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The lack of reference architecture for Internet of Things (IoT) modeling impedes the successful design and implementation of an IoT-based production logistics and supply chain system (PLSCS). The authors present this study in two parts to address this research issue. Part A proposes a unified IoT modeling framework to model the dynamics of distributed IoT processes, IoT devices, and IoT objects. The models of the framework can be leveraged to support the implementation architecture of an IoT-based PLSCS. The second part (Part B) of this study extends the discussion of implementation architecture proposed in Part A. Part B presents an IoT-based cyber-physical system framework and evaluates its performance. The paper aims to discuss this issue.

This paper adopts a design research approach, using ontology, process analysis, and Petri net modeling scheme to support IoT system modeling.

The proposed IoT system-modeling approach reduces the complexity of system development and increases system portability for IoT-based PLSCS. The IoT design models generated from the modeling can also be transformed to implementation logic.

The proposed IoT system-modeling framework and the implementation architecture can be used to develop an IoT-based PLSCS in the real industrial setting. The proposed modeling methods can be applied to many discrete manufacturing industries.

The IoT modeling framework developed in this study is the first in this field which decomposes IoT system design into ontology-, process-, and object-modeling layers. A novel implementation architecture also proposed to transform above IoT system design models into implementation logic. The developed prototype system can track product and different parts of the same product along a manufacturing supply chain.

The purpose of this paper is to conceptualize data quality (DQ) in the context of business process management and to propose a DQ oriented approach for business process modeling. The approach is based on key concepts and metrics from the data quality management domain and supports decision‐making in process re‐design projects on the basis of process models.

The paper applies a design oriented research approach, in the course of which a modeling method is developed as a design artifact. To do so, method engineering is used as a design technique. The artifact is theoretically founded and incorporates DQ considerations into process re‐design. Furthermore, the paper uses a case study to evaluate the suggested approach.

The paper shows that the DQ oriented process modeling approach facilitates and improves managerial decision‐making in the context of process re‐design. Data quality is considered as a success factor for business processes and is conceptualized using a rule‐based approach.

The paper presents design research and a case study. More research is needed to triangulate the findings and to allow generalizability of the results.

The paper supports decision‐makers in enterprises in taking a DQ perspective in business process re‐design initiatives.

The paper reports on integrating DQ considerations into business process management in general and into process modeling in particular, in order to provide more comprehensive decision‐making support in process re‐design projects. The paper represents one of the first contributions to literature regarding a contemporary phenomenon of high practical and scientific relevance.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

Complex system modeling requires not only understanding of modeling framework but also domain knowledge of the system. The purpose of this paper is to present an approach which separates the domain knowledge from the modeling framework with different views.

By establishing the mechanism of association and fusion among the views, the description and characterization of system from different aspect and point of view can form a complete system model. Based on the approach, a modeling and simulation (M&S) platform named SimFaster is developed. Modeling environment and simulation engine are the most important parts of the platform. The modeling environment provides multi‐views and multi‐layers to help the developers to modeling the structure, layers, composition, behavior, and interactions of an application system. The simulation engine provides mechanism of integration and interaction for components and objects, and provides runtime support for the concepts and terms from modeling environment. The simulation engine organizes the objects in the memory of distributed system as reflective object database system, so it is repository centered architecturally.

Based on the approach of multi‐views modeling, the platform is a flexible framework and supports top‐down design, model reuse and interoperation, dynamic refinement of models, corporative design among different users in different stages, and the rebuilt of application rapidly.

This paper deals with high‐level models of the complex systems.

This platform helps to design, modeling, and simulation complex system (especially for weapon combat system). It can participate into all the stages of the development of complex product/system, and can support the validation, refinement, optimization of models, and systems.

This paper presents a multi‐views modeling approach for the modeling of complex system.

The purpose of this paper is to review the available reduced order modeling approaches in the literature for predicting the flow and specially temperature fields inside data centers in terms of the involved design parameters.

This paper begins with a motivation for flow/thermal modeling needs for designing an energy‐efficient thermal management system in data centers. Recent studies on air velocity and temperature field simulations in data centers through computational fluid dynamics/heat transfer (CFD/HT) are reviewed. Meta‐modeling and reduced order modeling are tools to generate accurate and rapid surrogate models for a complex system. These tools, with a focus on low‐dimensional models of turbulent flows are reviewed. Reduced order modeling techniques based on turbulent coherent structures identification, in particular the proper orthogonal decomposition (POD) are explained and reviewed in more details. Then, the available approaches for rapid thermal modeling of data centers are reviewed. Finally, recent studies on generating POD‐based reduced order thermal models of data centers are reviewed and representative results are presented and compared for a case study.

It is concluded that low‐dimensional models are needed in order to predict the multi‐parameter dependent thermal behavior of data centers accurately and rapidly for design and control purposes. POD‐based techniques have shown great approximation for multi‐parameter thermal modeling of data centers. It is believed that wavelet‐based techniques due to the their ability to separate between coherent and incoherent structures – something that POD cannot do – can be considered as new promising tools for reduced order thermal modeling of complex electronic systems such as data centers

The paper reviews different numerical methods and provides the reader with some insight for reduced order thermal modeling of complex convective systems such as data centers.

Financial information about costs and return on investments are of key importance to strategic decision making but also in the context of process improvement or business engineering. The purpose of this paper is to propose a value‐oriented approach to business process modeling based on key concepts and metrics from operations and financial management, to aid decision making in process re‐design projects on the basis of process models.

