Model-based Enterprise Research Articles

An uncertainty management framework to support model-based definition and enterprise

In pursuit of industrial digitalisation, the manufacturing industry is going through a transformation in the methods for product definition from the traditional two-dimensional drawing to three-dimensional digital model known as the model-based definition (MBD). The real benefit of this digitalisation lies in the adoption of model-based definition across all stages of the product lifecycles throughout the enterprise and its supply chain which is termed as model-based enterprise (MBE). However, the current application of this technology is partial, due to the involvement of several associated uncertainties. This paper proposes a novel framework for the management of uncertainties in the adoption of the model-based definition and presents a system in support of the proposed framework. The development commenced with the collaboration of two major aerospace industries. The framework comprises five phases including the preliminary phase, identification, assessment, analysis, and response phase. A systematic process is followed in developing the framework while Numeral, Spread, Assessment, and Pedigree (NUSAP), and Analytical Hierarchy Process (AHP) are used in the assessment of uncertainties. The developed system consists of a user interface, a database of uncertainties, an assessment module, an analysis and prioritisation module, and a knowledge base of mitigation strategies for key uncertainties. The system facilitates the analyst to select the relevant uncertainties from a defined list, systematically assess and analyse each of the uncertainty and obtain recommendations for mitigation of the prioritised uncertainties in the project. The framework and the developed system were validated through expert interviews with two world-class aerospace companies. This system facilitates identifying the various types of uncertainties of MBD, quantifying their impact on the project rationally, and formulating a suitable management strategy for achieving the status of a model-based enterprise.

A quantitative analysis of parametric CAD model complexity and its relationship to perceived modeling complexity

Digital product data quality and reusability has been proven a critical aspect of the Model-Based Enterprise to enable the efficient design and redesign of products. The extent to which a history-based parametric CAD model can be edited or reused depends on the geometric complexity of the part and the procedure employed to build it. As a prerequisite for defining metrics that can quantify the quality of the modeling process, it is necessary to have CAD datasets that are sorted and ranked according to the complexity of the modeling process. In this paper, we examine the concept of perceived CAD modeling complexity, defined as the degree to which a parametric CAD model is perceived as difficult to create, use, and/or modify by expert CAD designers. We present a novel method to integrate pair-wise comparisons of CAD modeling complexity made by experts into a single metric that can be used as ground truth. Next, we discuss a comprehensive study of quantitative metrics which are derived primarily from the geometric characteristics of the models and the graph structure that represents the parent/child relationships between features. Our results show that the perceived CAD modeling complexity metric derived from experts’ assessment correlates particularly strongly with graph-based metrics. The Spearman coefficients for five of these metrics suggest that they can be effectively used to study the parameters that influence the reusability of models and as a basis to implement effective personalized learning strategies in online CAD training scenarios.

Simulation of Database Interactions for Early Validation of Digitized Enterprise Processes

Digitized enterprise processes often encompass interaction with relational databases. Describing and simulating large-scale and complex processes on different abstraction levels lead to the use of tools and methods of Model-based Systems Engineering. In practice, current entity-relationship modeling approaches solely enable modeling relational database structure without simulation of database interactions at an early development stage. However, in general, it is known that early validation improves common understanding and communication in the development team and reduces the risk of design flaws. This paper presents an approach for model-based enterprise process digitization and a previously developed and now enhanced broker-based SysML Toolbox for integrating real relational databases into SysML simulations. The approach comprises status quo documentation concerning enterprise processes, development of digitized processes and required relational database structures as well as validation of digitized processes using the SysML Toolbox.

Model-Based Enterprise Approach in the Product Lifecycle Management: State-of-the-Art and Future Research Directions

Innovations in product development and process technologies represent a promising strategy to face the increasing competitiveness of modern markets in the global economy. Also, customer requirements become more and more specific and the complexity of products is still increasing. Industries need to adopt effective solutions during the product development process and to support, for sustainable purposes, all the phases of the product lifecycle. Advanced model-based solutions emerge for digitally supporting these industrial needs. In this context, a Model-Based Enterprise (MBE) represents an organization that adopts modeling technologies, such as Model-Based Definition (MBD) solutions, to integrate and manage both technical and business processes related to product design, production, support, and retirement. Past research discusses the model-based approaches focusing on technical product development, mainly referring to the design and the manufacturing phases. A wide perspective from the other phases of lifecycle seems to lack in the literature. By carrying out a systematic literature review, this research aims to investigate the relationships between the MBE approaches and the product lifecycle phases and to identify potential benefits and challenges. It enhances the academic knowledge domain by also shedding light on potential future research directions.

Geometric Variability in Parametric 3D Models: Implications for Engineering Design

Modern manufacturing companies operate in environments characterized by increasingly shorter development cycles and the need to develop highly customizable products at competitive prices. In this paper, we examine the role of parametric 3D modeling in the product development process, and highlight the importance of robustness, flexibility, and responsiveness to geometric variations, which are particularly relevant in the context of the Model-Based Enterprise (MBE). We discuss the often-inefficient parametric 3D modeling practices used in industry, their root causes and implications, and identify the detrimental effects of low-quality models on engineering design activities, specifically design changes during development, generative design algorithms, design optimization, simulation, product/part family configuration, AI-based parametric modeling, Model-Based System Engineering (MBSE), and parametric and adaptive encryption. Finally, we present future lines of research aimed at increasing the quality of parametric models.

Digital Twin-Driven Process and Equipment FMECA Generation for Smart Manufacturing Applications

Qualtech Systems, Inc. (QSI)’s integrated tool set, consisting of TEAMS-Designer® and TEAMS-RDS® provides a comprehensive digital twin-driven and model-based systems engineering approach that can be deployed for fault management throughout the equipment life-cycle – from its design for fault management to condition-based maintenance of the deployed equipment. In this paper, we present QSI’s approach towards adapting and enhancing their existing model-based systems engineering (MBSE) approach towards a comprehensive digital twin that incorporates constructs necessary for development of a Process Failure Modes and Criticality Analysis (P-FMECA) and integrates that with an Equipment FMECA. The paper will discuss the various levels of automation towards incorporation of these model constructs and their reuse towards automation of the development of the different digital twins and subsequently the automatic generation of the combined Process and Equipment FMECA. This automated ability to develop the integrated FMECA that incorporates both Process-level Failure Modes and Equipment-level Failure Modes allows the system designer and operators to correlate and identify process failures down to their root causes at the equipment-level and thereby producing a comprehensive actionable systems-level view of the entire Smart Manufacturing facility from a fault management design and operations perspective. The paper will present the application of this novel technology for the Advanced Metal Finishing Facility (AMFF) at the Warner-Robins Air Logistics Complex (WR-ALC) in Robins Air Force Base, Georgia, as part of WR-ALC’s initiative towards model-based enterprise (MBE) and smart manufacturing.

Defining requirements for integrating information between design, manufacturing, and inspection

Industry desires a digital thread of information that aligns as-designed, as-planned, as-executed, and as-inspected viewpoints. An experiment was conducted to test selected open data standards' ability to integrate the lifecycle stages of engineering design, manufacturing, and quality assurance through a thorough implementation of a small-scale model-based enterprise. The research team set out to answer: from design, through production, and final inspections, what are the hurdles that a manufacturer would face during the development of a fully linked and integrated information chain? The research team was not able to fully link all the required information, but value for the industry was still identified. This paper presents the results of the experiment, provides guidance on how to overcome or mitigate identified challenges, and discusses the benefits or incentives to be gained from tracing or linking information through multiple stages a product lifecycle.

РАЗВИТИЕ АРХИТЕКТУР ЦИФРОВЫХ ПРЕДПРИЯТИЙ

The article examines the impact of the use of digital technologies, such as new production technologies, industrial Internet, artificial intelligence, big data and predictive analytics on the construction of dynamic and flexible architectures of modern digital enterprises. As a tool that implements a single information space of production and business processes of the enterprise, the concept of Industry 4.0 and the architectural approach based on RAMI are proposed, which consider the use of the network structure of the connected world as the technological basis of the enterprise. To model the production and business processes of a digital enterprise, the concept of building enterprises whose activities are based on the use of models (Model-Based Enterprise) and an approach to modeling and managing digital flow (Digital Thread) is considered. To increase the semantic interoperability of interacting models of digital enterprises, it is proposed to use methods of ontological modeling, and to accelerate the flexible configuration of digital enterprises – methods of microservice organization of software.

