Smart Product Design Methodology

The noticeable emergence of new technological advances, such as Artificial Intelligence (AI) and Internet of Things (IoT), and their continuous developments in today’s market, have paved the way for an apparent transformation from conventional products to smart connected products. Smart products are Cyber-Physical Systems (CPS) that provide services to users through Internet and Communication capabilities. The use of smart products offers exceptional potential for the users to meet their expectations and needs intelligently and effectively. Hence, designers and manufacturers are encouraged to cope with constantly changing consumers’ requirements and help in satisfying their needs. It is necessary to achieve a high level of awareness when interacting with smart products, where in some cases, ambiguity and uncertainty may lead to an undesired outcome. Thus, the objective of this research thesis is to introduce a novel smart product design methodology that reveals a new design dimension that was found by conducting an extensive literature review. Smart product design methodology uses integration between existing Design Theory and Methodologies (DTM), both Systematic Design Approach (SDA) and Axiomatic Design Theory (ADT) which are integrated through the features and functions of smart products. The proposed design methodology concentrates on reducing the complexity of the product and raising its affordances for the users to perceive. This research includes a case study on smart speakers and voice-initiated virtual assistants specifically on Amazon’s Alexa, where the methodology proposed was applied. As a result, the complexity was reduced by achieving an uncoupled design, and affordances’ measures were discussed using the guidelines and recommendations concerning both visual and voice design perspectives for designers and developers of virtual assistants in order to maximize the affordances for the user to perceive with the least amount of ambiguity and doubtfulness.

Name thesis:degree_name

M.A.Sc.

Level thesis:degree_level

Masters

Discipline thesis:degree_discipline

Industrial and Manufacturing Systems Engineering

Grantor

University of Windsor

Year dc:date.issued

2020

Author dc:creator

• Qutb, Abdullah

Advisor dc:contributor.advisor

• Waguih ElMaraghy

Contributors dc:contributor

• mita@uwindsor.ca

Licence

• http://creativecommons.org/licenses/by-nc-nd/4.0/

Language dc:language.iso

en_CA

Handle dc:identifier.uri

https://hdl.handle.net/20.500.14776/8944

OAI identifier oai:identifier

oai:uwindsor.scholaris.ca:20.500.14776/8944