Cloud-based Design And Manufacturing Research Articles

Design-as-a-Service Framework for Enabling Innovations in Small- and Medium-Sized Enterprises

Abstract Modern manufacturing enterprises must be agile to cope with sudden demand changes arising from increased global competition, geopolitical factors, and unforeseen circumstances such as the Covid-19 pandemic. Small- and Medium-Sized Enterprises (SMEs) in the manufacturing sector lack agility due to lower penetration of Information Technology (IT) and Operational Technology (OT), the inability to employ highly skilled human capital, and the absence of a formal innovation ecosystem for new products or solutions. In recent years, Cloud-based Design and Manufacturing (CBDM) has emerged as an enabler for product realization by integrating various service-based models. However, the existing framework does not thoroughly support the innovation ecosystem from concept to product realization by formally addressing economic challenges and human skillset requirements. The present work considers the augmentation of the Design-as-a-Service (DaaS) model into the existing CBDM framework for enabling systematic product innovations. The DaaS model proposes to connect skilled human resources with enterprises interested in transforming an idea into a product or solution through the CBDM framework. The model presents an approach for integrating human resources with various CBDM elements and end-users through a service-based model. The challenges associated with successfully implementing the proposed model are also discussed. It is established that the DaaS has the potential for rapid and economical product discovery and can be readily accessible to SMEs or independent individuals.

Industry 4.0 - Digital Twin Applied to Direct Digital Manufacturing

Marinha Grande is a city in Leiria’s district, Portugal. Marinha Grande is known as the moulding city, influenced by the glass, plastic and rapid manufacturing industry. Its history comes from the 18th century with the first glass factory. In order to improve technological development in the local industry, Centre for rapid and sustainable product development (CDRsp) was established in 2007.With that historical know-how and data-based moulding manufacturing, this work goal is to link that data with today’s technology, implementing the Industry 4.0. That information would be stored in a Cloud-Based Design and Manufacturing (CBDM) as well as the real-time operational data. Accessing to that cloud, the design and production engineers can work together to digitally create a product without having to stop the machinery.To implement these concepts, this paper suggests a Digital Twin (DT) to take advantage of the historical information allied to the existent industrial machinery. It suggests a digital twin of a robotic arm with an additive or hybrid manufacturing tool, printing big parts (e.g. garden benches or urban furniture) with reused materials such as tire, cork, wood or stone pow loads.

Intelligent virtual manufacturing cell formation in cloud-based design and manufacturing

Cloud-based design and manufacturing (CBDM) can presumably stimulate greater intelligence in cloud-based models. This paper assumes that cloud-based design for cellular manufacturing can be referred to as a multiscale, uncertain, and dynamic service-oriented network where a set of CAD parts, modelled by set of features, can be manufactured in intelligent virtual manufacturing cells under certain constraints. Using the concepts of the holon and the attractor, integrating the uncertainty in the modelling of part design and part–manufacturing network, an approach to address intelligent virtual manufacturing cell formation in CBDM is proposed. The powerful role of the CAD features is exploited to organize and integrate part design and part–manufacturing engineering knowledge. Intelligent manufacturing features, modelled as fuzzy agents, are recognized in CAD part models and the distributed capabilities of machines in cloud manufacturing are evaluated through mobile intelligent agents. Then, intelligent virtual manufacturing cells, with holonic structure, emerge from the interactions of fuzzy machine holon agents and fuzzy part holon agents with holon agent attractors. The concepts of the holon and the attractor allow multi-scale cell formation with holonic structure: “intelligent virtual manufacturing cells within an intelligent virtual manufacturing cell”. These fuzzy cell holons overcome the distinction continuous–discontinuous of traditional cell design formation problem.

