Engineering Commons^™

Generic Design Methodology For Smart Manufacturing Systems From A Practical Perspective, Part I—Digital Triad Concept And Its Application As A System Reference Model, Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo, Lida Xu

Information Technology & Decision Sciences Faculty Publications

Rapidly developed information technologies (IT) have continuously empowered manufacturing systems and accelerated the evolution of manufacturing system paradigms, and smart manufacturing (SM) has become one of the most promising paradigms. The study of SM has attracted a great deal of attention for researchers in academia and practitioners in industry. However, an obvious fact is that people with different backgrounds have different expectations for SM, and this has led to high diversity, ambiguity, and inconsistency in terms of definitions, reference models, performance matrices, and system design methodologies. It has been found that the state of the art SM research is limited …

Generic Design Methodology For Smart Manufacturing Systems From A Practical Perspective. Part Ii—Systematic Designs Of Smart Manufacturing Systems, Zhuming Bi, Wen-Jun Zhang, Chong Wu, Chaomin Luo, Lida Xu

Information Technology & Decision Sciences Faculty Publications

In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing system aims to reconfigure different systems in achieving high-level smartness in its system lifecycle; moreover, each smart system is customized in terms of the constraints of manufacturing resources and the prioritized performance metrics to achieve system smartness. Few works were found on the development of systematic methodologies for the design of smart manufacturing systems. The novel contributions …

Development Of Smart Semiconductor Manufacturing: Operations Research And Data Science Perspectives, Marzieh Khakifirooz, Mahdi Fathi, Kan Wu

Bagley College of Engineering Publications and Scholarship

With advances in information and telecommunication technologies and data-enabled decision making, smart manufacturing can be an essential component of sustainable development. In the era of the smart world, semiconductor industry is one of the few global industries that are in a growth mode to smartness, due to worldwide demand. The important opportunities that can boost the cost reduction of productivity and improve quality in wafer fabrication are based on the simulations of actual environment in Cyber-Physical Space and integrate them with decentralized decision-making systems. However, this integration faced the industry with novel unique challenges. The stream of the data from …

Building A Simple Smart Factory, Iman Abdulwaheed

Mechanical Engineering Theses

This thesis describes (a) the search and findings of smart factories and their enabling technologies (b) the methodology to build or retrofit a smart factory and (c) the building and operation of a simple smart factory using the methodology. A factory is an industrial site with large buildings and collection of machines, which are operated by persons to manufacture goods and services. These factories are made smart by incorporating sensing, processing, and autonomous responding capabilities.

Developments in four main areas (a) sensor capabilities (b) communication capabilities (c) storing and processing huge amount of data and (d) better utilization of technology …

Developing An Architecture Framework For Cloud-Based, Multi-User, Finite Element Pre-Processing, Jared Calvin Briggs

Theses and Dissertations

This research proposes an architecture for a cloud-based, multi-user FEA pre-processing system, where multiple engineers can access and operate on the same model in a parallel environment. A prototype is discussed and tested, the results of which show that a multi-user preprocessor, where all computing is done on a central server that is hosted on a high performance system, provides significant benefits to the analysis team. These benefits include a shortened preprocessing time, and potentially higher-quality models.