Grants and Contributions:

Title:
Optimal Concurrent Design of Complex Products Considering Uncertainties
Agreement Number:
RGPIN
Agreement Value:
$110,000.00
Agreement Date:
May 10, 2017 -
Organization:
Natural Sciences and Engineering Research Council of Canada
Location:
Alberta, CA
Reference Number:
GC-2017-Q1-02295
Agreement Type:
Grant
Report Type:
Grants and Contributions
Additional Information:

Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023)

Recipient's Legal Name:
Xue, Deyi (University of Calgary)
Program:
Discovery Grants Program - Individual
Program Purpose:

Concurrent design is an approach to incorporate considerations and activities in downstream product life-cycle aspects, such as manufacturing and operation, into early design stage for shortening product development lead-time and improving overall product life-cycle quality. Over the past years, the applicant’s research program has focused on development of new methodologies and software tools for supporting concurrent design activities, as well as their industrial applications. The research has led to significant scientific contributions and economic benefits.

For design of a complex product that requires multiple techniques in modeling, simulation and optimization, uncertainties significantly influence design quality due to complexities of the designed product. The proposed research program will extend the applicant’s previously developed methods to the optimal concurrent design of complex products where multiple techniques are required in modeling, simulation and optimization, and uncertainties due to these techniques are considered. The long-term objective of this research is to develop the methodologies for future CAD systems that support optimal concurrent design functions.

The proposed research program will focus on the following four aspects: (1) introduction of a hybrid modeling scheme to integrate different types of product descriptions in different product life-cycle aspects considering different types of modeling uncertainties, (2) development of a hybrid simulation approach to integrate various tools for evaluations of different product life-cycle aspects considering different types of simulation uncertainties, (3) development of a hybrid optimization method to identify the optimal design and its downstream life-cycle aspects efficiently considering different types of optimization uncertainties, and, (4) applications of the developed methods for solving engineering problems in industry.

The proposed research will introduce a new approach and many new methodologies/tools for concurrent design of complex products considering uncertainties. These methods and tools can be used for identifying the optimal designs considering functional performance, production cost and operation cost, thus improving competitiveness of the products in marketplaces. The proposed approach has the potential to develop the key components in the future CAD systems that support optimal concurrent design functions.