Cloud-Based Computer-Aided Engineering Education: Finding The

Paper ID #29350

Cloud Based Computer-Aided Engineering Education: Finding the Silver Lining

Dr. Derek M Yip-Hoi, Western Washington University

Dr. Yip-Hoi received his Ph.D. from the Department of Mechanical Engineering at the University of Michigan in 1997. Following his Ph.D. he worked for several years with the NSF Engineering Research Center for Reconﬁgurable Machining Systems also at the University of Michigan. His work involved supervision of sponsored research projects that focused on developing software applications to assist manufacturers design and plan operations on manufacturing systems that could be rapidly reconﬁgured to meet changes to a product’s design or production volume. Sponsors of this work included Ford, GM and Chrysler. In 2003 he joined the faculty of the Mechanical Engineering Department at the University of British Columbia as junior chair of an NSERC sponsored research program in Virtual Machining. After 3 years at UBC, he moved to the Department of Engineering Technology at Western Washington University to focus on teaching. His teaching and scholarship interests lie in the areas of design, CAD/CAM, CAPP, and CNC machining. Dr. Yip-Hoi is currently director of Western’s Manufacturing Engineering Program.

c American Society for Engineering Education, 2020 Cloud Based Computer-Aided Engineering Education: Finding the Silver Lining Abstract The availability of cloud-based technologies to support engineering education has seen significant growth in recent years. This includes design (CAD), analysis (FEA), and manufacturing (CAM and Digital Mock-Up) capabilities. The availability of affordable and broadly accessible 3D-printing is one major driver of this trend. This has created demand for cheaper, easier to learn and more simply deployed CAD systems for authoring parts that can be 3D-printed. Industry 4.0 is another driver. To support the Internet-of-Things high levels of information automation are needed throughout the product development process. CAx software developers have noted these trends and have brought to market new systems that are configured to be profitable in this new era. However, these systems present unique challenges in an educational setting that impact the choice of platform and how they are deployed for instruction and project work. Depending on the system, one challenge may be the level of IT support that is needed. The cost of use for systems is also a major consideration for universities. Some vendors have adopted the Software-as-a-Service business model, while others still require paying a hefty one-time licensing fee for student and faculty accounts and data storage. As a result, there can be a significant variation in cost for access to the available platforms. This cost can be justified partly by the difference in capabilities. Though most systems now bundle in basic analysis tools and some manufacturing, others provide additional capabilities in advanced manufacturing planning and simulation, advanced analysis, integrated product lifecycle management, process planning and project management tools, and systems engineering. Finally, though some may argue otherwise, there are employment advantages for graduates in some industries that do their CAx work using a preferred platform. This paper will present the plans, efforts and experiences to date in deploying and use of Dassault Systemes 3DExperience® platform within a Manufacturing Engineering curriculum. This is a multi-year effort starting with CAD and Analysis that will over time incorporate into the curriculum many of the additional capabilities mentioned above. Rationale for the choice of this system will be discussed along with the challenges encountered to date and those that need to be overcome in fully implementing the plan. The experiences of students taking their first class using this platform will be presented along with those of faculty who have needs for CAx in their teaching and research. Introduction Cloud-based infrastructures have found their way into the realm of CAD/CAM/CAE (CAx) and promise to revolutionize the way in which engineers engage in using these tools. In the same way that computers and CAD revolutionized the approach to creating engineering drawings, cloud-based solutions are revolutionizing how information is automated throughout engineering problem-solving and design processes. This can be viewed as part of the direction being set by Industry 4.0 and the drive to support the Internet-of-Things which necessitates high levels of information automation throughout product development. This includes all information related activities from content generation to management, retrieval, analysis and dissemination. In addition to the impact of Industry 4.0, the availability of cheap 3D Printing machines and services is driving the growth of cloud-based CAx technologies. Greater access to 3D Printing technology for everyday use has fueled the growth of affordable and easy to use cloud-based applications to support use of these machines. These applications are easier to use and typically more affordable than their desktop-based predecessors. They present options for authoring content and to easily use this content to create a physical product if only a prototype. Junk and Kuen [4] provide a review of different cloud-based systems and their capabilities to effectively support 3D Printing.

