Cloud-based Manufacturing Research Articles

Cloud Usage for Manufacturing: Challenges and Opportunities

Due to its potential to improve agility, efficiency, innovation, and global collaboration, cloud manufacturing is probably going to be an essential part of the manufacturing sector in the future. In a manufacturing environment that is becoming more and more competitive and changing quickly, businesses that strategically use cloud technologies could effectively broaden their capabilities. This research review demonstrates the possible development of cloud computing transformative effects on the manufacturing sector and highlights the advancements in cloud usage for manufacturing. The research examines various manufacturing uses for cloud computing, including cooperative production, data management, analytics, process optimization, and supply chain management. It also delves into some disadvantages of using the cloud in the manufacturing industry and estimates future developments in cloud-based manufacturing solutions. Finally, a simple use case is shown, using a typical commercial application.

Column generation for service assignment in cloud-based manufacturing

Cloud-based manufacturing has gained significant attention in academia and industry, presenting opportunities for enhanced operational efficiency. This paper addresses two critical challenges in cloud manufacturing: service assignment and transportation within hybrid hub-and-spoke networks. We propose a novel approach to minimize the total cost, encompassing manufacturing and transportation costs, through a mixed integer programming model and a column generation-based algorithm. Numerical experiments are conducted to validate the efficacy of the proposed model and algorithm, considering different system sizes. The results demonstrate the tangible benefits of our approach. By introducing a hybrid hub-and-spoke network, we achieve a substantial average reduction of 7.46% in the total cost of the cloud manufacturing system. Furthermore, our proposed algorithm outperforms existing methods such as Particle Swarm Optimization (PSO) and CPLEX. Particularly, in large-scale instances where CPLEX fails to solve, our algorithm outperforms PSO by an additional 3.43% in terms of cost reduction. Moreover, sensitivity analysis provides valuable insights for cloud manufacturing, contributing to its effective implementation.

TÜRKİYE’DE BT KARAR VERİCİLERİN BULUT ÜRETİMİN KABUL EDİLMESİNE İLİŞKİN GÖRÜŞLERİNİN ORTAYA KONMASI

Cloud manufacturing has emerged as a breakthrough of IT services, including the internet of things (IoT) and artificial intelligence (AI) for business processes in the manufacturing sector. It has also brought the need to complete the integrated business processes such as an integrated supply chain, inventory management, and production for utilizing this technology. In this context, IT decision-makers attempt to develop a cloud-based manufacturing model for downloading, configuring, and maintaining machinery from cloud providers that enables the top managers just to focus on their product in business. The research aims to build for monitoring the differences between cloud manufacturing adopters and non-adopters to understand the behavioral intention by monitoring the Diffusion of Innovation (DOI) theory and the Technological, Organizational, and Environmental (TOE) theory of cloud manufacturing adoption. An independent t-test sample was used to analyze data. 19 manufacturing cloud adopters and 19 non-cloud adopters were selected to analyze data via SPSS 26.0 in Turkey. The results exhibited that manufacturing cloud adopters and non-cloud adopters considered the same for relative advantage, cost-saving, competitive pressure, and regulatory support. However, they found differences in security concerns, compatibility, complexity, technological readiness, and top management support. The study brought an outlook for understanding the benefits, drawbacks, and hinders of cloud manufacturing of manufacturers. This will enable comprehensive information for cloud providers to offer appropriate integrated software according to manufacturers’ needs of the production.

Resource scheduling in cloud-based manufacturing system: a comprehensive survey

Resource scheduling in cloud-based manufacturing system: a comprehensive survey

Review of Smart Contracts for Cloud-Based Manufacturing

Review of Smart Contracts for Cloud-Based Manufacturing

Allocation and scheduling of digital dentistry services in a dental cloud manufacturing system

ABSTRACT Recent enhancements in computer aided design and manufacturing have made dentistry workflow more effective. Dental products are highly customized and personalized for patients. So, they require manufacturing processes for flexibility and agility and fulfilling requirements like quality, delivery time and cost. Various types of scanners, design software and production devices are used by stakeholders in digital dentistry. Also, other stakeholders such as dentists, dental surgeons and lab technicians work together to respond to patient demands to produce the required products while they are distributed in different geographical locations. This paper introduces a new practical and multidisciplinary contribution named as personalized dental production system. The system uses the cloud-based manufacturing paradigm to shape the collaborative workflow of medical manufacturing processes. This workflow is modeled using XaaS (Everything as a Service) approach and addresses limitations such as delivery time and cost of production services. A new mathematical model is developed to allocate and schedule all tasks to providers. The developed model allocates and schedules tasks to providers considering services composing and orders decomposing simultaneity. To response NP-hard challenges of the mathematical model, a new algorithm is proposed. The results show that the proposed algorithm generates appropriate solutions within a reasonable time.

