ABSTRACT. This presentation will describe the application of artificial intelligence to precision part manufacture and measurement. Specifically, it will summarize current efforts toward self-aware operation, or the ability of a production or measuring machine to understand its current state and surroundings and respond accordingly. The innovation is the combination of data-driven and physics-based models to provide hybrid physics-guided data learning approaches that improve the accuracy, physical consistency, traceability, and generalizability of model predictions. Ongoing research efforts leverage artificial intelligence, machining process modeling, measurement science, and design and ultraprecision machining of freeform optics.

The research capitalizes on the adoption of new digital technologies that establish the digital thread, or communication framework that enables seamless data flow and an integrated view of manufacturing processes. This digital thread links every phase of a manufactured part’s life cycle – from design, production, and testing through end use. For example, parts are described using a digital solid model that is developed using computer-aided design (CAD) software. Computer numerically-controlled (CNC) machine instructions for subtractive manufacturing, as well as other processes, are produced using computer-aided manufacturing (CAM) software. This data is partnered with the physical part as its digital twin, which accompanies the part throughout its lifetime. While these digital connectivities represent an evolutionary leap forward, human intervention is still required at nearly all stages. For example, the CAM part program is manually produced for every part in every factory by a specially trained, high wage programmer. To further complicate these issues, high volumes of data are available at each step through the IIoT that must be manually interpreted and implemented to improve the factory’s productivity. This presentation will describe current research that addresses these challenges with the end goal of self-aware operation.

ABSTRACT. This presentation will highlight the importance of a model-based enterprise (MBE) to sustainment and across the life cycle. Model-based X where “X” is sustainment needs to be considered as part of the systems of systems engineering starting early in the life cycle. Computer-aided manufacturing, inspection tools, and approaches should be planned for use in sustainment to include repairs and ease of mods and upgrades to update capabilities. The complexity of managing the digital thread or tapestry is greater when sustainment is considered, with the need to linking and management the “as maintained” bill of materials for each delivered system. Application of data analytics and artificial intelligence (AI)/machine learning (ML) supports prognostics and health management and performance feedback. System of systems modeling methods that include application of the Affordable Systems Operational Effectiveness (ASOE) framework to help organize the sustainment considerations for both the primary and enabling systems to reduce life cycle costs and improve reliability and support return on investment (ROI) case studies. There are several opportunities for leveraging digital thread for sustainment as a concentration area. The first is application of augmented/virtual/mixed reality for maintenance opportunities and supported by global subject matter expert networks. The sustainment community pull for application of advanced manufacturing approaches to include additive manufacturing also relies on distributed access to technical data packages to support manufacturing at the point of need for parts that can be printed. A third focus area is on acquisition reform focus on capability management for legacy systems to meet the challenges of the National Defense Strategy. Systems designed with standards-based architectures and interfaces can support lower cost and more agile modifications and upgrades of both hardware and software in a system.

ABSTRACT. Most proprietary and industry engineering standards and specifications are in standalone “dead-text” formats like print, PDF and Word. Some OEMs and most of the top Standards Organizations are in the process of adoption of SWISS Digital Models, using AI to transform static documents into digital models of interconnected, intelligent data. SWISS digital models for part and process specifications expand the integrated view of engineering requirements to non-3D data. They facilitate more effective analysis throughout product life-cycle and enable assessment of change impact not feasible for legacy documents. SWISS digital models relate internal Enterprise requirements to digital models of referenced Military and Industry specifications. In this demonstration, we will show how an engineer can transform legacy part and process specifications into smart, connected and change-aware assets within the enterprise PLM system, and link them to internal and external digital models to save time and eliminate risks of using obsolete, non-authoritative sources. SWISS was developed with funding and guidance from the Department of Defense, leading standards organizations, and leading aerospace, energy, and manufacturing companies.

ABSTRACT. The Journey of Adopting Model Based Systems Engineering (MBSE) can be a challenge; however, the organizational journey has to start somewhere. That journey starts with applying methods, standards and the right tooling to solve today’s problems. Applying the right capabilities—methods, processes, technologies (infrastructure and tools), resources, and policies—to address real-world large-scale problem is crucial to successful systems engineering with models central to capturing and elaborating views and models in considerations of the concerns associated with the system of interest and enabling systems. Designing individual systems without accounting for the entire ecosystem is no longer enough. Considerations for the System context considerations including System-of-Systems (SoS) can be accommodated using a common language such as SysML provides a semantically rigorous basis for the architecture description. This presentation will identify the key model relationships to physical system, its subsystems, and associated requirements enabling engineers from multiple domains to work on common models in a collaborative environment. We will present on how to address system complexity through application of the MagicGridTM Framework/method built upon the SysML language. The MagicGridTM method and framework have evolved by organizing, rationalizing, and codifying the experience of many MBSE adoption projects, business practices, and lessons-learned. During the presentation, using a simple climate control subsystem, we will demonstrate the MagicGridTM Framework and highlight some key adoption lessons-learned.

