ABSTRACT. This paper provides an update on the Department of Defense (DoD) digital engineering policy, guidance, collaboration efforts, education and training, and science and technology investments under way to advance the state of practice.  Digital engineering is the Department’s initiative to transform the way it designs and delivers complex systems.  DoD defines digital engineering as “an integrated digital approach that uses authoritative sources of system data and models as a continuum across disciplines to support life cycle activities from concept through disposal.”  The Office of the Under Secretary of Defense for Research and Engineering (OUSD(R&E)) has begun enterprise-wide initiatives to implement digital engineering.

ABSTRACT. The philosophy of Capvidia software when it comes to Model Based Enterprise is simple: enabling automated workflows with a focus on PMI semantics, and using “real” CAD data — which is far from perfect. In this demonstration, you will see how Capvidia’s customers are benefiting from semantic PMI workflows even with the imperfect CAD data that they have in production — or even, as in this Creo-based demonstration, not having any 3D PMI on the model at all. This demonstration will feature:

• Automating creation of 3D PMI on Creo model based on annotations found on the 2D drawing in Creo
• Exporting the CAD model to an industry standard MBD format for downstream consumption
• Validation of derivative model to ensure data integrity
• Healing the PMI to make sure it is semantic and ready for downstream consumption by software
• Loading the 3D model in metrology software to demonstrate consumption of the PMI
• Automatic generation of inspection reporting documents in the Excel format
• Harvesting measurement results from metrology software, Excel, and Net-Inspect to ensure the traceability of measurement data to the authority model

We think that you will be surprised about the some of the low hanging fruit out there in terms of productivity from MBE workflows. The time for Model Based Enterprise is now!

ABSTRACT. Ten plus years after its introduction, the practice of Model-Based Systems Engineering (MBSE) has yet to be widely adopted across the industry. Amongst several reasons, a few stand out: the lack of a formalism with well-defined semantics to create system model, the lack of a methodology to create system model across tools, disciplines, and organizations, the lack of rigor to analyze the system model continuously and automatically, the lack of comprehensive content-based version control to support provenance, traceability and reproducibility, the lack of best practices in managing configuration and change of system model, and the inability of different kinds of stakeholders to access the system model and provide feedback on it. We call an approach that addresses these challenges Integrated Model Centric Engineering (IMCE). This paper overviews the challenges facing MBSE, outlines the virtues of IMCE, discusses requirements to enable IMCE, and presents a vision for an IMCE approach.

ABSTRACT. The key to a successful Model-Based Enterprise is control of the massive amounts of data that it generates and tracks. Understanding the complexities and relationships of this data is daunting, little on implementing a successful configuration management strategy. This paper will present a methodology for understanding a Model-Based data set and then a couple of fundamental concepts to manage it.

ABSTRACT. As model-based definition (MBD) becomes prevalent throughout the enterprise, the need to educate both new hires entering the workforce and those who author and consume traditional product definition is critical. A tactical education and training plan is essential to the success of MBD adoption. Workforce development for MBD adoption within an enterprise requires three phases: 1) Establishing literacy 2) Building practitioners 3) Establishing mastery. As an organization moves its people through these phases of awareness, competency, and mastery, not only are training programs required but a strong communication ramp-up is also needed to bolster the enterprise knowledge. Challenges in current practice will be highlighted as they relate to establishing a successful MBE workforce.

ABSTRACT. Additive manufacturing (AM) has come on strong in recent years, maturing from niche manufacturing processes to processes that have become increasingly mainstream. Additively manufactured parts have become less taboo as industry and government alike become more comfortable with the technologies. Parts created using AM processes are showing up across industries, from aerospace to defense to medical to nuclear. With this seemingly new level of comfort, government and industry alike are suddenly being faced with the potential conundrum of how to incorporate AM parts into their supply chain. In this session we review recent efforts that back the notion that AM parts require special attention in a model-based enterprise. We then discuss whether that attention is warranted or not, presenting scenarios that advocate for both sides of the story.