Editorial: Security of cloud service for the manufacturing industry

With the rapid development of the industrial Internet, cloud service-based manufacturing has emerged as a next generation manufacturing paradigm that has potential to revolutionize the manufacturing industry. It is foreseeable that cloud services will be popular in the next generation manufacturing industry. In recent years, more and more manufacturing companies have recognized the benefits of cloud service and have developed cloud-based manufacturing models. However, the security problems need to be researched and solved for the cloud services in the manufacturing industry, especially the data security issues are important, and restrict the cloud application in the manufacturing industry. Regarding the security of data, some people believe that when data are stored in the cloud, manufacturing companies lose control of the data. The manufacturing companies focus on how to secure the data from the top-level management and how to minimize the security risks, such as those caused by data security or service migration challenges. The manufacturing companies select the reliable cloud service while consider function and budget feasibility. How to ensure security in cloud service for the manufacturing industry has become a topic of increasing interest for both academic researchers and developers from the industry. This special issue addresses this emerging and fast developing research area on cloud security in manufacturing industry. The summary of these papers is as follows. [...]

RETRACTED ARTICLE: Secure access control for manufacturing sector with application of ethereum blockchain

Past local and worldwide international logistic operations have been related with obscure data streams that have thwarted detectability and made obstacles in deregulation. Ethereum based Distributed Ledger Technology and unified advancements were explored for solving the issues looked of Cloud-Based Manufacturers. Nonetheless, past writing has zeroed in on restricted parts of a regular Cloud-Based Manufacturing chain, for example, checking resources and making sure about discernibility, which is generally dismissing information trustworthiness and information access. To conquer such disadvantages, the current study attempts to protected keen agreements dependent on ERC20 interface of controlled Ethereum based Distributed Ledger Technology with significant cycles and capacities to get an all encompassing structure for making sure about Cloud-Based Manufacturing activities. The adequacy was exhibited on the study. So, it was discovered that basic escape clauses in blockchain can be beaten utilizing the prototyped structure. Also, a few blueprints for future examination are plot.

Cloud manufacturing service composition in IoT applications: a formal verification-based approach

Nowadays, one of the new solutions to develop Internet of Things (IoT) applications is cloud manufacturing. By increasing the number of actuators, industrial devices and sensors in industry 4.0 technology, the IoT is going to improve the intelligence of the enterprise information systems with a fast transition towards flexible, smarter, automated and reactive services. In order to respond the needs more quickly or matching the cloud services with modified requirements, cloud manufacturing service composition is used to take advantage of several services available in the Industrial IoT applications. The cloud-based manufacturing services can be characterized, published, shared, and retrieved over the cloud infrastructure to provide integrated services according to the user QoS requirements in a collaborative environment. In this work, a service composition approach is provided for cloud manufacturing in IoT applications. For evaluating the correctness of the proposed solution, a formal verification method is presented based on Labeled Transition System (LTS). Also, Whale Optimization Algorithm (WOA) is utilized to enhance the Quality of Service (QoS), when the number of cloud services have been increased. Finally, deadlock-free and reachability factors as important logical problems are satisfied in verification of the proposed approach. The verification results obtained under different Linear Temporal Logic (LTL) properties and various number of cloud providers indicate that the proposed approach is a correct and valid solution and it outperforms in terms of the reachability, verification time, deadlock, and memory usage.