These trends have major implications for engineering education. Educators need to understand how information automation is going to impact the skill set for graduates entering the workforce and adapt instruction to accommodate for this. Curriculums that develop student’s skills in authoring using CAx tools must look to broadening this effort to include the other aspects of information automation. Educator’s must choose from the growing number of cloud-based systems available and strategize on how they are deployed for instruction and project work. Part of this strategy includes consideration of the available level of IT support. Cloud-based systems have the advantage of externalizing the effort needed to support Product Lifecycle Management (PLM). Universities no longer need to invest IT resources in setting up the server infrastructure to support this function. However, there are still IT needs that vary with the platform adopted. For example, some platforms run completely in the cloud (i.e. both data storage and computation) and can be used through a generic browser (e.g. Onshape®). Others require a heavy client to be downloaded onto a computer and rely on the Cloud mostly for data storage (e.g. 3DExperience). The latter require more in-house maintenance though the cost for developing and supporting a PLM infrastructure has been eliminated. This situation maybe transitionary as the trend seems to be towards shifting both data storage and computation to the Cloud. In their review of Digital Design and Manufacturing in the Cloud, Wu et al. [5] provide a technology guide to assist in making decisions on how best to select a Cloud-based application for use throughout product development. Though focused on the commercial customer their insight is useful for educators to also consider. The cost of use for systems is also a major consideration for universities. Some vendors have adopted a Software-as-a-Service (SaaS) business model, while others still require paying a hefty licensing fee for student and faculty accounts and data storage. There can be a significant variation in cost for access to the available platforms. This cost can be justified partly by the difference in capabilities. Most systems now bundle in basic analysis tools (e.g. FEA, Kinematics Simulation, CFD) and some manufacturing (e.g. CAM for CNC machining). The additional capabilities typically center around access to more advanced manufacturing planning and simulation (e.g. Robotics, Virtual Factory, Ergonomics), advanced analysis (e.g. Composites FEA), integrated Product Lifecycle Management, process planning and project management tools, and systems engineering. The integration of these tools within a single platform around a common database has advantages over disparate tools that need to be integrated, even though with standards this is getting easier. This presents unique challenges that will be discussed in this paper. Finally, though some may argue otherwise, there are employment (internship and permanent) advantages for graduates in some industries that do their CAx work using a preferred platform. Literature Review Wu et al. [1] pose the question “Is cloud-based design and manufacturing (CBDM) actually a new paradigm?” To answer this question they compare existing definitions related to the field of CBDM, develop a checklist with requirements that can be used to verify the existence of appropriate capabilities and provide a comparison with other related technologies such as web- and agent-based design and manufacturing. As part of this study, they develop a drone delivery system using existing CBDM tools such as Dassault Systemes 3DExperience platform (Software-as-a Service, SaaS), Compute Cloud® (Intrastructure-as-a-Service, IaaS), Google BigQuery® (Platform-as-a-Service, PaaS) and Alibaba.com® (hardware-as-a-Service, HaaS). They conclude that CBDM is in fact a new, emerging paradigm evolving from existing technologies that will revolutionize “digital manufacturing and design innovation” [1]. In their work, Vila et al. [2] note that CAx and PLM are taught separately and that a holistic approach is needed to support Industry 4.0 skills and competencies. They identify Project-Based Learning (PBL) as a method of practice and to support evaluation of project experiences where integrated CAx and PLM technologies are enablers. Two parallel projects involving 4 universities have been initiated to study experiences of CAx-PLM using two different platforms (Fusion 360® and 3DExperience) in manufacturing related courses. The intention is to benchmark these platforms with respect to the metrics of Data Management, Decision Support, Personal Data management, Project Management and Communication. Though a work in progress at the time of publication, the authors provide an initial benchmarking of the two platforms with respect to these metrics. However, they offer no clear preference of system based on findings to date though they point to challenges with project planning using Fusion 360. Barrie [3] also presents an evaluation of cloud-based CAD in an academic setting specifically looking at the Fusion 360 and Onshape platforms. In this evaluation the author points to the reluctance of universities to transition from more well-established desktop applications and the workflow challenges using cloud documents as impediments to adoption. As with the work by Vila, no preference is expressed for either of the two systems though it is noted that Onshape has a more advanced cloud-document workflow management system that may be challenging for traditional users to adapt to. This work does not include consideration of a fully integrated CAx- PLM system such as 3DExperience. Junk and Kuen [4] review a range of Open-Source and Freeware CAD Systems. Though this is for the purpose of 3D Printing, the evaluation criteria focus of general capabilities such as ease of use and scope of functions. Among the systems compared are AutoDesk 123D® (the precursor to Fusion 360), Onshape and a generic commercial CAD system which would include a platform such as CATIA® or 3DExperience. Their analysis concluded that Onshape led in ease of use while the generic system led in the scope of available functions. AutoDesk 123D trailed in both in ease of use, though not by much. They point to generating freeform surfaces as a complex feature used by professionals that requires extensive training. CATIA is widely acknowledged for its surface modeling capabilities. Le [6] compared Onshape and Solidworks using the Analytic Hierarchy Process (AHP) to perform a SWOT analysis. The conclusion from the AHP analysis was that users preferred Onshape for simple mechanical modeling suggesting that its advantages lay in its browser-based interface which eliminated installation and licensing, and its ability to allow merge/branch versions of a design. Wu et al. [7] provide a survey of Cloud-Based software tools for design and analysis. Their goal was to assess the extent to which both design and analysis capabilities could be executed using this new generation of systems and to review the key capabilities and benefits of available packages. In the area of design, the authors summarize features of AutoCAD 360, Fusion 360, Creo®/Windchill®, Teamcenter®/NX®/SolidEdge®, 3DExperience/Solidworks®/CATIA, Onshape and GradCAD®. We refer the reader to this source for details of their study while echoing their point that this is not an exhaustive list of available platforms, though we would argue that these are the major players. Though this source goes on to discuss issues such as “Performance Evaluation and Benchmarking”, “Usability Evaluation” and “Cybersecurity”, it poses these within the context of future research and does not offer any specific conclusions regarding differences in the platforms identified. They elaborate that the performance metrics include “speed up, scalability, reliability, and latency.” We would add that other important issues are availability of Training Resources and Ease of Learning of these platforms. The latter is distinguishable from the issue of “Usability Evaluation” which was largely defined in terms of bandwidth constraints and ease of use of workflows. These two issues are particularly important from an education perspective as each platform to a different extent requires additional skills development beyond just the ability to use a CAx tool in the traditional sense.