ABSTRACT. In diamond machining freeform and symmetric optics, it is essential to ensure that surface characteristics are maintained. Optics for imaging applications require tight tolerances on surface roughness, mid-spatial frequencies, and form. This work predicts surface roughness in diamond turning as a function of machining parameters using machine learning. Diamond turning is chosen for its relative simplicity when compared to other machining operations. No tool wear is expected, and the surface is generated by a simple geometric replication of the tool into the surface for a wide range of parameters. Machine learning algorithms are trained by associating machining characteristics / parameters with the resulting surface finish performance measures. Surface finish prediction results obtained with traditional regression machine learning algorithms are reported, including a general regression neural network. Work is ongoing to further validate results and use additional diamond turning machining data to train the neural network. In addition, work continues to better interpret the effects of machining parameters on the surface function estimates obtained by the machine learning algorithms.

ABSTRACT. Proper data availability within a manufacturing enterprise directly drives the ability of industry decision makers to function and operate at optimal effectiveness. The needs of different decision makers can vary greatly based on, not only the level at which the decision is being made, but also the perspective and end effects of that decision. For example, an operator at the equipment level needs knowledge of that equipment’s condition when deciding whether to operate that machine; a production manager needs to know the number of operational machines in that production line when planning system level operations; a maintenance manager needs knowledge of what maintenance tasks are in the queue and the availability of their technicians. Although each decision is related, this information is distinct, different, and may be obtained in deductive reasoning, or from sources that are independent of one another. Here the equipment level decision, whether to operate the machine, can directly inform the system level production and maintenance planning without passing along the specific condition of the machine. The granularity of what information is needed to make a decision is informed directly by what that decision is and any consequences of that decision. This paper looks at different perspectives in maintenance for manufacturing facilities -- system level, equipment level, and component level -- and discusses information and data requirements for various decisions at each level. The goal of this paper is to guide manufacturers for what types of data should be collected for the decisions they want to make.

ABSTRACT. This paper & presentation will discuss the direct parallels between Newport News Shipbuilding’s (NNS’s) “Product Model centric Strategy” and the Office of the Under Secretary of Defense for Research and Engineering (USD(R&E)) “Digital Engineering Strategy” (DES). These NNS and Navy strategies can be related through the five DES foundational elements (listed below, NNS related efforts in BLUE) necessary for a Digital Engineering Ecosystem to thrive: 1. Formalize the development, integration, and use of models to inform enterprise and program decision making (NNS-Strategy for Digital Thread and Digital Twin) 2. Provide an enduring, authoritative source of truth (NNS-Configuration Managed links between Navy Databases and Digital Product Model) 3. Incorporate technological innovation to improve the engineering practice (NNS-Implementation of AR/VR, laser scanning, IOT and other technologies incorporated into production processes) 4. Establish a supporting infrastructure and environment to perform activities, collaborate, and communicate across stakeholders (NNS-Integrated, Secure Cloud Environment) 5. Transform the culture and workforce to adopt and support digital engineering across the life cycle (NNS-integrated Digital Shipbuilding (iDS) for digital manufacturing)

This paper & Presentation focuses on NNS’s strategy, vision, and the development of an Aircraft Carrier “Intelligent Digital Twin” for lifecycle sustainment. The concept of an Intelligent Digital Twin is completely consistent with NNS’s efforts to integrate digital capabilities based on smart technologies throughout the Digital Thread. The new capabilities will utilize connected digital information to form a holistic view of operations. This view promotes a safer workplace, efficiency, and reduced downtime to allow assets to remain in service longer.

ABSTRACT. Technical endeavors have always used the concept of models. Models are fundamental to the way humans think and solve problems. Efforts around modeling with software attempt to capture and reflect the abstract nature of human reasoning and memory. As engineering modeling languages and analysis capability evolve, engineering organizations are approaching a transformative condition where Engineering Environments enable modeling as a basis for Engineering work. These environments incorporate sophisticated collaboration and configuration control on top of massively scaled computing, promising a modern digital experience known as a Model-Based Engineering Environment or MBEE.