Using machine learning for service candidate sets retrieval in service composition of cloud-based manufacturing

Using machine learning for service candidate sets retrieval in service composition of cloud-based manufacturing

A two-stage mechanism for production planning and revenue allocation in a cloud-based manufacturing environment

This study targets on a Cloud-based Manufacturing (CM) environment composed of a coordinator and multiple companies and proposes an efficient production planning and fair revenue allocation method named Scheduling Auction based Cooperative Game (SACG). In the CM environment, participating companies share their resources and trade the right of using them. Thus, some companies are buyers and others are sellers of the right. When the demand amount is more than the supply amount, the coordinator has to choose which buyers’ requests to accept under the constraint of the total available capacity of the supplied resources and allocate the buyers to the sellers. When there are multiple sellers, the coordinator has to distribute revenue to them. SACG proposed in this paper consists of two parts. The first one is an auction to establish a production plan maximizing the social surplus and determine the contract price of each buyer. The second one is a cooperative game to distribute the whole sales income to the sellers according fairly to their contribution. Numerical experiments illustrate some basic characteristics of the proposed SACG.

Pelatihan Tech for Kids Memperkenalkan STEM untuk Mengembangkan Kemampuan Kepemimpinan Siswa di Era Industri 4.0

The industry is currently undergoing a transformation towards full digitization and intelligence of the manufacturing process, which is called the Fourth Industrial Revolution or Industry 4.0. Visionary but fairly realistic concepts such as Internet of Things, Cloud-based Manufacturing and Smart Manufacturing applications. Although there is mutual agreement on the need for advancement in production technology and business models in the Industry 4.0 sense, the main obstacle lies in the perception of complexity and abstractness which partially hinders its rapid transformation into industrial practice. The term "STEM education" refers to teaching and learning in the fields of science, technology, engineering and mathematics. Usually includes educational activities at all grade levels starting from the period before entering school to higher education, from formal arrangements in the classroom to informal such as after school programs. Student leadership means students take an active role in their education and develop positive skills in the process. The goal of inspiring student leaders is to create a culture of ownership and collaboration. Student leadership development helps create skills that students can carry into adulthood. With this background, community service activities were carried out by providing STEM skills training to foster the leadership of the students of Madrasah Ibtidaiyah Raudhatul Qur'an Tanjungpinang in preparing for the era of the industrial revolution 4.0. This training is also known as Tech for Kids.

Construction of a cloud-based mold manufacturing system based on JAFMAS

Molds are the basis of manufacturing of other products, and thus have higher requirements and more complex design processes than other products. Therefore, studying the technologies used in mold production is necessary. This paper aims to build a cloud manufacturing system of mold manufacturing enterprises based on the Java-based agent framework for multi-agent systems (JAFMAS). Specifically, according to the operation characteristics of different cloud-based manufacturing enterprises, this paper first made in-depth analysis of the cloud manufacturing and multi-agent technology, and put forward a hierarchical model of cloud manufacturing system based on multiple agents. Then, as per the structure of the agents and JAFMAS, the interaction and collaboration mechanism between agents in the system were analyzed to establish the functions of the cloud-based mold manufacturing system, thereby building a cloud-based manufacturing system for mold manufacturers based on JAFMAS.

Competence and readiness of small and medium industries against of industrial revolution 4.0

Small and Medium Industry (SMI) is one of the strategic business sectors that is very influential in the industrial revolution 4.0. Industry 4.0 refers to the concept of using the internet of things, as well as smart and cloud-based manufacturing. The SMI constraints from the knowledge, skills, use of technology, so that needed the competence and readiness of Small and Medium Industries in the Industrial Revolution 4.0. This study examines the level of SMI Competence and SMI Readiness in facing the Industrial Revolution 4.0. The design and model of this study were developed using TRA. The development of this model was carried out in three stages. The purpose of the conceptual is to explain and analyze the description of the Small and Medium Industry Competency variables and the readiness of small and medium industries. The results of the conceptual about the indicators of each variable that will be used in further research.

Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology

Blockchain technology has been enjoying rapid development in numerous areas where trust, safety, and global payments are deemed important. In this research, we introduce a framework that integrates blockchain technology with the emerging concept of cloud manufacturing. It has the potential to dramatically improve the feasibility and applicability of cloud manufacturing. Our focus is on the pricing strategies for service providers in bidding for jobs in such a system. A scenario is developed based on cloud additive manufacturing services. A game theoretic approach for pricing simulation is proposed in the research, and a fuzzy algorithm is employed in the pricing decision. Two pricing policies are considered: one is that the information of players is unknown to each other, and the other is that the information of players who are within a limit of Euclidean space is known to each other. The effects of system load and the weight coefficients in KNN recommendation algorithm are also studied. The results show that the pricing policy has significant effect on revenue generation for providers, and the increase of system load helps to grow revenue for providers only when the machine utilization is low and job waiting time is short. In addition, the system seems to be less sensitive to the change of KNN weights in terms of individual provider and system revenues.