Democratizing digital design and manufacturing using high performance cloud computing: Performance evaluation and benchmarking

Cloud computing is an innovative computing paradigm that can bridge the gap between increasing computing demands in computationally intensive tasks for digital design and manufacturing applications and limited resources, scalability, flexibility, and agility in traditional computing paradigms. In light of the benefits of cloud computing, cloud-based high performance computing (HPC) has the potential to enable users to not only accelerate computationally expensive tasks, but also to reduce costs by utilizing on-demand, ubiquitous, seamless, and user-friendly access to remote engineering application packages as well as remote HPC resources. However, due to uncertainty about computing performance on the cloud, many manufacturers find it challenging to justify and adopt Cloud-Based Design and Manufacturing (CBDM). Therefore, the objective of this research is to evaluate the performance of solving a large-scale engineering problem using finite element analysis on several public HPC clouds as well as introduce a new workflow for CBDM. A set of experiments is conducted to compare the performance of the public HPC clouds with that of a standard workstation and a dedicated in-house supercomputer. The performance metrics include elapsed time, speedup, scalability, and stability. Experimental results have shown that the Azure Cloud with 32 cores and the Nimbix Cloud with 16 nodes speed up the finite element analysis over a workstation with 8 cores by more than seven-fold and eight-fold. A dedicated in-house supercomputer speeds up the finite element analysis over cloud computing by approximately two-fold because of better I/O performance and larger memory. In addition, considerable variations of elapsed time for solving the finite element model with multiple nodes in the cloud were observed due to resource sharing in cloud computing.

Resource allocation in cloud-based design and manufacturing: A mechanism design approach

The focus of this paper is on matching service seekers and service providers, such as designers and machine owners, in cloud-based design and manufacturing (CBDM). In such decentralized scenarios the objectives and preferences of service seekers are different from those of service providers. Current resource configuration methods are unsuitable because they optimize the objectives of only one type of participants – either service seekers or service providers. Existing marketplaces based on first-come-first-serve (FCFS) approach are inefficient because they may not result in optimal matches. To address these limitations there is a need for mechanisms that result in optimal matching considering the private preferences of all the agents. In this paper, we formulate the resource allocation problem as a bipartite matching problem. Four bipartite matching mechanisms, namely, Deferred Acceptance (DA), Top Trading Cycle (TTC), Munkres, and FCFS are analyzed with respect to desired properties of the mechanisms such as individual rationality, stability, strategy proofness, consistency, monotonicity and Pareto efficiency. Further, the performance of these mechanisms is evaluated under different levels of resource availability through simulation studies. The appropriateness of matching mechanisms for different scenarios in CBDM such as fully decentralized, partially decentralized and totally monopolistic are assessed. Based on the analysis, we conclude that DA is the best mechanism for totally decentralized scenario, TTC is most appropriate when cloud-based resources are used in an organizational scenario, and Munkres is the best mechanism when all resources are owned by a single agent.

Software-defined Cloud Manufacturing for Industry 4.0

Many of the world's leading industrial nations have invested in national initiatives to foster advanced manufacturing, innovation, and design for the globalized world. Much of this investment has been driven by visions such as Industry 4.0, striving to achieve a future where intelligent factories and smart manufacturing are the norm. Within this realm, innovations such as the Industrial Internet of Things, Cloud-based Design and Manufacturing (CBDM), and Social Product Development (SPD) have emerged with a focus on capitalizing on the benefits and economies of scale provided by Internet Protocol (IP) communication technologies. Another emerging idea is the notion of software-defined systems such as software-defined networks, which exploit abstraction and inexpensive hardware advancements in an effort to build more flexible systems. Recently, the authors have begun considering how the notion of software-defined systems might be harnessed to achieve flexible cloud manufacturing systems. As a result, this paper introduces the notion of Software-Defined Cloud Manufacturing (SDCM). We describe a basic SDCM architecture based on leveraging abstraction between manufacturing hardware and cloud-based applications, services, and platforms. The goal of SDCM is to advance Cloud-Based Manufacturing and other Industry 4.0 pillars by providing agility, flexibility, and adaptability while also reducing various complexity challenges.