There are challenges for making MBEEs successful. Economically viable implementations are needed to enable organizations to operate MBEEs successfully. MBEEs must be able to evolve in scale to meet the insatiable appetite for compute and data handling that accompany their use. And possibly most important, Engineers using an MBEE are being driven by the requirements for the product they are Engineering. Thus, an MBEE must provide significant advantages for the Engineer by both increasing the quality of the creative experience and removing obstacles to productivity.

Open MBEE exists to address these challenges and empower Engineers through the phenomena of the open source collaborative software movement. The community that comes with open source provides a large-scale mechanism for developing consensus that is captured as concrete technical products. These technical products represent invariants that can propel Model-Based Engineering Environments to success in adopting organizations. Commodity access is crucial in maintaining the strong pace of innovation and technical capability necessary for MBEEs to evolve quickly enough to meet the needs of Engineers. This vision begins to form a projection of a substantial transformation in the world of collaborative engineering modeling such that MBEEs can be sophisticated, productive, and cost-effective.

ABSTRACT. The Model-Based Enterprise (MBE) must deal with exploding volumes of data distributed over multiple repositories. A key capability needed for the MBE is a handler system that provides services to: (1) connect to a wide range of enterprise repositories, such as PLM , ALM , and databases, (2) search and query versioned models in repositories, (3) subscribe and track model elements, and (4) visualize and trace connected models. This handler system would be used by the MBE for analysis, verification and validation, and certification.

We will demonstrate the latest release of Syndeia, the MBE interoperability platform from Intercax, that federates models and databases from system development to manufacturing, testing, distribution and field operation. Syndeia provides capabilities to: (1) connect to enterprise PLM, ALM, databases, requirements management and other version-managed systems; (2) query and search models, such as bill-of-materials, requirement structures, CAD, database tables and records; (3) generate, connect, compare, and sync models; and (4) visualize all model-based connections. Syndeia makes it possible to create a Total System Model of a system, a digital blueprint that evolves through the system’s lifecycle. Two features are critical for production-level deployment: • Microservice-based architecture for resilience and accessibility in multi-user environments • Graph databases and pattern-matching query languages to analyze, visualize and navigate dataspaces with millions of elements. Intercax will demonstrate Syndeia for a multi-facetted sample data set with a focus on building connections in a multi-centric environment where no single tool or repository is the hub for all connections.

ABSTRACT. DOD has traditionally procured, created, and maintained Technical Data Packages (TDPs) based on 2-Dimensional (2D) engineering drawings. While the source of these drawings have transitioned to 3D Computer Aided Design (3D CAD) over the last 15 years or so, the legally binding technical data is still largely 2D, black line art, third angle projection, "front, top, side" drawings. Various organizations in DOD have recently begun the transition to 3D intelligent (3Di) pdf based technical data as the core of our technical data packages. 3Di based technical data provides a superior means to define products compared to traditional drawings. DOD is developing the training, standards, templates and infrastructure to transition to this better technical data of the future. Part of this transition is the update of MIL-STD-31000 to incorporate 3Di based technical data, which has recently been released as the B revision. DOD intends to work with our industry partners on this transition to a superior technical data package to improve communication, lower costs and provide improved support to the warfighter.

ABSTRACT. Over the past several years the Defense Logistics Agency has participated with Engineering Service Activities and Sustainment Activities in pilot projects to study the acceptance of 3D Technical Data within the Department of Defense Supply Chain. The initial pilot projects focused on the use of embedded PRC geometry in a PDF file with other technical data attached as necessary. Subsequent pilot projects performed during 2018 have been expanded to include different formats. This paper will provide a short overview of the Defense Logistics Agency pilot project program, progress of the expanded pilots, and an introduction to an upcoming technical data project, “Connecting the MBE” which is a look at the issues facing the Defense Logistics Agency interfacing with a broad spectrum of PLM systems having dissimilar formats, product definitions, domains, and scope.