Though not exhaustive, these examples of recent work highlight the growing importance and interest on the part of researchers in understanding the impact of cloud-based CAx.

Manufacturing Engineering Perspective The perspective of CAx training from a Manufacturing Engineering perspective differs from that of other engineering disciplines particularly Mechanical Engineering. It should be noted that an ME’s exposure to manufacturing and the supporting use of CAx technologies can be quite limited in their degree work. Those who transfer to a MFGE career after graduation acquire the skills through appropriate supplemental training and practice. Both MEs and MFGEs get exposed to authoring content in their CAD and analysis (e.g. FEA) classes. MFGEs get exposure to authoring CAM content in courses related to CNC programming and robotics. These are often optional for MEs depending on their specialization through technical electives. A manufacturing engineer needs to be able to engage at any point in a product development cycle. They must bring to bear a vast reservoir of knowhow about how products can be feasibly and cost effectively manufactured with quality and how this impacts design and selection of tooling and equipment for fabrication and production. With the coming of Industry 4.0, the responsibilities and the skills for success are evolving. The increased need for automation of operations and information for all manufacturers (not just the largest) is changing and impacting the emphasis of the skill set. The Internet-of-Things as it extends to the factory floor is presenting opportunities and challenges for manufacturing engineers to leverage this information through data analytics and machine learning to improve profitability for their businesses. The other side of the coin is increasing the value derived from the information and modeling generated during the design and planning phases before production is initiated. The fusion of these two spheres of activities where modeling, simulation and analysis is informed by information generated during production to make real-time decisions that can improve throughput and quality is becoming a major emphasis for industry.