Model-Based Definition and Enterprise: State-of-the-art and future trends

Model-Based Definition (MBD) is being adopted by the manufacturing industry as a single source for all product information in place of conventional 2D drawings. This paper aims to review the current literature on Model-Based Definition (MBD) and Model-Based Enterprise (MBE) to recognize the main contributions towards the development and implementation of MBD and explore its various perspectives. The publications encompassing technology and applications of MBD are categorized into seven domains. These domains are lifecycle information; design, discrete part manufacturing, and inspection; assembly; maintenance, repair, and overhaul; process planning; engineering change management; and contemporary aspects of digital product definition. The major outcomes of research literature, in these domains, are reviewed and future research directions are identified and formulated. Additionally, the paper highlights the issues and challenges associated with the realization of MBE by the manufacturing industry. These issues are categorized into technical, management, and certification categories. The prevalent issues in each of these categories are further discussed and analyzed.

Leveraging Category Theory in Model Based Enterprise

A mathematical framework based on category theory is proposed to formally describe and explore procedures of modeling engineering products and processes that comprise operation of a model-oriented enterprise. The framework is intended to provide interoperability across a variety of engineering modeling languages and tools, supplying them with a common abstract foundation capable to represent, generate, and verify diverse design and production knowledge. The framework is leveraged via algebraic representation of product configurations as diagrams in categories with models as objects and descriptions of actions involved into products assembly as morphisms. Relevance of the framework is justified by appealing to systems engineering standards such as IEC 81346. Category theoretical methods for solving direct assembly problems that consist in constructing a product model from a given configuration are presented. Specifically, solutions are obtained via the universal construction called a colimit of a diagram. Much attention is then paid to stating and solving inverse assembly problems that consist in recovery and subsequent optimization of the configuration from the product model and assembly actions. Inverse problem solving is in demand for generative design, viz. an emerging fully automatic product development and manufacturing technology. Example solutions to direct and inverse problems are described in categories that represent two major areas of model-based enterprise operation: solid body geometric modeling of mechanical products and discrete-event simulation of production processes.

A knowledge-based system for quality analysis in model-based design

The quality of model-based definition (MBD) models is one of the significant challenges to achieving model-based enterprise (MBE). Different stakeholders in MBE put forward different quality requirements for MBD models, while any quality defect may hinder the production. Therefore, it is essential to analyze the quality of MBD models adequately before the usage. However, existing quality tools are difficult to apply in MBE. A knowledge-based quality analysis system for MBD part models is presented in this paper. The system utilizes model quality knowledge to analyze model quality from the perspective of various stakeholders in MBE. And it can be extended by adding new MBD part model quality knowledge. In order to judge model quality, a concept of the model definition unit is introduced for converting model information into the description towards model semantics quality, and a quality analysis method based on this description is proposed. For the ease of model quality knowledge representation and maintenance, a knowledge representation framework based on the object chain and parameter table is developed. Finally, a prototype system is implemented to verify the effectiveness and practicality. With 46 knowledge items derived from eight model-used stages, in total 24 potential quality defects are found in two case models. And additional two defects are discovered by extending the system with new model quality knowledge. In this way, the model quality is improved from the perspective of corresponding users.

Method for enabling a root of trust in support of product-data certification and traceability.

Trust in product-data quality (PDQ) is critical to successful implementation of model-based enterprise (MBE). Such trust does not extend to the exchange and reuse of three-dimensional (3D)-product models across the product lifecycle because verifiable traceability in product data is lacking. This assurance is especially crucial when "siloed" manufacturing functions produce product data that is not fully interoperable and thus requires frequent reworking to enable reuse. Previous research showed how Public Key Infrastructure (X.509-PKI) from the X.509 standard could be used to embed digital signatures into product data for the purposes of certification and traceability. This paper first provides an overview and review of technologies that could be integrated to support trust throughout the product lifecycle. The paper then proposes a trust structure that supports several data-transaction types. Next, the paper presents a case study for common configuration management (CM) workflows that are typically found in regulated industries. Finally, the paper draws conclusions and provides recommendations for further research for enabling the product lifecycle of trust (PLOT).

Design, Manufacturing, and Inspection Data for a Three-Component Assembly.

To better understand and address the challenges faced in linking all stages of a manufacturing and design process, an investigative fabrication process was designed and enacted as part of a collaboration between the National Institute of Standards and Technology (NIST) and the Manufacturing Technology Centre (MTC). This collaboration sought to test selected open standards’ ability to integrate the product-lifecycle stages of engineering design, manufacturing, and quality assurance through a thorough implementation of a small scale model-based enterprise (MBE). A dataset was generated as a result of the collaboration. This article provides details about the dataset and instructions for how to access and/or retrieve it.