ABSTRACT. Cost and time reduction of the mold and die production is a critical issue for any manufacturing companies. Part designers are basically not manufacturing experts, therefore they often design parts with various problems for manufacturing with molds and dies. These problems are usually detected by manufacturing engineers in the later production stage. Problems are reported to the part designer and they are resolved by modifying the part shape. Reduction of such reworks is important for realizing the efficient production of the mold and die, and consequently efficient part production. In this paper, we explain a software system named manufacturability assistant for reducing the reworks. This system detects shape elements of a part with potential manufacturability problems by applying various shape extraction procedures to the CAD model of the part. By using this system, designers can evaluate the quality of a part in the manufacturability view point. They can reflect the evaluation result in the part design to obtain a part with higher manufacturability.

ABSTRACT. This talk will introduce a new NIST-industry consortium for a coordinated response to the increasing verification needs, as the complexity of geometric product specification in standards has grown by an order of magnitude. In response to industry need, NIST has long operated a testing service for a limited scope of coordinate metrology software. But the time is overdue for broad software verification on many fronts of coordinate metrology. A lot has been discovered during the development and execution of the existing test service that will be applied to a much wider effort. Not only will this lead to an increased scope of NIST testing but also to a reservoir of confirmed mathematical reference fits associated with sets of interdependent data representing verification of complex geometric requirements.

ABSTRACT. This paper discusses how the ANSI/DMSC Quality Information Framework (QIF) standard provides benefit to the model-based enterprise (MBE) in two important ways: (1) automation of cyber-physical processes, allowing faster realization of higher quality products at lower cost, and (2) by providing traceability of massive quantities of measurement-related data to the authority product definition model. Over the last decade, efforts have been made to develop digital interoperability standards that address the connection points for information transfer through the product lifecycle. Through early work in the Automotive Industry Action Group (AIAG) and the Digital Metrology Standards Consortium (DMSC), new data models have emerged and achieved significant maturity levels.

The benefits of automation and business process systemization are made possible with meaningful, semantic data packaged in the QIF format. With Model Based Definition (MBD) data (i.e., PMI, FT&A, etc.) becoming more commonplace, QIF is becoming an attractive complete and unambiguous MBD delivery mechanism for industrial end users. In addition to automation benefits, QIF helps to provide data traceability in this age of Big Data, where traceability is sorely needed. MBE provides a paradigm for organizing this data by mapping it all to a meaningful product definition: the master model-based definition enabled by a product data management system. QIF is designed to instantiate this MBE approach to data management.

This paper will explain the background for why QIF is needed, and the features built into QIF which will ensure that it is equipped to handle the needs of modern industry.

ABSTRACT. While large scale manufacturers are able to continually invest in the equipment and infrastructure of their manufacturing systems, small and medium enterprise size manufacturers are more financially constrained. These smaller organizations are slower to invest in new systems with digital capabilities. Small and Medium Manufacturers (SMMs) commonly have different generations of CNC machines with varying levels of digital capability. Many SMMs still also own and operate fully manual legacy machines. This research investigates how to provide digital manufacturing capabilities to manual legacy machines. Three different price points of sensor suites are investigated to monitor legacy manual machines for quality, operator training, and predictive maintenance. This project creates the foundation for the development of a distributive manufacturing network at Auburn University.

ABSTRACT. A number of manufacturing demonstration and research cells have been developed that address key Digital Thread use cases. Free, open-source software and relatively affordable desktop 5-axis machine tools, along with detailed documentation and publicly available data provided by NIST, has allowed researchers to 1) create their own research platforms; and, 2) prove out fundamental concepts of Digital Thread. This paper identifies system components and architectures, as well as target research areas, for development testbeds that realistically and usefully model key areas of manufacturing while avoiding the expense of industrial CNC machines.

