Login | Register

Optimizing Sustainable Product Development

Title:

Optimizing Sustainable Product Development

Salari, Meysam (2017) Optimizing Sustainable Product Development. PhD thesis, Concordia University.

[img]
Preview
Text (application/pdf)
Salari_PhD_S2018.pdf - Accepted Version
Available under License Spectrum Terms of Access.
1MB

Abstract

Global warming, which is caused by increasing concentrations of carbon emissions, mainly results from human activities, such as fossil fuel burning and deforestation. In order to alleviate global warming and its adverse effects, many countries including the United States and the European Union members have attempted to enact legislation or design market-based carbon trading mechanisms to control carbon emissions. Analyzing the impact of such governmental legislation on developing products has been studied, both in theory and practice. Firms need to incorporate governmental regulations and consider environmental issues and reduced carbon emission in their product development processes, this thesis presents three models for sustainable product development. All models consider environmental issues and cost for the whole life cycle of the product, from the extraction of raw materials to the end of life of the product. Three group of customer requirements are defined as cost, quality and sustainability. The objective of the models is to maximize utility to the customers for these groups of customer requirements. In all three models, three groups of customer requirements are translated to design specifications and the utility of each group is evaluated. The first model is a scoring model to compare between different designs and select the best one; the second model is an optimization model, which provides optimum value for design specifications while maximizing the total utility to the customers for the final design. And finally, the third model is a two-stage stochastic optimization model in which the weights of customer requirements are considered as uncertain parameters. This model also provides the optimum value for design specifications while modeling the weight of customer requirements as an uncertain parameter. The last two models are non-linear, non-convex models with certain conditions and are solved using the Branch-and-Reduce Optimization Navigator methodology. In all three models, Quality Function Deployment is applied to make trade-offs within each group of customer requirements and multi-attribute utility theory is used to make trade-offs between three groups of customer requirements. All three models are applied to a case study, and results show that introducing uncertainty in the parameters increases the total utility by 9.41%, and the optimization model also has the potential to help designers find an optimum design yielding higher customer satisfaction, reducing the time of product development process and making the final design more reliable based on stakeholder’s opinions.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Thesis (PhD)
Authors:Salari, Meysam
Institution:Concordia University
Degree Name:Ph. D.
Program:Industrial Engineering
Date:5 October 2017
Thesis Supervisor(s):Bhuiyan, Nadia
ID Code:983302
Deposited By: MEYSAM SALARI
Deposited On:05 Jun 2018 14:02
Last Modified:05 Jun 2018 14:02
All items in Spectrum are protected by copyright, with all rights reserved. The use of items is governed by Spectrum's terms of access.

Repository Staff Only: item control page

Downloads per month over past year

Back to top Back to top