• Differences in Capabilities Though the issues identified by Wu et al. [7] must be acknowledge as important, in this section other capabilities of cloud-based CAx platforms that are impactful in an educational setting include the following. We follow this by a discussion of the platform currently being evaluated.

o Cloud Presence This capability refers to the degree to which a solution uses cloud resources. Some platforms use the Cloud for everything i.e. both data storage and computation (e.g. Onshape), while on the other extreme a heavy-client application is still needed for computation on a workstation, with the Cloud used only for data storage (e.g 3DExperience). o Licensing Newer cloud-based CAx platforms have pioneered distribution and licensing using the Software as a Service (SaaS) model. This conforms well with systems that are fully cloud present. This mechanism offers access to a broader range of potential users and is viewed to promote a given platforms market share. The SaaS model reduces in-house IT overhead. o Hardware Requirements This capability is impacted by the previous. Platforms that are fully cloud-based rely on standard browser capabilities for graphics and I/O. This has a low hardware requirement when compared to platforms that rely heavily on desktop computing power. High-end graphics cards are typically a requirement. o Level of IT Support This varies depending on how much platform accounts, storage and updating are managed as part of the licensing service. In some cases, this is largely transparent to the educational program (e.g. with SaaS distributed systems). In other situations, these must be administered by program IT staff and can be a significant workload. o Ease of Access The time required before a user can start authoring content and the speed of interaction thereafter is impacted by the need to use the Cloud. As a rule, these systems are slower than full desktop implementations. Among themselves, browser-based systems tend to suffer more from network latency issues during modeling work, while systems with a heavy-client tend to take longer to get up and running. o Ease of Data Management This starts with basic functions such as loading, search and retrieval, copying, renaming and deleting content. This varies between platforms, being significantly more difficult to perform in some cases. The need for compatibility with legacy PDM systems to ensure customers can transition data as they adopt the cloud-based functionality, is likely a factor. o Level of Out-of-the-Box Integration of CAE Functions As mentioned earlier, CAx platforms are increasingly able to integrate in CAE functions with CAD. Whether this happens out-of-the-box varies. For example, with a platform like Onshape, CAE comes from a third-party vendor such as Simcale® using a connector app to facilitate data transfer and in many cases associativity. These typically require separate licensing and present a new interface for the user to negotiate. On the other hand, platforms like 3DExperience provide full access out-of-the-box, guarantee associativity of data, a common user interface and typically provide a richer palette of CAE capabilities. o PLM Functionality Advanced PDM functionality such as version and workflow control maybe available but optional for use. Platforms vary in their ability to facilitate use of engineering authored information to support other functions such as project management, supply chain management (SCM), enterprise resource planning (ERP) and marketing. These capabilities are typically the subject of advanced technical electives in an educational setting. o Training Support All platforms provide extensive integrated training resources that can be used for flipped- classroom instruction. There are also in many cases third-party authored training materials available. However, while CAx training pedagogy is well developed in these, the same cannot necessarily be said for cloud-based PLM. This will undoubtedly change as educators increasingly adopt and develop best-practices using these tools that can be disseminated in new training materials. o Cost Effectiveness This can vary significantly between systems. In some cases, educational licensing comes without charge e.g. Fusion 360, Onshape. Others range in cost with fully integrated CAx and PLM platforms carrying a hefty licensing fee e.g. 3DExperience. It’s worth noting that with the large integrated platforms students are getting access to an extensive palette of CAx apps at a fraction of the cost that industry pays for even a single seat. In addition, there is new value to shifting to cloud-based access in that licensing fees now cover the cost of accounts rather than licensed software seats. This sales model allows students to install and use these tools on their own personal computing devices from any location with access to the Internet. o Professional Recognition Experience of a student using a specific platform can offer advantages to employers in industries influenced by a regional manufacturing emphasis e.g. automotive, aerospace. These may often be indicated as preferred qualifications on engineering job postings. Certification in use of a platform can also carry professional value, in particular the older CAx systems that have developed broad userbases e.g. SolidWorks, CATIA, NX, Creo. This credentialing is also becoming available for the Cloud-based versions of these. 3DExperience Platform Overview A brief overview of Dassault Systemes’ 3DExperience platform is in order as it is the cloud- based system for the case study to follow. The decision to use this platform stems largely from the tradition of the ENGD Department using CATIA as its primary instructional CAD/CAM system. This use goes back almost two decades to the time when CATIA was developed by IBM. Beyond just its technical capabilities, CATIA is a system that is used extensively regionally in support of the aerospace industry. So, graduates with experience in this system have this to promote their industry-ready credentials. 3DExperience is the evolution of CATIA. The department currently utilizes CATIA V5 as its primary CAD/CAM system outside of the case study course that will be described. Transition to V6 was considered and rejected several years ago largely due to the immense IT overhead needed to setup and manage on-site the PDM backend. The emergence of cloud computing has been a benefit in this regard. With the PDM backend supported by cloud IT services integrated in by Dassault Systemes, this overhead has largely been eliminated with 3DExperience. This has made transition to 3DExperience feasible for smaller engineering departments that do not have deep IT resource pockets. However, it does not come cheaply as the cost of these cloud services are included in the licensing fees. It should be noted that Dassault Systemes acquired SolidWorks back in 1997. Dassault is also integrating SolidWorks into the 3DExperience platform. In fact, it is possible to manage both CATIA-based and SolidWorks data using the same cloud tenant.