ABSTRACT. To bolster the efficiency and performance of maintenance work in manufacturing—maintenance being one of the key components to ensuring successful long-term operations—it is becoming increasingly necessary to ensure that maintenance operations are capable of seizing on analysis techniques from prognostics, health-monitoring, and related disciplines. Despite a surge in availability for low-cost sensing and data processing generally, the bulk of available knowledge on any given maintenance workflow will currently exist within historical records, via Maintenance Work-Orders (MWOs). Additionally, despite burgeoning standards in sensing and the related analysis, there is a dearth of similar standards scoped to MWOs. To that end, this paper addresses standards needs in MWOs, specifically, MWO data collection and storage, MWO data cleaning and parsing, and MWO data analysis needs.

ABSTRACT. Laser scanning allows for the capture of as-built products and structures. Point clouds are generated from the scans, which enables the use of software for multiple use cases such as comparison of as-built vs. as-designed. Multiple different technologies exist for capturing point clouds, just as multiple software packages exist for the processing of point clouds. Workflows in organizations shift constantly, point clouds are being targeted for their ability to enhance communication throughout the lifecycle. We discuss BIMs, scanning hardware, the capture and processing of point clouds and problems that exist with point clouds today. While laser scanning and the processing of point clouds are the primary focus of this paper, a brief introduction to other technologies is presented. Finally, an existing software for consolidating the point cloud workflow is discussed.

ABSTRACT. Model-Based Systems Engineering (MBSE) delivers benefits including increased product quality, shorter time-to-market, and reduced program cost. The design and operation of discrete manufacturing systems may benefit from applying MBSE processes, methods, and tools. However, MBSE is far from contemporary practice and these systems present unique challenges to developing and applying domain-specific MBSE methodologies. This talk explores what MBSE's application might look like for these systems and a value proposition for its inclusion.

ABSTRACT. Sometimes aerospace manufactures of the defense industry go out of business or the parts are so old there are no TDP or performance requirements available. This paper will provide a methodology for a rapid response to organizations that need to generate a Technical Data Package (TDP) and manufacture backlogged spare parts. Since there is no access to Computer Aided Design (CAD) model data for these components a reverse engineering (RE) technique need to be employed to generate the geometry of the Baseline Geometry in a parametric feature based CAD format. If complex surfaces are present a Sub-divisional surface modeling technique (Sub-D) is deployed. The static load levels and the natural frequency limits can be determined by assuming that the existing design meets all structural and dynamic performance requirements. Enhancing this Reverse Engineering process with Generative Design and Lattice Structure generation techniques presents an opportunity to not only reproduce the part but improve its performance, reduce its weight and reduce its time to manufacturing.

Since the additive manufacturing (AM) industry continues to grow with new machines, faster processes and a large selection of materials there is a great opportunity to redesign these parts using Lattice Structures and Generative Design Techniques. Lattice structures such as Gyroid minimal surfaces are very effective for light weighting, energy absorption, dynamic damping, ballistic protection, etc. This presentation will demonstrate how to combine Sub-Divisional surface modeling, Topology Optimization, manufacturing constraints and Lattice Structure generation tools to generate optimum designs.

ABSTRACT. A Q & A panel containing representatives from the QIF Community, authors, implementers, users, and thought leaders. Panel will also discuss the scope and uses for the new ANSI/DMSC QIF v3.0 standard and status on progressing QIF as an ISO/QIF. Furthermore, discuss the development and adoption of QIF from vendors and large industrial end users.

ABSTRACT. System Engineering models are fantastic models for describing a system. To extend their usefulness, Phoenix Integration has developed a plugin to ModelCenter that will allow system engineering models to be integrated to any simulation toolset for validation of the system engineering model. This includes requirements and behavior analysis with the integrated environment.

The objective of this video demonstration would be to show how the integration can be utilized for performance analysis and solution validation.