ABSTRACT. Computer Aided Design (CAD) software that is used to design mechanical components continues to evolve, as well as the Product Lifecycle Management (PLM) processes that manage this data, but the transfer of this information to anyone in the enterprise that will interact with the product, has changed very little in the last few decades. On the horizon is Model-Based Definition (MBD) which entails designing not only the product geometry in CAD but also all of the information needed to manufacture, inspect and sustain the product. The DMDII 15-11 project addresses the industry need for a way to meaningfully capture and connect such information at the CAD feature level.

ABSTRACT. Different participants in the supply chain of an asset, from original equipment manufacturer (OEM) to owner/operator (O/O), know more than others about significant aspects of the asset. Sharing of information between these participants is necessary to most effectively manage a product or asset for all stakeholders involved. In particular, one type of data generated about an asset during its lifecycle is maintenance data. Field maintenance data collected over the usage of a product provides valuable information about its failure patterns and performance in different operating contexts that can benefit all. However, maintenance data by itself typically has data quality issues and needs to be understood and processed in order for information of value to be extracted and used. In this article, we present a case study of how maintenance data from the CMMS/EAM can be processed to return information that can be used to benefit everyone in the supply chain.

ABSTRACT. Addressing cross-cutting concerns such as traceability, change management, and trade-off studies is complex in multi-disciplinary engineering. These aspects can only be addressed efficiently if organizations take a global level perspective on data and view data from many different sources as a whole.

Traditionally, enterprise software applications are coupled to a specific data store. The application layer communicates with the data layer through an interface to perform basic create-read-update-delete (CRUD) operations. These operations are common to most applications. By standardizing the interface between application and data layers through a standard API, enterprise software applications can be decoupled from specific data stores. APIs in general have 2 aspects: the API protocol and the semantics of the data being consumed and produced by the API. The latter aspect is independent of technology and is based on reaching a consensus between domain experts, which can be much harder than standardizing the API protocol using common technology.

Standardizing the API protocol can help organizations access data from various sources, reuse old data with new applications, and connect data to establish a digital thread. Several technologies such as REST, Linked Data, Hypermedia APIs, GraphQL, or collections of standards such as OSLC and Solid can be used to standardize the API protocol. The main ideas of these technologies as well as their adoption levels are presented. The impact of a standard API protocol for organizations, application vendors, and standardization organizations is explained. The opportunities as well as remaining challenges related to a standard API ecosystem are described.

ABSTRACT. In recent years, the emergence of improved three-dimensional scanning products and software has begun to disrupt various processes at Newport News Shipbuilding (NNS). The technology is evolving at a very rapid pace and we are continuing to develop new uses for it resulting in benefits for nearly all areas of our business. More importantly, we are recognizing it as a major component in our digital transformation and it is impacting how we understand the digital thread. Figure 1 below shows NNS’ quintessential digital thread with areas where laser scanning is impacting the business.

This paper is broken into two sections. The first section, titled Technology Summary, contains an overview of laser scanning technology, how it works, and its current applications. The second section, titled Digital Problem Resolution (DPR) Project Overview, describes our most recent project involving laser scanning technology.

ABSTRACT. Space-time dependent simulations (STDS) described by partial differential equations (PDEs) help with decision-making across the product lifecycle. For example, simulation driven design, a loop that alternates 3D CAD design and STDS reduces the need of expensive prototype testing and assesses design validity to requirements earlier in the design process. In the Model-based Enterprise (MBE) context, MBSE (model-based SE (MBSE)) is a system engineering methodology that enables, for example, the traceability of stakeholder requirements to digital artefacts such as simulation results. With MBSE, systems are described by information models, in the same way software code is described by an architecture model. Domain-specific model integration (e.g CAD model) and exchange in MBSE is facilitated by standardization of domain models. We identified two major problems that reduce the use of STDSs for MBE, one related to the association between CAD and simulation metadata, and another related to the description of numerical libraries. In this paper, we first propose to give a brief outline of the role of SDTSs across the product lifecycle and then explain the current challenges associated with them. We propose two solutions candidates, one that promotes the creation of a mesh standard that keeps metadata association between CAD and simulation using virtual topologies, the other that captures modelling decisions of numerical libraries by representing physics equations and numerical decisions using graph data structures. We illustrate how this would work with finite element analysis (FEA). By combining standardized mesh and solver-independent descriptions, STDS could be run using different solvers interchangeably.