Assessment of Parametric Assembly Models Based on CAD Quality Dimensions

This work was partially supported by the Spanish grant DPI2017-84526-R (MINECO/AEI/FEDER, UE), project CAL-MBE, Implementation and validation of a theoretical CAD quality model in a Model-Based Enterprise (MBE) context. , and the ANNOTA2 project funded by Universitat Politecnica de Valencia.

Promoting Model-based Definition to Establish a Complete Product Definition.

The manufacturing industry is evolving and starting to use 3D models as the central knowledge artifact for product data and product definition, or what is known as Model-based Definition (MBD). The Model-based Enterprise (MBE) uses MBD as a way to transition away from using traditional paper-based drawings and documentation. As MBD grows in popularity, it is imperative to understand what information is needed in the transition from drawings to models so that models represent all the relevant information needed for processes to continue efficiently. Finding this information can help define what data is common amongst different models in different stages of the lifecycle, which could help establish a Common Information Model. The Common Information Model is a source that contains common information from domain specific elements amongst different aspects of the lifecycle. To help establish this Common Information Model, information about how models are used in industry within different workflows needs to be understood. To retrieve this information, a survey mechanism was administered to industry professionals from various sectors. Based on the results of the survey a Common Information Model could not be established. However, the results gave great insight that will help in further investigation of the Common Information Model.

Gaps Analysis of Integrating Product Design, Manufacturing, and Quality Data in The Supply Chain Using Model-Based Definition.

Advances in information technology triggered a digital revolution that holds promise of reduced costs, improved productivity, and higher quality. To ride this wave of innovation, manufacturing enterprises are changing how product definitions are communicated - from paper to models. To achieve industry's vision of the Model-Based Enterprise (MBE), the MBE strategy must include model-based data interoperability from design to manufacturing and quality in the supply chain. The Model-Based Definition (MBD) is created by the original equipment manufacturer (OEM) using Computer-Aided Design (CAD) tools. This information is then shared with the supplier so that they can manufacture and inspect the physical parts. Today, suppliers predominantly use Computer-Aided Manufacturing (CAM) and Coordinate Measuring Machine (CMM) models for these tasks. Traditionally, the OEM has provided design data to the supplier in the form of two-dimensional (2D) drawings, but may also include a three-dimensional (3D)-shape-geometry model, often in a standards-based format such as ISO 10303-203:2011 (STEP AP203). The supplier then creates the respective CAM and CMM models and machine programs to produce and inspect the parts. In the MBE vision for model-based data exchange, the CAD model must include product-and-manufacturing information (PMI) in addition to the shape geometry. Today's CAD tools can generate models with embedded PMI. And, with the emergence of STEP AP242, a standards-based model with embedded PMI can now be shared downstream. The on-going research detailed in this paper seeks to investigate three concepts. First, that the ability to utilize a STEP AP242 model with embedded PMI for CAD-to-CAM and CAD-to-CMM data exchange is possible and valuable to the overall goal of a more efficient process. Second, the research identifies gaps in tools, standards, and processes that inhibit industry's ability to cost-effectively achieve model-based-data interoperability in the pursuit of the MBE vision. Finally, it also seeks to explore the interaction between CAD and CMM processes and determine if the concept of feedback from CAM and CMM back to CAD is feasible. The main goal of our study is to test the hypothesis that model-based-data interoperability from CAD-to-CAM and CAD-to-CMM is feasible through standards-based integration. This paper presents several barriers to model-based-data interoperability. Overall, the project team demonstrated the exchange of product definition data between CAD, CAM, and CMM systems using standards-based methods. While gaps in standards coverage were identified, the gaps should not stop industry's progress toward MBE. The results of our study provide evidence in support of an open-standards method to model-based-data interoperability, which would provide maximum value and impact to industry.

Testing the Digital Thread in Support of Model-Based Manufacturing and Inspection.

