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Since the manufacturing process information and their mutual relationship are complex and diverse, the clear and accurate description and modeling of manufacturing process information is a challenge in related study of manufacturing process. Considering the diversity of the process data, a four-layer framework for manufacturing process information...
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... Metamodel is a generalized description of the manufacturing process information, so it has a wider application range, and adapts to more application scenarios, which requires better completeness and generality in description of manufacturing process information. Figure 1 shows the four-layer framework of manufacturing process information modeling based on metamodel, including the meta-metamodel layer, metamodel layer, model layer and data layer. The structure and the mutual relationship between different layers of the framework are demonstrated. ...
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Automation of any business process primarily requires the identification of clear and precise requirements. However, the initially collected business requirements are usually expressed in natural language that create ambiguities among different stakeholders. To overcome this problem, various BPML’s (Business Process Modeling Language) have been int...
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... The metamodel describes the common syntax, semantic, or structural features of a class of models, which provides elements to establish a unified and standard workflow system for the assembly process. Yang et al. [23] proposed a manufacturing process information modeling method based on metamodel, considering the diversity of the process data. The modeling framework completes the process planning and provide a detailed metamodel guidance to manufacturing process modeling implemented by unified modeling language to express the mechanism information. ...
Human–robot collaborative assembly (HRCA) is one of the hot trends in intelligent manufacturing and has gained the attention of many researchers. In HRCA, errors in assembly sequence may reduce working efficiency and damage workpieces. To detect the assembly sequence errors rapidly and not influence the assembly process, the assembly sequence monitoring system demands high real-time performance and non-contact requirements. Therefore, an assembly sequence monitoring method based on workflow modeling is proposed for HRCA. The framework of the monitoring method is divided into an assembly state recognition block, an action library, and a monitoring block. The assembly state recognition block characterizes the complicated and unstructured assembly environment as a state vector in real time. The action library is constructed to model the workflow of the assembly sequences. The monitoring block matches the state-change vector calculated from the state vectors with defined actions in the action library and outputs the monitoring result. The assembly state recognition block is tested in simulation, and the assembly sequence monitoring method is validated in simulation and real-world experiments to exhibit the effectiveness. The comparison with other similar methods illustrates the superiority in monitoring range and recognition accuracy.
... Another way to overcome existing contradictions is to im prove the structure of models or develop new metamodels. In [10], a fourlevel structure is proposed for modeling informa tion about the production process based on a metamodel. However, the proposed metamodel does not fully describe a system with four elements of subsystems, where each element of the subsystem has five possible states. ...
Purpose. Study on the process of combining several methods for determining the quality indices of human-machine interaction, containing various configurations for determining the weight coefficients in an ensemble. Methodology. The process of diagnosing the quality of the interaction of a human-machine system with four elements of subsystems is studied using the example of the system “Operator–Machining Center – Control Program – Safe Environment”. The main hypothesis of the study is the combination of several methods for determining the quality indices of human-machine interaction, containing different configurations for determining the weight coefficients in the ensemble. A combined method for diagnosing the quality of interaction between human-machine systems based on ensemble models, which include non-ensemble ones, has been proposed. The ensemble index has been determined by averaging the non-ensemble indices. The defined ensemble indices and element scores of the four subsystems are used as input scores to a multiple regression model to generate prediction. Findings. Four combinations of ensemble indices have been developed and implemented in software, which are characterized by a minimum value of the standard deviation compared to the existing ones. According to the results of experimental verification, the proposed models demonstrate the value of the standard deviation of 0.1404; 0.1401; 0.1411; 0.1397, and the existing ones are 0.1532; 0.1535; 0.1532; 0.1532. Originality. The combined ensemble method for diagnosing the quality of interaction between elements of subsystems takes into account linear models with non-linear variables and different ways of determining weight coefficients. Practical value. The scenario for the practical use of the results obtained is a possible option for optimizing production, where, depending on the final result, specialists can adjust the value of a particular subsystem to achieve the desired result.
... They give a comprehensive overview of relevant classes and their interconnection, but not in a standardized manner. Other models of the manufacturing domain in general were made in [42][43][44][45]. ...
The use of digital technologies in the industrial environment enables great potential for increasing efficiency in manufacturing. One building block are production environments that plan and control their production flow autonomously and decentrally. To this end, all machines and systems (so-called ‘‘assets’’) need to communicate with each other and derive suitable actions based on the exchanged information. Therefore, all assets need to be represented in the virtual world. This can be realized with digital twins. A concrete implementation of digital twins is the asset administration shell, which comprises all the assets’ properties and the endpoint of the corresponding asset, so intercommunication is possible. Here, the challenges comprise establishing a manufacturer-independent vocabulary that standardizes the assets’ properties and enabling the machines and systems to interpret this vocabulary semantically. Existing standards and information models represent only a fraction of the information requirements (i.e., terms) in this domain, making autonomous production planning and control (PPC) challenging to implement. Furthermore, the information requirements of the machines and peripheral assets as well as the corresponding information flows are insufficiently defined. Therefore, this contribution aims to build a comprehensive vocabulary for the domain of PPC, which serves as a basis for standardized asset administration shells that realize machine-to-machine communication. In particular, PPC processes concerning the injection molding domain’s characteristics are considered since the interaction between the domain’s assets, i.e., injection molding machines, molds, peripheral assets, raw materials, and operators, are especially complex. For this purpose, the relevant input and output information within the injection molding domain was first collected for each process step in PPC. After that, a UML class diagram was modeled under consideration of established standards. The result of this work is an ontology, which can be used as a dictionary for the PPC in the injection molding domain and as a foundation of standardized digital twins in the form of asset administration shells.