• Repackaging of Dassault CAE Applications The 3DExperience platform is largely a repackaging of the full suite of Dassault CAx and PLM applications using cloud infrastructure. This suite encompasses the design world with CATIA, manufacturing with DELMIA, simulation with SIMULIA, Product Lifecycle Management with ENOVIA and Systems Engineering with DYMOLA. Functionality is made accessible to users through “Apps”. In the case of CATIA, these apps roughly correspond to Workbenches in V5. Dassault’s business model for 3DExperience bundles Apps together aligned with various engineering-type roles. Examples of these roles include Mechanical Designer, Mechanical Analyst, Machine and Equipment Designer and Manufacturing Engineer. Dassault currently identifies over 300 such roles. This bundling presumably allows customization of the capabilities provided by a license to the needs of a customer. This would imply more efficient access to CAx tools, a win-win for both: Customer only pays for those apps an engineer needs to do their job, Dassault can market role bundles to an expanded range of engineering functions i.e. a larger number of end users. From an educational perspective, the current licensing for 3DExperience provides access to all apps through blanket Design and Engineering, Manufacturing and Production and Systems Engineering roles. This access to CAx tools goes way beyond anything available with the other cloud-based systems discussed in this paper. It’s also the type of access that will likely not be encountered outside of an academic setting because of the exorbitant cost of commercial licensing. Whether or not this access is meaningful and can be exploited to learning value within an engineering curriculum is of course an open question. • General Interface and Dashboard Concept The primary interface to 3DExperience is through a browser. The dashboard concept is used to allow the browser interface to be highly customizable by the end-user. Widgets that display and manage all the information stored in the Cloud can be configured on dashboard tabs. This includes widgets to display 3D content, perform markup, display documentation and perform project planning. This capability is transformative in how student teams working on a project communicate and collaborate. Access to apps is facilitated through a 4-way grouping into My 3DModeling Apps, My Simulation Apps, My Social and Collaborative Apps and My Information Intelligence Apps. Launching of an app can take a couple of minutes in some cases, though this time reduces significantly after the first app is launched. • Organization and Retrieval of Data One of the biggest challenges to using the 3DExperience platform is the storage and retrieval of content. It utilizes an advanced tagging scheme called 6WTags (Who, What, Where, When, Why and hoW) to organize content. Files are retrieved by searches that filter content using these tags. There is no default hierarchical organization to content such as a folder structure. This creates the biggest challenge to new users whose experiences are limited to desktop computing and server file management. However, users can create their own tags which are referred to as Bookmarks. Bookmarks can be nested hierarchically emulating a folder structure. Searches can be performed using bookmarks as filters or by using a Bookmark App which lists bookmarks using a tree structure and graphically displays tagged content that can be easily opened. • PLEXP (Peer Learning Experience) PLEXP is an integrated LMS that provides access to the training materials for learning 3DExperience. This provides over 100 courses and 1000 hours of material spanning all the authoring apps and platform operations, management and administration. Use of this resource is currently almost by necessity since there are few other instructional resources available on the market. SDC Publications provide one option with texts on CAD Modeling [8], Finite Element Analysis [9] and Mechanisms Design [10]. The PLEXP materials provide a combination of videos, background materials presented in slide format, exercises and case studies that provide varying levels of guidance as one progresses through the material. The LMS can be a bit tedious to navigate and sometimes suffers from network latency or hanging. Case Study of Instructional Use • Class in Advanced CAD and Analysis using Surfaces A pilot has been conducted over the past three years using 3DExperience for an advanced CAD class, MFGE 362. This class focuses on the use of surface modeling and analysis techniques to expand student’s skills in these areas. It is an evolution of a class previously reported on [10]. One addition of note over the previous version is a module on the modeling and analysis of composite products. These products are to a large extent fabricated by layups built on surfaces, hence the relationship to the modeling content in this course. This is to address a course outcome that students should acquire the ability to “Create a CAD model of a laminate composite product” and “Perform and validate a simple structural analysis on a laminate composite model using Finite Element Analysis.”

