Design and Simulation of Manufacturing Organizations Based on a Novel Function-Based Concept

Historically, researchers and managers have often failed to consider organizations as a sum of functions leading to a set of capabilities that produce a product that can serve society’s needs. Furthermore, functions have increased with the development of industrial revolutions, however, many manufacturing organizations have not realized their full potential. As a result, many industrial organizations do not know why, where, and when the existing functions and projects for implementing new functions fail where tactical and strategic functions of a manufacturing organization are commonly over-seen. Thus, the aim of this research was to propose a holistic approach for manufacturing organizations in order to model their functions enabling the assessment, design, management, and control of operations and performance as well as to identify improvement potentials. For this purpose, a conceptual model was developed based on the evolution of functions along with the industrial revolutions. Moreover, using the conceptual model, manufacturing organizations can be modeled, considering common organizational functions in the respective areas of production, maintenance, and quality, etc., in the three planning horizons—strategic, tactical, and operative. As a result, the model serves as a basis for the integral management and control of manufacturing organizations. Moreover, it can be also used as a basis framework for a digital twin model for organizations. Thus, a system dynamics simulation model based on the conceptual model was developed for a generic organization. The goal of the simulation model is to provide an exemplary digital model of a manufacturing organization in which the different functions are applied with different methods, systems, and/or individuals along the development phases.

Integrating Non-Destructive Surveys into a Preliminary BIM-Oriented Digital Model for Possible Future Application in Road Pavements Management

The implementation of the digitalization of the linear infrastructure is growing rapidly and new methods for developing BIM-oriented digital models are increasing. The integration of the results obtained from non-destructive surveys carried out along a road infrastructure in a pavement digital model can be a useful method for developing an efficient process from a pavement management systems (PMS) point of view. In fact, several applications to optimize PMS have been thoroughly investigated over the years and several researchers and scientists have investigated significant elements for improving the PMS applied to a transport network, including road infrastructures. This study presents a new, tentative process for implementing into a BIM environment the dataset processed from two surveys carried out in a case study. Moreover, the main reason for this investigation is related to the need for an effective system able to evaluate continuously the pavement conditions and programming maintenance interventions. To date, both the instruments and the methods to detect the pavement configuration have evolved, along with the development of non-destructive technology (NDT) tools such as laser-scanners and ground-penetrating radar. Finally, the main results of the research demonstrate the possibility to provide a digital twin model from the synergistic use of geometric and design information with the results from monitoring conducted on a road infrastructure. The model can be potentially used in future BIM-based PMS applications.

A blockchain-based cooperative modeling method for digital twin ontology model of the mechanical product

With the rapid increase of multi-source heterogeneous dynamic data of mechanical products, the digital twin technology is considered to be an important method to realize the deep integration of product data and intelligent manufacturing. As a digital archive of the physical entity in entire life cycle, the mechanical product digital twin model is cross-phased and multi-domain. Therefore, safe and stable cooperative modeling has become a basic technical problem that needs to be solved urgently. In this paper, we proposed a blockchain-based collaborative modeling method for the digital twin ontology model of mechanical products. First, an authorization network was constructed among stakeholders. Then modeling processes of the digital twin were mapped to ontology operations and formatted through extensible markup language. Finally, consensuses were obtained based on practical byzantine fault tolerance. And a material modification process of a helicopter damper bearing was taken as an example to verify. The proposed method enables all participants to accurately obtain the latest state of the digital twin model, and has the advantages of tamper-proof, traceability, and decentralization.

The Digital Twin for Agricultural Machinery Restoration Processes

Introduction. Agricultural machinery provides the required level of mechanization. Sand abrasive, dirt, and open-air operations considerably accelerate the wear of mechanisms. An improper work plan and lack of complete information about the state of specific equipment units increase the time for repair and maintenance operations. The purpose of the study is to develop a digital twin model for the repair and restoration system of enterprises. The model will reduce material costs and allow for the best solutions to organize the work. Materials and Methods. The model is developed on the basis of simulation modeling. The authors used the approach based on discrete-event modeling with the logical-mathematical apparatus for describing events occurring in a real object. Results. Information support is formed taking into account the parameters of the production systems of repair enterprises and a mathematical model, which is a digital twin of the production system. This approach made it possible to automate the development of optimal plans for organizing repair work by repair enterprises, taking into account their interrelationships. Discussion and Conclusion. The digital twin for the generalized production system of repair organizations allows developing options for the resource allocation and verifying them promptly to choose the best options through accumulating information about the most successful solutions. This will reduce the time for repair and restoration works, improve their quality and save labor.

A Digital Twin Architecture Model Applied with MLOps Techniques to Improve Short-Term Energy Consumption Prediction

Using extensive databases and known algorithms to predict short-term energy consumption comprises most computational solutions based on artificial intelligence today. State-of-the-art approaches validate their prediction models in offline environments that disregard automation, quality monitoring, and retraining challenges present in online scenarios. The existing demand response initiatives lack personalization, thus not engaging consumers. Obtaining specific and valuable recommendations is difficult for most digital platforms due to their solution pattern: extensive database, specialized algorithms, and using profiles with similar aspects. The challenges and present personalization tactics have been researched by adopting a digital twin model. This study creates a different approach by adding structural topology to build a new category of recommendation platform using the digital twin model with real-time data collected by IoT sensors to improve machine learning methods. A residential study case with 31 IoT smart meter and smart plug devices with 19-month data (measurements performed each second) validated Digital Twin MLOps architecture for personalized demand response suggestions based on online short-term energy consumption prediction.

Efficiency Evaluation of the Dual System Power Inverter for On-Grid Photovoltaic System

The implementation of a dual electric system that is capable of operating with either constant current and variable voltage, or constant voltage and variable current appliances, is one of the possible options to solve low-intensity stochastic energy utilization problems from renewable energy sources. This research paper analyzes the potential benefit of a novel three-phase dual system power inverter over the conventional inverter used in a solar power plant. The concept of such a power inverter is explained, and the digital twin model is created in a MATLAB Simulink environment. The efficiency characteristic of the simulated inverter is compared to the efficiency characteristic of a real conventional inverter. A standalone data logging system and an additional data acquisition system were used to collect and process data from the real inverter. Comparison of the digital twin inverter and the real conventional inverter shows the potential benefit of this novel inverter technology. It is shown that the novel inverter can operate in a wider range of DC input power. The potential economic benefit is also presented and discussed in the paper.

Model Construction of Material Distribution System Based on Digital Twin

Aiming at the problems of poor periodicity of workshop material distribution, difficult prediction of station material demand time node and redundant distribution route, this paper proposes a model construction method of material distribution system based on digital twin. Build a material distribution control mode based on digital twin, and establish a full cycle material distribution mechanism on this basis to comprehensively optimize the distribution cycle from the material preparation stage, dynamic replenishment stage and data transmission stage of adjacent distribution cycles. Build the digital twin model of material distribution system, establish the material demand time node prediction operation mechanism based on LSTM, accurately predict the station material demand time node, establish the material distribution route optimization model with the lowest total cost, and optimize the AGV route. Finally, it is applied to the asynchronous card line workshop of A enterprise to verify the effectiveness of this method.