A number of manufacturing companies have reported anecdotal evidence describing the benefits of Model-Based Enterprise (MBE). Based on this evidence, major players in industry have embraced a vision to deploy MBE. In our view, the best chance of realizing this vision is the creation of a single "digital thread." Under MBE, there exists a Model-Based Definition (MBD), created by the Engineering function, that downstream functions reuse to complete Model-Based Manufacturing and Model-Based Inspection activities. The ensemble of data that enables the combination of model-based definition, manufacturing, and inspection defines this digital thread. Such a digital thread would enable real-time design and analysis, collaborative process-flow development, automated artifact creation, and full-process traceability in a seamless real-time collaborative development among project participants. This paper documents the strengths and weaknesses in the current, industry strategies for implementing MBE. It also identifies gaps in the transition and/or exchange of data between various manufacturing processes. Lastly, this paper presents measured results from a study of model-based processes compared to drawing-based processes and provides evidence to support the anecdotal evidence and vision made by industry.

Digital factory system for dynamic manufacturing network supporting networked collaborative product development

During the last years, important research investments have been made by Airbus Group Innovations for the establishment of sustainable Product and Process data interoperability based on open standards. Driven successively by concurrent engineering, collaborative product design in the virtual enterprise or digital behavorial aircraft, it was capitalize through the establishment of a federative interoperability framework. Driven by factory of the future-related research, the dynamic manufacturing network (DMN) concept enriched the framework, which aims at providing agile infrastructure for networked collaborative product development. For such networks, protocols based on open eBusiness product lifecycle management (PLM) standards for exchange and sharing of product and process data between the implied organizations, their processes and the technical enteprise applications supporting these processes are needed This paper presents a new way of combining model-based enterprise platform engineering, model-driven architecture, and system engineering in order to adress the establishment of a sustainable interoperability within DMN. Based on relevant litterature interoperability issues, this paper describes the new approach, which relies on the association of effective existing technologies coupled with research results on the fields of model-driven engineering (MDE), enterprise interoperability, system engineering and PLM. The new approach relies on the concept of digital factory system (DFS) coupled with DMN in order to produce sustainable and agile collaborative infrastructure for manufacturing digital ebusiness ecosystem. The approach is then illustrated through use case coming from the IMAGINE project and an outline is provided on how it will be used and developed further for the assessment of PLM standards and their implementation in the Standard Interoperability PLM project at IRT-Systemx.

Extended 3D annotations as a new mechanism to explicitly communicate geometric design intent and increase CAD model reusability

A successful implementation of the Model-Based Enterprise concept (MBE) requires maximizing the potential benefits of annotated 3D models. The foundations of the MBE model are established by digital product definition data practices, which are currently regulated by standards such as ASME Y14.41-2003 and ISO 16792:2006. At the center of the MBE concept is the notion of CAD model reusability, which relies on the idea that 3D CAD models can be reused both throughout the entire product lifecycle and as a starting point for future development of new products. In this context, a critical aspect of CAD model reuse is the proper identification and understanding of the geometric design intent that is usually expressed implicitly within the CAD model.In this work, we present a method to communicate geometric design intent explicitly by overloading and extending the scope of the current annotation instruments available in the MBE approach. We propose a new broader type of model annotation that we call “extended annotation”, where design information is represented both internally within the 3D model and externally, on a separate repository. This structure naturally demands additional mechanisms to support the interaction of users with the information. In order to manage the information stored in these extended annotations effectively, we implemented an annotation manager that automatically synchronizes the dual representation of the annotations. To reduce the visual clutter in the 3D model, the software provides powerful filtering, editing, and visualization capabilities, giving users complete control of the information stored in the model. Finally, a study was conducted with 60 participants to evaluate the performance of the proposed model and the usability of the annotation manager. Results show a statistically significant benefit of using the extended annotation system, suggesting the use of this model as a valuable approach to improve design intent communication.

Using Ontologies for Enterprise Architecture Integration and Analysis

Enterprise architecture facilitates the alignment between different domains, such as business, applications and information technology. These domains must be described with description languages that best address the concerns of its stakeholders. However, current model-based enterprise architecture techniques are unable to integrate multiple descriptions languages either due to the lack of suitable extension mechanisms or because they lack the means to maintain the coherence, consistency and traceability between the representations of the multiple domains of the enterprise. On the other hand, enterprise architecture models are often designed and used for communication and not for automated analysis of its contents. Model analysis is a valuable tool for assessing the qualities of a model, such as conformance and completeness, and also for supporting decision making. This paper addresses these two issues found in model-based enterprise architecture: (1) the integration of domain description languages, and (2) the automated analysis of models. This proposal uses ontology engineering techniques to specify and integrate the different domains and reasoning and querying as a means to analyse the models. The utility of the proposal is shown through an evaluation scenario that involve the analysis of an enterprise architecture model that spans multiple domains.