• Relationship to MFGE Curriculum

Figure 1. MFGE 362 and the MFGE CAD/CAM Curriculum Figure 1 illustrates the relationship of this course to the rest of the CAx intensive courses in the MFGE curriculum. For a description of the complete curriculum see [11]. MFGE 362 builds upon an introduction to CAD class (MFGE 261) where students are introduced to basic parametric modeling, assembly modeling and generative drafting techniques. It supports CAD and CAM experiences in the senior year such as CAD Automation and Advanced CAM and CNC. MFGE majors also have the option to take an injection molding tooling design class offered by the department’s Plastics and Composites program as a technical elective. Figure 1 clearly demonstrates the breadth of impact of adopting a cloud- based platform on the program’s curriculum. Though faculty have the option to choose the CAx tools that best suit the learning outcomes of their courses, practicality often dictates that it is easier to work with the system that students are already familiar with from earlier CAD instruction. Adopting 3DExperience would require each of the classes illustrated to re- structure experiences using the new platform. For example, MFGE 333 and 463 utilize Model-Based Definition [12] for teaching GD&T, MFGE 332 Prismatic (2½ D) Machining [13], MFGE 381 Ergonomics Design and Analysis, MFGE 434 Advanced Machining (3 – 5- Axis) and MFGE 466 the use of macro programming to automate CAx functions [14]. The references indicate previously reported work related to these classes that help explain the type of exposure students receive. It should be clear that the effort to adopt a new platform that integrates in cloud-based functions is significant and should not be underestimated. With 3DExperience, the content generating apps have also been redesigned to enhance the user’s experience over the CATIA V5 desktop application. This by itself requires a complete revamping of instructional materials and retraining for instructors using the new interface for effectiveness.

• 3DExperience Apps Utilized In MFGE 362 students are given an introduction at the start of the term to the 3DExperience platform using a video sequence. They follow this with a review assignment using the Part and Assembly Design Apps. Some limited video instruction is provided on these as students are already familiar with the equivalent CATIA V5 tools from their MFGE 261 training. This review is primarily helping students transition to using the new interface. Following this review, the training, assignments and project work focus on designing and analyzing models generated using surfaces with the following apps: 1. Generative Shape Design: This is the primary tool for modeling using surfaces in CATIA. Students are introduced to the various techniques and options for creating wireframe geometry and then using these to construct surfaces. Techniques such as sweeps, lofting (Multi-Section Surfaces in CATIA parlance), blends and a range of surface and modification operations (split, trims, shape and edge fillet) are covered. 2. Digitized Shape Preparation: This app is used to input 3D point cloud data and convert it to a mesh. This is used to instruct students on how to build CAD models through reverse engineering from a physical prototype. 3. Sketch Tracer: Drawings of a product created during design can be input using this app and curve modeling tools used to construct the wireframe foundations for the surfaces of the product. Engineers working with Industrial Designers on products with significant styling often receive drawings as an input to guide their modeling work. 4. Composites Design: This app provides a range of methods for modeling a laminate structure using a sequence of plies by layup on a surface. One of these, Grid Design supports optimization of the layup to meet varying laminate thicknesses and materials across the surface. 5. Structural Model and Structural Scenario: These two apps are used to setup a Finite Element Model and perform an analysis on a composites structure. These fall under the SIMULIA app grouping and utilize the Abaqus solver.

Given these apps, students are challenged to manage a range of data in the Cloud. Beyond the basic CAD models this includes, point cloud data, polyhedral meshes, images, finite element models, analyses and results. This as will be discussed later provides evidence of the ability of the platform to be effective while different types and size of data are transferred to and from cloud storage during CAx work.

