Ontology-Based Cloud Manufacturing Framework in Industrialized Construction

Cloud manufacturing is an emerging manufacturing paradigm to enable rapid production for mass customization. Industrialized construction shares a similar production environment with manufacturing products, so it has a great potential to utilize the paradigm. Previous studies never examined cloud manufacturing in the construction context. This work takes the industrial difference into account and proposes a cloud manufacturing framework by ontology modeling. Three ontologies, including ifcOWL, OPW, and OWL-S, are linked to support the design to the manufacturing process of a building project. The framework benefits the design data and manufacturing data integration, and enhances the resource sharing by semantic web service

App chaining software-as-a-service for an advanced manufacturing marketplace

Advances in the field of cloud computing and networking have led to development of Marketplaces (e.g., Awesim) that support Advanced Manufacturing enterprises consisting of Apps. These Marketplaces host Apps that perform simulation and modeling on specialized designs (e.g., pipes, automobile parts). However, the salient limitation in these App Marketplaces is the lack of a development environment that supports effective runtime capabilities for 'Agile Manufacturing' that efficiently and cost-effectively integrates several Apps when building innovative products. To address this problem, we propose a new Software-as-a-Service based App Runtime for the Marketplace environment that can be utilized for agile development of 'Apps' that involve high-performance modeling and simulation. Our solution approach features a web framework for the App runtime that chains together generic set of 'Apps' that run complex simulation jobs on Supercomputer and publish customer facing results. We demonstrate how multiple Apps can be chained using our web framework for a product case study viz., 'WheelSim' deployed in the NSF GENI Cloud platform. Our results show improved App development convenience via rich UI elements interacting with RESTful web services and through dynamic chaining of workflows. Our study also provides App developers with insights pertaining to estimation of resource cost for App pricing issues in the manufacturing Marketplace

Modeling of Cloud-Based Digital Twins for Smart Manufacturing with MT Connect

The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model for one type of 3D printers is designed and integrated into the core of the KRC as a shared resource. Several experiments are conducted and the results show that the CBDT has an excellent performance compared to existing methods

Cyber-physical manufacturing cloud: An efficient method of building digital twin for 3D printer by adapting MTConnect protocol

The common modeling of a virtual machine is using an information model to describe the physics of machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strict requirements such as reducing overhead and saving resources for the systems. In this paper, we investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the processing center and guarantees the fastest speed of the interactions between the human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model for one type of 3D printers is designed and integrated into the core of the KRC as a shared resource. Several experiments and results are provided to show the performance of the CBDT compared to traditional methods --Abstract, page iii

A framework for smart production-logistics systems based on CPS and industrial IoT

Industrial Internet of Things (IIoT) has received increasing attention from both academia and industry. However, several challenges including excessively long waiting time and a serious waste of energy still exist in the IIoT-based integration between production and logistics in job shops. To address these challenges, a framework depicting the mechanism and methodology of smart production-logistics systems is proposed to implement intelligent modeling of key manufacturing resources and investigate self-organizing configuration mechanisms. A data-driven model based on analytical target cascading is developed to implement the self-organizing configuration. A case study based on a Chinese engine manufacturer is presented to validate the feasibility and evaluate the performance of the proposed framework and the developed method. The results show that the manufacturing time and the energy consumption are reduced and the computing time is reasonable. This paper potentially enables manufacturers to deploy IIoT-based applications and improve the efficiency of production-logistics systems

Cloud-based manufacturing-as-a-service environment for customized products

This paper describes the paradigm of cloud-based services which are used to envisage a new generation of configurable manufacturing systems. Unlike previous approaches to mass customization (that simply reprogram individual machines to produce specific shapes) the system reported here is intended to enable the customized production of technologically complex products by dynamically configuring a manufacturing supply chain. In order to realize such a system, the resources (i.e. production capabilities) have to be designed to support collaboration throughout the whole production network, including their adaption to customer-specific production. The flexible service composition as well as the appropriate IT services required for its realization show many analogies with common cloud computing approaches. For this reason, this paper describes the motivation and challenges that are related to cloud-based manufacturing and illustrates emerging technologies supporting this vision byestablishing an appropriate Manufacturing-as-a-Service environment based on manufacturing service descriptions

Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities