview.ca/article/1332

New product development strategies, such as set-based concurrent engineering design (SBCED) or set-based design (SBD), have demonstrated improved ways to address knowledge gaps in alternate design concepts prior to the decision to select a single concept for development. Most of the corpus in this field addresses engineering product development that relies on systems and subsystems with years of prior experience in testing, development, and operation. These often have known or existing solutions, and use state-of-the-art (SOA), or near SOA technology. In addition, most papers do not dive into the details of how knowledge was attained to rapidly close critical knowledge gaps. This paper attempts to explain how a research-based method to construct knowledge can accelerate the knowledge capture critical for developing solutions to extremely challenging problems. This rapid R&D methodology enables a rapid acquisition of critical knowledge to understand potential failure modes of concepts in a set-based way. Thus, it enables intelligent decisions for the selection of the final concept as well as the continuous maturation of parallel concepts. The continuous, parallel maturation of multiple concepts enables effective off-ramps in the design process as requirements and new knowledge arise in the course of the development program, without incurring excessive rework, cost growth, and schedule creep. The goal of this paper is to describe a method that accelerates the generation of critical knowledge early in the conceptual design phase, as a way to close knowledge gaps quickly, and thus enable intelligent design decisions and concept selections early in the product development cycle. The methodological descriptions are illustrated with case examples from NASA technology development.