• Examples of Training, Assignments and Project Work Figure 2, 3 and 4 give examples of the type of modeling and analysis work performed by students in MFGE 362. A significant number of the modeling assignments focus on the modeling of plastic molded products such as the three shown in Figure 2. This includes using the surface model of a product as a starting point to model a tool such as the calculator face mold shown in Figure 2(c). For composites design, modeling and analysis, a simple springboard is used. Though obviously trivial from a modeling perspective, the challenge students face is in redistributing material from a constant thickness design to meet a stiffness constraint with the objective of weight reduction. The Grid Design Method provided by the Composites Design App allows varying material thicknesses and ply sequences to be specified over a grid laid out on the surface (see Figure 3(a)) which is optimized into a ply lay-up (Figure 3(b)). The model is simple enough that it can be quickly solved using the FEA solver so that students can iterate their designs towards meeting the objective. The geometry and loading conditions are also simple enough for an analytical solution to be derived for the baseline constant thickness board as a basis for confirming the FEA result.

Figure 2. Examples of MFGE 362 Modeling Assignments The term project provides a more open-ended experience that requires use of 3D point cloud data and drawings to model an automobile body with accessories (e.g. rear wing, wheels etc.). This is also accomplished through teamwork which requires collaboration on the use of common CAD data stored in the Cloud. Top-down modeling techniques such as the use of skeletons and parametric data sharing between files using publications are practiced. Figure 4 shows and example of the input scanned data provided to team, the result of applying tools from the Digitized Shape Preparation App to create a healed polyhedral mesh, and a final result with integrated accessories.

Figure 3. Examples of MFGE 362 Analysis Assignments Student Feedback on Use of Platform Following the completion of the first two offerings of MFGE 362, students were surveyed on their experiences. Since this cohort of students had their preliminary CAD training using a traditional CAD system (CATIA V5), several of the questions were presented to solicit a comparison between their two experiences. The number of student participants in the survey was 43. Figure 4 shows the results on a set of general comparison questions between the two systems where the right side of the scale indicates greater agreement. Apart from searching and retrieval the answers skew towards use of the new 3DExperience platform. This is not surprising since as mentioned previously the switch to cloud-based data retrieval has been identified as the biggest challenge to adoption. Of note is that students see significant similarity between the actual mechanisms of modeling (question 3) with their earlier V5 experience and as a result their indication that this was helpful in them adopting the new platform (question 5). In this regard, another question on the survey showed that students recommended by almost 2 to 1 (63% to 37%) sticking with the current strategy of starting with CATIA V5 in their introductory CAD class (MFGE 261) before transitioning to 3DExperience. Finally, when asked “In the future, if you were given the choice to use 3DX or CATIA V5 to complete an assignment, which would you use?”, the response was 63% in favor of 3DExperience, 21% in favor of CATIA V5 and 16% having no preference.