A Cloud-Based Research and Learning Factory for Industrial Production

The Digital Factory Vorarlberg is the youngest Research Center of Vorarlberg University of Applied Sciences. In the lab of the research center a research and learning factory has been established for educating students and employees of industrial partners. We devised learning scenarios and developed courses addressing a wide variety of topics related to Industry 4.0 and showcase best practice scenarios for various topics of digitalization. In addition, novel methods and technologies for digital production, cloud-based manufacturing, data analytics, IT- and OT-security or digital twins are being developed. A centralized SCADA (Supervisory Control and Data Acquisition)-System is the core data hub for the factory. As an alternative to on premise manufacturing, orders can be pushed into a cloud-based manufacturing platform, which has been developed at the Digital Factory. In this paper, we present the basic concept of the Digital Factory Vorarlberg, some of the newly developed topics as well as learning scenarios for students and industry staff.

Artificial Intelligence-based Decision-Making Algorithms, Industrial Big Data, and Smart Connected Sensors in Cloud-based Cyber-Physical Manufacturing Systems

Artificial Intelligence-based Decision-Making Algorithms, Industrial Big Data, and Smart Connected Sensors in Cloud-based Cyber-Physical Manufacturing Systems

Schematizing Insured Healthcare Dossiers in Cloud using Blockading Maneuver Sequence Amplification (BMSA)

Blockade technology in healthcare industry captures the focus in the newfangled years. As a major development it has resulted in the inclusion even in marketing commerce. This progression has enriched the user preoccupied with pharmaceutical sector consequently endorsing possible manipulations and potentials. This conduct in blockading maneuver is done by calculating total file numerals through tokenization which subsequently processed by encryption. Whereas Cloud-Based Manufacturing delegates on-demand ingress to manufacturing stratagems, a reliable emissary is required for transactions between the users who aspire to suffice manufacturing services. Therefore it results in counting to the lines that are availed in an indicted block by the usage of that exacting value derived by division. The health records enclosed in a block is encrypted by blockading maneuver accordingly. In the previous works only permission is accessed to the user and encrypts the whole file. This concept of blockage advances in displaying contents in attendance and also permits to read the intact block. The files are stocked up in a block to encrypt them each. This method in endowing two strategies upshots in reducing decryption time. Ensuring data availability and uploading data by the user in encrypted form is scrutinized as a chief component in this line of attack.

Schematizing Insured Healthcare Dossiers in Cloud using Blockading Maneuver Sequence Amplification (BMSA)

Blockade technology in healthcare industry captures the focus in the newfangled years. As a major development it has resulted in the inclusion even in marketing commerce. This progression has enriched the user preoccupied with pharmaceutical sector consequently endorsing possible manipulations and potentials. This conduct in blockading maneuver is done by calculating total file numerals through tokenization which subsequently processed by encryption. Whereas Cloud-Based Manufacturing delegates on-demand ingress to manufacturing stratagems, a reliable emissary is required for transactions between the users who aspire to suffice manufacturing services. Therefore it results in counting to the lines that are availed in an indicted block by the usage of that exacting value derived by division. The health records enclosed in a block is encrypted by blockading maneuver accordingly. In the previous works only permission is accessed to the user and encrypts the whole file. This concept of blockage advances in displaying contents in attendance and also permits to read the intact block. The files are stocked up in a block to encrypt them each. This method in endowing two strategies upshots in reducing decryption time. Ensuring data availability and uploading data by the user in encrypted form is scrutinized as a chief component in this line of attack.

On Secured Blockchain Technology For K-Nearest Neighbors Algorithm

This paper proposes a cloud-based manufacturing knowledge sharing system for injection mould redesign (IMR) in perspective on square chain development. In our proposed structure, private cloud is connected to spare the IMR becoming more acquainted with, and square chain offers measures and shows to completing the system similarly as making certain the wellbeing in a trustless space. k-Nearest colleagues is connected for convalescing the square chain-essentially based report becoming more acquainted with. The proposed system not solely can energize imbuement structure supplant, yet further give a component to data proprietors to share their own special favorable circumstances adequately.