Engineering Commons^™

Understanding The Impact Of Virtual-Mirroring Based Learning On Collaboration In A Data And Analytics Function: A Resilience Perspective, Nabil Raad

Wayne State University Dissertations

Large multinational organizations are struggling to adapt and innovate in the face of increasing turbulence, uncertainty, and complexity. The lack of adaptive capacity is one of the major risks facing such organizations as the rapid change in technology, urbanization, socio-economic trends, and regulations continues to accelerate and outpace their ability to adapt. This is a resilience problem that organizations are addressing by investing in Data and Analytics to improve their innovation and competitive capabilities. However, Data and Analytics projects are more likely to fail than to succeed. Competing on data and analytics is not only a technical challenge but also …

Understanding The Relationship Of Innovation And Quality In A Fast-Changing Market: An Automotive Industry Perspective, Donna Leanne Bell

Wayne State University Dissertations

In a time when the consumer electronics industry is getting new products to market at a rapid rate, automotive original equipment manufacturers (OEM) must identify ways of getting new products and features to customers faster and with high quality to maintain or increase market share. This accelerated product development process requires a positive relationship between conceptual design and quality in order for a firm to have high performance in strategic areas innovation and quality. The purpose of this dissertation is to research the impact that quality practices have on the advanced product development process. Specifically, this research is focused on …

Deep Learning Based Reliability Models For High Dimensional Data, Mohammad Aminisharifabad

Wayne State University Dissertations

The reliability estimation of products has crucial applications in various industries, particularly in current competitive markets, as it has high economic impacts. Hence, reliability analysis and failure prediction are receiving increasing attention. Reliability models based on lifetime data have been developed for different modern applications. These models are able to predict failure by incorporating the influence of covariates on time-to-failure. The covariates are factors that affect the subjects’ lifetime.

Modern technologies generate covariates which can be utilized to improve failure time prediction. However, there are several challenges to incorporate the covariates into reliability models. First, the covariates generally are high …

A Structured Methodology For Tailoring And Deploying Lean Manufacturing Systems, Kenneth John Gembel Ii

Wayne State University Dissertations

The seminal works of Peter Drucker and James Womack in the 1990’s outlined the lean manufacturing practices of Toyota Motor Corporation (TMC) to become a world leader in manufacturing. These philosophies have since become the springboard for a significant paradigm shift in approaching manufacturing systems and how to leverage them to optimize operational practices and gain competitive advantage. While there is no shortage of literature touting the benefits of Lean Manufacturing Systems (LMS), there has been significant difficulty in effectively deploying them to obtain and sustain the performance that TMC has achieved.

This body of work provides a novel methodology …