... The use of information modeling [17] and digital tools [18] is becoming increasingly important in the activities of leading industrial enterprises. At the same time, the leading role is given to improving communication between modern equipment and maintenance personnel using digital means. ...
The paper is devoted to the disclosure the construction of the SCADA system for managing the operating modes and monitoring the electric drive of the overhead crane. The material is provided in the form of step-by-step instructions for building such a system in the Vijeo Designer program. The creation of a new project, interface elements, binding variables with interface elements, setting the behavior of dynamic interface elements are shown in detail. The issue of communication of global variable visual elements of the interface with the M241 controller and the program in SoMachine has been revealed. The developed interface allows to control three mechanisms of the bridge crane: main hoist, auxiliary hoist and carriage movement. It is shown how to control frequency converters that are connected to the controller through different types of communication: direct analog to the controller, and through the Ethernet/IP protocol. The work will be useful for academic purposes in teaching students as well as for researchers and industrial engineers.
... The M0 layer describes how knowledge related to tactical activities is structured (Inan, Beydoun, and Pradhan, 2018). The M0 layer consists of the input, production, and output data of the digital process planning system (Yang et al., 2016). It is an instance of the model and directly interacts with the system users (Yang et al., 2016). ...
... The M0 layer consists of the input, production, and output data of the digital process planning system (Yang et al., 2016). It is an instance of the model and directly interacts with the system users (Yang et al., 2016). In this case, the M0 layer refers to real-world data, that is, landslides data. ...
According to the United Nations (UN) World Risk Index 2020, Malaysia is at high risk of natural catastrophes and is highly exposed to them, but has a low vulnerability to them. This is due to Malaysia's geographical location at the edge of the Pacific Ring of Fire, which makes it relatively secure from earthquakes and volcanic eruptions. Large-scale landslides continue to occur in the country, mainly during the monsoon season. Landslide disasters in Malaysia are managed by several entities, coordinated by The National Disaster Management Agency (NADMA) where each entity has its particular landslide disaster management practices. Therefore, several concerns remain, such as inadequate documentation and decentralization of standards of procedure (SOP). This paper presents an implementation review of the current landslide risk register, focusing on the geospatial metamodel approach. A risk register is an active document that lists all the identified hazards in a region and the decisions taken to monitor and manage them. Initially, preliminary studies were conducted to identify the current practices of landslide disaster management in Malaysia. These include collecting geospatial data, such as LiDAR, aerial photographs (AP), existing landslide inventory maps, and SOPs for landslide non-structural mitigation activities. The geospatial metamodel consists of the concept and the relationship, which describes the domain with an additional geospatial element. To conclude, a risk register using the geospatial metamodel approach would enable NADMA to monitor and coordinate the landslide disaster management process more effectively.
... A possible way to sort the required data of the production process is displayed in Fig. 5. Guidance for the development of a suitable data structure can be found in [8], [9] and [10]. Data for the description of the manufacturing process can be assigned to the part, to the manufacturing activity or to the machine. ...
The purpose of this work is to point out the importance of the production phase for the carbon footprint calculation of powertrain components and to improve the understanding of necessary data for this calculation. Evaluation of lifecycle assessment data from numerous studies showed, that there is often a shift from the emissions in the use phase to emissions in the production phase, when alternative powertrain concepts are used. Therefore, in this work our focus is on the carbon emissions in the production phase of powertrain components. Data of raw materials used, production processes and supply chains is necessary and the uncertainties associated also have to be considered. At present, there is only little sufficient support for design engineers regarding the collection of relevant data for the carbon footprint calculation of pow-ertrain production. In this work a data structure, which supports the collection of relevant data, including possible data sources, is presented.
It is critical to capture and share product manufacturability knowledge along with manufacturing operations and their sequences to enhance the competitiveness of manufacturing enterprises. The developed approaches have proven to be expensive and time consuming. In this paper, a new core manufacturing ontology is developed to model manufacturing operations, sequence knowledge and make it easily shareable. The ontological approach involves identification and definition of a core set of concepts with relations to develop the hierarchical structures of manufacturing models. The ontological model is then formalised through the Web Ontology Language (OWL) whilst formal axioms and rules are written in the Semantic Web Rule Language (SWRL). The model was validated in an industrial environment via collaboration with one of the largest aero engine manufacturing companies. The generic nature of the proposed model renders that it is capable of capturing manufacturing operations and their sequences into proper categorisation. The multifaceted capability of the ontological model can greatly facilitate manufacturing engineers in decision making for new product manufacturing planning.
Model-based systems engineering (MBSE) plays a vital role in complex product development. In order to make the system modeling processes consistent with the business processes of the industry, it is necessary to use the product lifecycle management (PLM) system to manage system models. In this paper a SysML-based domain specific meta-model is proposed to support a visualization framework that includes graphics and data synchronization, which enables PLM software to present the product manufacturing data and models under the practicing of MBSE. Product manufacturing process and data are described, and the allocation of resource is represented in the early design phase.