The paper suggests a theoretically founded extension to current process modeling approaches, and delineates a framework as well as methodical support to incorporate financial information into process re‐design. The paper uses two case studies to evaluate the suggested approach.

Based on two case studies, the paper shows that the value‐oriented process modeling approach facilitates and improves managerial decision making in the context of process re‐design.

The paper presents design work and two case studies. More research is needed to more thoroughly evaluate the presented approach in a variety of real‐life process modeling settings.

The paper shows how the approach enables decision makers to make investment decisions in process re‐design projects, and also how other decisions, for instance in the context of enterprise architecture design, can be facilitated.

This paper reports on an attempt to integrate financial considerations into the act of process modeling, in order to provide more comprehensive decision‐making support in process re‐design projects.

Ubiquitous web applications (UWA) are a new type of web applications which are accessed in various contexts, i.e. through different devices, by users with various interests, at anytime from anyplace around the globe. For such full‐fledged, complex software systems, a methodologically sound engineering approach in terms of model‐driven engineering (MDE) is crucial. Several modeling approaches have already been proposed that capture the ubiquitous nature of web applications, each of them having different origins, pursuing different goals and providing a pantheon of concepts. This paper aims to give an in‐depth comparison of seven modeling approaches supporting the development of UWAs.

This methodology is conducted by applying a detailed set of evaluation criteria and by demonstrating its applicability on basis of an exemplary tourism web application. In particular, five commonly found ubiquitous scenarios are investigated, thus providing initial insight into the modeling concepts of each approach as well as to facilitate their comparability.

The results gained indicate that many modeling approaches lack a proper MDE foundation in terms of meta‐models and tool support. The proposed modeling mechanisms for ubiquity are often limited, since they neither cover all relevant context factors in an explicit, self‐contained, and extensible way, nor allow for a wide spectrum of extensible adaptation operations. The provided modeling concepts frequently do not allow dealing with all different parts of a web application in terms of its content, hypertext, and presentation levels as well as their structural and behavioral features. Finally, current modeling approaches do not reflect the crosscutting nature of ubiquity but rather intermingle context and adaptation issues with the core parts of a web application, thus hampering maintainability and extensibility.

Different from other surveys in the area of modeling web applications, this paper specifically considers modeling concepts for their ubiquitous nature, together with an investigation of available support for MDD in a comprehensive way, using a well‐defined as well as fine‐grained catalogue of more than 30 evaluation criteria.

The purpose of this paper is to conveniently and accurately design partial knitting knitted fabrics based on matrix transformation.

Using mathematical modeling, the pattern diagram block matrix and process design matrix of partial knitting knitted fabrics are established, and the process knitting diagram with parameter information is generated. Based on the establishment of the mathematical model of the process knitting diagram, a loop deformation method based on three-dimensional (3D) coordinate point matrix transformation is proposed.

The matrix transformation method can provide a suitable deformed loop mode for partial knitting knitted fabrics and helps to generate a 3D modeling diagram conveniently.

This paper proposed a method of design and modeling of partial knitting knitted fabric based on matrix transformation. Taking the 3D modeling effect of conventional partial knitting as an example to test the modeling method, the results show that after matrix transformation, the loop model can realize the rapid transformation and calculation of the coordinates of the control point and generate a 3D modeling diagram.

This paper aims to provide a design of intelligent model‐based topology analyzer that can be used to improve plant operation.

POOM process modeling methodology is proposed to model and partition plant topology so that plant operation can be designed in effective manner as mapped to plant topology partitions. Plant topology is divided into areas based on the operation required and material flow and isolation paths are identified automatically using intelligent algorithm.

It is possible to define hierarchical plant structure (topology) partitions that can be mapped to plant operation levels, which are described by ANSI/ISA‐S88. In addition, the use of design knowledge can be useful to define conceptual partitions such as Block, which is essential to link design and operation knowledge. Plant operation (jobs) can be flexibly defined in view of plant structure partitions in terms of resources (materials, plant structural areas) required and operation scheduling.

It is important to link to production scheduling to ensure effective use of topology partitions in real time based on available resources. The proposed approach can be improved via the integration with intelligent production scheduling.

Production and manufacturing plants will be able to use the proposed approach to design and validate plant operation and to improve plant maintenance while reducing operation risks by identifying plant structures required for each operation task. The proposed technique can be helpful to engineers and R&D members to consider in their design and investigation for process safety, risk management, and plant operation and management.

The idea of topology analysis is quite new where it is usually implemented using search algorithms without considering domain knowledge and operation structures. This paper proposes a valuable technique to link plant structure with plant operation hierarchies, which is important for design and engineering practices and R&D activities for plant operation.

This paper presents a versatile and economical knowledge‐based assembly design of blade and shell assemblies by employing behavioral modeling concepts. Behavioral modeling is a new generation CAD concept aimed at achieving ultimately optimum results with the efforts made in the early stage of the product development cycle. As a result, the assembly process of any odd‐configured parts such as torque converter blades, can be accurately planned, and made adaptable to all potential in‐process alterations due to either changes of components design or that of the assembly kinematics. Optimum assembly design is achieved when the volumetric interference meets a desired value based on an expert's determination. Experimental verification of the proposed optimum assembly design conducted in Luk, Inc. with two different blades' assemblies demonstrates satisfactory results.