ABSTRACT. We introduce a prototype implementation of the Securing and Authenticating Data-Links (SADL) Interface, which interacts with a manufacturing handle registry to facilitate traceability of digital resources for engineering projects. This paper outlines the intended use of SADL and the handle registry by laying out hypothetical questions from potential users. Additionally, we map the core concepts of key standard data representations in manufacturing to a popular data type taxonomy. Future work will include the design and testing of data visualizations based on our mapping protocols.

ABSTRACT. The exact amount of a product’s cost that is committed during the design phase is commonly debated, however based on the literature it is generally agreed that 70-85% of the costs are committed during the design phase. This information combined with the Department of Defense (DoD) focus on engineered resilient systems (ERS) has led to the research and development of a Manufacturability Assessment Knowledge based Evaluation (MAKE) methodology. This research is focused on the development of a manufacturability methodology to evaluate and assess alternative product designs in the early life cycle stages. McCall et al outlines the research efforts focused on the creation of the methodology and development and testing of a corresponding software tool. The research has continued forward with enhancements to the MAKE methodology and tool based on case study findings, which is the basis for this paper.

The case study provided valuable insight into the research and development activities needed to improve the methodology to better fit with an early lifecycle development phase. Subsequently, a software tool redesign effort took place to improve the outputs available to the user and to streamline the methodology process. This paper will discuss the improvements for the design of the updated version of the MAKE tool and how it can be used for future assessments of DoD products for benefit to the warfighter.

ABSTRACT. Industry interviews conducted during this project have revealed some potential inaccuracies in the conventional thought as to the readiness of the US industrial base to adopt digital manufacturing processes and procedures. The performers in this DMDII project went into the research phase with the assumption that approximately half of the supply chain would be ready to implement digital manufacturing capabilities into their organizations. With this assumption the deliverable of the project would be a set of technically-oriented playbooks for Original Equipment Manufacturers and Small/Medium Manufacturers to use as guides for implementation. What was found during the interview process was that less than 30% of those companies were actually in a position to adopt digital capabilities and that there is a gap in awareness and knowledge in what digital manufacturing means. Additional research into other studies has revealed similar issues in adoption of these necessary skills and capabilities. This realization has led the research team to rethink the deliverables of the project to include a digital manufacturing awareness/education component. In this paper the authors will present the findings and discuss the meaning of these revelations to the digital manufacturing and model based enterprise community.

ABSTRACT. Digital Twins, sometimes known as digital surrogates, are attracting attention as a means to rapidly assess the current status of manufacturing enterprises. A digital twin models one or more aspects of a physical element so that it can be measured and optimized. A digital twin framework is a set of protocols and standards that can be used to assist the development, synchronization and measurement of digital twins. This paper contains an assessment of some early digital twin examples. They were submitted to Working Group 15 of ISO TC184/SC4 who are developing the ISO 23247 standard for Digital Twin manufacturing frameworks. The working group classified the examples into large, medium and small frameworks, and gave preliminary definitions to the protocols necessary to support digital twinning on the shop floor. The definitions were tested against a small-scale digital twin example, and measurements were made for the times and responses necessary to support real time digital twinning for machining processes.

ABSTRACT. In many Model Based Enterprise (MBE) pilot programs for product realization, product acceptance has been one of the primary inhibitors for moving towards MBE implementation. Once an organization matures to realizing a Model-Based Definition (MBD) as the master authoritative definition both legally and functionally, assurance that product acceptance can be performed from an authorized part defining model is a critical driver toward achieving maximum MBE return on investment. Furthermore, determining an end-to-end model-based quality solution will enable the manufacturing quality function to become a primary advocate for MBE.

