Date of Graduation


Document Type


Degree Name

Doctor of Philosophy in Computer Science (PhD)

Degree Level



Computer Science & Computer Engineering


Xiaoqing "Frank" Liu

Committee Member

Brajendra Nath Panda

Second Committee Member

Qinghua Li

Third Committee Member

Miaoqing Huang

Fourth Committee Member

Wenchao Zhou


Cloud Computing, Cyber-Manufacturing, Cyber-Physical Manufacturing Cloud, Digital Twins, Service Computing, Virtual Production Lines


In last decade, the paradigm of Cyber-Physical Systems (CPS) has integrated industrial manufacturing systems with Cloud Computing technologies for Cloud Manufacturing. Up to 2015, there were many CPS-based manufacturing systems that collected real-time machining data to perform remote monitoring, prognostics and health management, and predictive maintenance. However, these CPS-integrated and network ready machines were not directly connected to the elements of Cloud Manufacturing and required human-in-the-loop. Addressing this gap, we introduced a new paradigm of Cyber-Physical Manufacturing Cloud (CPMC) that bridges a gap between physical machines and virtual space in 2017. CPMC virtualizes machine tools in cloud through web services for direct monitoring and operations through Internet. Fundamentally, CPMC differs with contemporary modern manufacturing paradigms. For instance, CPMC virtualizes machining tools in cloud using remote services and establish direct Internet-based communication, which is overlooked in existing Cloud Manufacturing systems. Another contemporary, namely cyber-physical production systems enable networked access to machining tools. Nevertheless, CPMC virtualizes manufacturing resources in cloud and monitor and operate them over the Internet. This dissertation defines the fundamental concepts of CPMC and expands its horizon in different aspects of cloud-based virtual manufacturing such as Digital Twins and Virtual Production Lines.

Digital Twin (DT) is another evolving concept since 2002 that creates as-is replicas of machining tools in cyber space. Up to 2018, many researchers proposed state-of-the-art DTs, which only focused on monitoring production lifecycle management through simulations and data driven analytics. But they overlooked executing manufacturing processes through DTs from virtual space. This dissertation identifies that DTs can be made more productive if they engage directly in direct execution of manufacturing operations besides monitoring. Towards this novel approach, this dissertation proposes a new operable DT model of CPMC that inherits the features of direct monitoring and operations from cloud. This research envisages and opens the door for future manufacturing systems where resources are developed as cloud-based DTs for remote and distributed manufacturing. Proposed concepts and visions of DTs have spawned the following fundamental researches.

This dissertation proposes a novel concept of DT based Virtual Production Lines (VPL) in CPMC in 2019. It presents a design of a service-oriented architecture of DTs that virtualizes physical manufacturing resources in CPMC. Proposed DT architecture offers a more compact and integral service-oriented virtual representations of manufacturing resources. To re-configure a VPL, one requirement is to establish DT-to-DT collaborations in manufacturing clouds, which replicates to concurrent resource-to-resource collaborations in shop floors. Satisfying the above requirements, this research designs a novel framework to easily re-configure, monitor and operate VPLs using DTs of CPMC.

CPMC publishes individual web services for machining tools, which is a traditional approach in the domain of service computing. But this approach overcrowds service registry databases. This dissertation introduces a novel fundamental service publication and discovery approach in 2020, OpenDT, which publishes DTs with collections of services. Experimental results show easier discovery and remote access of DTs while re-configuring VPLs. Proposed researches in this dissertation have received numerous citations both from industry and academia, clearly proving impacts of research contributions.