A Cloud-Based Framework for Lean Maintenance, Repair, and Overhaul of Complex Equipment

Large, complex, expensive, and long-lived equipment often operate in harsh environments, which leads to the requirements of lifecycle maintenance, repair, and overhaul (MRO). To support the continuous improvement of productivity and to reduce the cost of MRO, this paper developed a cloud-based framework for lean MRO of the equipment with the aforementioned characteristics. A concept and a model of lean MRO are proposed. Taking advantage of cloud-based design and manufacturing (CBDM) into account, an architectural framework of cloud-based MRO is proposed. A case of a lean MRO for continuous casting equipment demonstrates that the proposed cloud-based framework can achieve the goal of lean MRO of complex equipment.

Economic Benefit Analysis of Cloud-Based Design, Engineering Analysis, and Manufacturing

AbstractFrom a business perspective, cloud computing has revolutionized the information and communication technology (ICT) industry by offering scalable and on-demand ICT services as well as innovative pricing plans such as pay-per-use and subscription. Considering the economic benefits of cloud computing, cloud-based design and manufacturing (CBDM) has been proposed as a new paradigm in digital manufacturing and design innovation. Although CBDM has the potential to reduce costs associated with high performance computing (HPC) and maintaining ICT infrastructures in the context of cloud computing, it is challenging to justify the potential cost savings associated with design and manufacturing because of the complexity in the economic benefit analysis of migrating to CBDM. In response, this paper provides important insights into the economics of CBDM by identifying key cost factors and potential pricing models that can influence decision making on whether migrating to the cloud for computationally expensive analyses that are commonplace for design and manufacturing (e.g., computer-aided design (CAD)/computer-aided engineering (CAE)/computer-aided manufacturing (CAM)) is economically justifiable. This work, for the first time, identifies the key economic benefits required for a comparative study that supports organizations in determining when traditional in-house design and manufacturing versus CBDM is most appropriate. Several comparative case studies and a hypothetical application example are provided to demonstrate and quantitatively validate decision support methods. Finally, key issues and road blocks for CBDM are outlined.

RETRACTED: Cloud-Based Design, Engineering Analysis, and Manufacturing: A Cost-Benefit Analysis

From a business perspective, cloud computing has revolutionized the information and communication technology (ICT) industry by offering scalable and on-demand ICT services as well as innovative pricing plans such as pay-per-use and subscription. Considering the economic benefits of cloud computing, cloud-based design and manufacturing (CBDM) has been proposed as a new paradigm in digital manufacturing and design innovation. Although CBDM has the potential to reduce costs associated with high performance computing (HPC) and maintaining ICT infrastructures in the context of engineering design and manufacturing, it is challenging to justify the potential cost savings associated with HPC in the cloud because of the complexity in the cost-benefit analysis of migrating to CBDM. In response, this paper provides important insights into the economics of CBDM by identifying key cost factors and potential pricing models that can influence decision making on whether migrating to the cloud is economically justifiable. Specifically, the cost breakdown of adopting CBDM is presented. The general key benefits are demonstrated using real case studies. In addition, a hypothetical application example is presented to compare costs in CBDM with that of traditional in-house design and manufacturing. Finally, some of the key issues and road blocks are outlined.

Enhancing the Product Realization Process With Cloud-Based Design and Manufacturing Systems

The rise of cloud computing is radically changing the way enterprises manage their information technology assets. Considering the benefits of cloud computing to the information technology sector, we present a review of current research initiatives and applications of the cloud computing paradigm related to product design and manufacturing. In particular, we focus on exploring the potential of utilizing cloud computing for selected aspects of collaborative design, distributed manufacturing, collective innovation, data mining, semantic web technology, and virtualization. In addition, we propose to expand the paradigm of cloud computing to the field of computer-aided design (CAD) and manufacturing and propose a new concept of cloud-based design and manufacturing (CBDM). Specifically, we (1) propose a comprehensive definition of CBDM; (2) discuss its key characteristics; (3) relate current research in design and manufacture to CBDM; and (4) identify key research issues and future trends.