ABSTRACT. In this paper, we seek to provide multiple comparison studies to present use cases of automated 3D scanning both for in-lab and in-line applications. The primary goal of these comparison studies is not only to assess the return on investment from utilizing automated 3D scanning compared to the existing inspection methods, such as CMM or 3D scanning heads on CMMs, but also to highlight the productivity and user experience enhancement by utilizing the collaborative robotics instead of traditional industrial robots. First study calculates the cost savings from replacing CMM using a reference automated 3D scanning system with an area-laser based 3D scanner. Second study calculates the return from deploying the same reference system in-line to reduce scrap. Third study compares the benefits of using collaborative robots over traditional industrial robots and also using multi-line laser based 3D scanners over popular structured blue light scanners. Throughout this paper, in addition to evaluating the productivity of robotic automation of 3D scanning, we also seek to articulate the value of data automation that results in easier human-machine interaction in setting up complex inspection programs and advanced data analytics that maximizes the return from collecting high resolution 3D measurement at high frequency across supply chain.

ABSTRACT. The Quality Information Framework (QIF) standard was used to facilitate a MBD pilot at a Tier 1 Manufacturer. It specifically addressed the 3D data interoperability gap that exists when 3D data is passed from an OEM (Original Equipment Manufacturer) to a supplier. QIF v3.0 is an American National Standard that provides a common interface for digital interoperability that maintains the digital thread (3D data traceability) and enables closed loop feedback throughout product manufacturing. For example, it captures measurement results in the product model adjacent to the design requirement (i.e. tolerance). QIF defines, constrains, and provides for the exchange of Model-Based Definition (MBD), quality planning, measurement results, and enterprise connectivity via a persistent unique identification method called the QIF Persistent Identifier (QPId). QPId’s are universally unique identifiers (UUIDs). The use of QIF and QPIds allows for the digital capture of the design requirements and measurement results without manual data entry. The techniques and tools used in this pilot resulted in reduced lead time, increased data reporting accuracy, and improved OEM to supplier collaboration.

ABSTRACT. Augmented Reality (AR) for manufacturing-oriented use cases has recently gained wide interest due to the democratization of the core technologies, both software and hardware. Opportunities exist for co-developing standard guidelines, practices, and requirements to lessen the barriers for either new users to enter into this developing space or push advanced users to realize value. This panel will respond to feedback from the Augmented Reality for Enterprise Alliance (AREA) membership base regarding the opportunities, challenges, and overall vision for standards development in AR for smart manufacturing.

ABSTRACT. As of today, there are only very few CAD models with PMI that can be used in their current state. Most CAD models will have semantic errors in the PMI they contain. These problems are usually caused by a lack of knowledge about what the downstream consumers of the CAD model and its PMI require.

Using a Creo Model and the MBD Ready Check technology from Capvidia, we will show some semantic problems in PMI and how they can be corrected. Once fixed, the Creo Model will be made available in QIF format for downstream utilization. Consumers of QIF files created by Capvidia can be sure that the model can be used instantly.

ZEISS CALYPSO is one possible downstream application that consumes QIF formatted files. The QIF file can be treated just like any other native CAD file with the exception that a QIF file is error free. Consuming QIF in CALYPSO and creating an inspection from it is easy. Having it run on a CMM requires just a few user interactions and is done in a couple of minutes. Compared to other standard formats, QIF does not interfere with the intelligence embedded in downstream applications like CALYPSO.

ABSTRACT. The intent of Model-Based Enterprise is to allow downstream users and applications to be able to use the 3D model to perform their operations. It also provides for the traceability of downstream data to the authority CAD model, thus linking operations across domains. Some examples of this include: correcting GD&T errors or identifying issues with a specific tolerance due to machine limitations; or that a process is drifting out of control; or decision rules for what the corrective action is for process variations.

This demonstration will show how Semantic PMI enables a truly digital workflow. Using software tools from Capvidia and KOTEM, the viewer will see the following capabilities in action:

• Transmission of the authority CAD model’s geometry and PMI to downstream applications for software consumption and processing
• Return of the results of these downstream systems to the Digital Authority to allow for incorporation of changes to the model, and traceability of metrology results to the “Single Source of Truth.”

KOTEM is a leading supplier of advanced software for evaluation and fitting of measurement data, functional GD&T evaluation, and 3D best fitting solutions. KOTEM products are used by a wide range of manufacturers to design, fabricate and verify components tolerances since 1992.

Capvidia specializes in providing software solutions for CAD, MBE, and interoperability. The company has offered CAD plugins, standalone applications, and components (SDK) for CAD, PLM, CAE and quality processes since 1994.