Figure 4. MFGE 362 Project Work

Figure 5. A General Comparison Between 3DX and CATIA V5 Instructor and IT Support Feedback The instructor experience with using the 3DExperience platform indicates a significantly steeper and more drawn out learning curve over traditional CAx systems with all the extra effort focused on negotiating the challenges with cloud data storage and retrieval. Developing instructor level expertise is a drawn-out process and one in which learning of best practices for using the platform is sometimes a matter of trial-and-error. This is partly due to deficiencies in documented training, and guidance through what is available in a strategic way that helps an instructor understand the critical tools that are needed for managing data in the Cloud. One example of this is the use of Bookmarks that were described early. This feature is being used for the first time during the current offering of MFGE 362 largely because its value was not understood due to lack of emphasis and explanation in the available training materials. Bookmarking could significantly impact the experiences of students in search and retrieval of models, a deficiency indicated in the surveys discussed in the previous section. These types of problems are likely to resolve themselves as 3DExperience use increases both in academia and industry and better training materials that more clearly document best practices become available. From an IT support perspective, resources to support a PLM type infrastructure has not been totally eliminated through use of the Cloud. 3DExperience requires universities to administer their own cloud tenants which includes setting up accounts for students and faculty and controlling how the cloud storage is utilized. Some of the other available CAx platform options provide external support for these functions, completing removing this IT overhead. The use of a heavy client that goes through regular revisions also requires significant IT support in updating laboratory computers when revisions are pushed out. These can sometimes happen at inconvenient times. Again, by way of comparison, a system such as Onshape which runs completely in the Cloud and requires only a standard browser for use, does not have this overhead or potential for disruption. On a positive note, notwithstanding the range of data used for work in MFGE 362 which includes large datasets such as 3D point cloud scans and finite element models, latency of the platform in communication with the cloud has not been observed as a major impediment. Discussion In “Finding the silver lining” for cloud-based CAx in education, there are two questions that universities need to answer. The first is given that these systems add more technology skills development to curriculums that are already crammed full, is this value added? And second, if the answer to this first question is in the affirmative, then which of the available platforms makes the most sense to adopt? It’s becoming apparent from the trajectory of technology evolution that the answer to the first question is “yes”. CAx technology and related skills development over the past two decades has been fused with PLM in industry i.e. CAx+P. While CAx focuses on authoring information, P has dealt with information management and dissemination. Industry 4.0 is further transforming the meaning of P to embrace how information can be automated to serve model-based decision making. Integral to this is the concept of the Digital Thread that is infused with intelligence derived from Data Analytics of production operations. The Cloud as an enabling mechanism is both driving industry at an increasingly faster pace in this direction and making it increasingly more feasible for these technologies to be adopted at least partially by university engineering programs. To ignore this is to risk ignoring a growing need for information related skills that industry will increasingly seek from engineering graduates to exploit the benefits of Industry 4.0. There is an argument to be made that we are at a transformational point in the evolution of technology due to Industry 4.0 that is not unlike the transformation ushered in when CAD became a viable replacement for the paper drawing. On the second question, there is the temptation to base this choice solely on cost and ease of use. A second argument often made is that CAx skills are transferable and consequently it does not really matter which platform is used in an educational setting. Graduates will retrain as needed once they enter the workforce. While there is some truth to these positions, our perspective is that the implications of CAx+P and other situational factors also need to be considered in deciding which platform is the best the adopt. P will be a critical component in leveraging information automation in the service of Industry (Industry 4.0). Its inclusion creates an additional dimension of variability when making educational technology choices, that is the ease of P-type skills acquisition possible using a CAx+P platform. This choice is further complicated by the continuing lack of clarity at as to what exactly P-type skills might be. This is a question that has been in the asking since PDM/PLM technologies have emerged which might finally be answerable due to the impact of the Cloud on these technologies. Other situational factors as mentioned earlier include the degree type and regional industry influence. The consideration of 3DExperience for use in this MFGE program weighs these significantly. Access to a broad range of manufacturing apps including those that support CAM for machining, ergonomics, robot programming and simulation and factory flow (discrete event) simulation make this platform a potential one-stop-shop for these capabilities as opposed to having to assemble and license these from individual vendors. It should be noted that it is certainly easier today to do the latter than in the past. Many vendors are eager to provide educational access to their products to promote their long-term use in industry. And increasing data compatibility and standardization makes integration of these tools much easier. However, there is still an advantage to not needing to shop around and eliminating the additional IT overhead in licensing, installation and integration, providing the apps are capable and the cost is justifiable. The regional aerospace influence and the commitment of the two largest commercial global aircraft manufacturers to using 3DExperience for the next generation of products, also weigh in favor of its adoption. For future work, the impact of 24/7 access to a CAx+P platform on student learning is one of great interest. The availability of these tools and data through the Cloud makes their use outside of a lab setting feasible and desirable. The limitation in the current setting is students not having access to a computer and Internet connection adequate for the job. Some do, but many do not. The department is considering implementation of a laptop program for its engineering majors to ensure that all students have this access and benefit equally. Of interest is how much students are motivated to learn beyond the classroom/laboratory because of ease of access, and how much does this impact innovation in project work (similar to how easy access to 3D Printing has spurred innovation). Another area of interest for future work is the impact of integrated Virtual Reality capabilities that come with 3DExperience on learning and project work for manufacturing oriented topics such as Robotics and Ergonomics.

Conclusion In conclusion, it seems unavoidable that engineering educators must embrace some form of cloud-based CAx+P as the fourth industrial revolution unfolds. These systems are making feasible the use of PLM capabilities that have until now presented major implementation resource challenges to smaller engineering programs. However, adoption is still not resource neutral and major questions are yet to be answered on what value is added with investment. Part of the challenge is that available platforms differ on how much additional effort is needed to negotiate the data management aspects. This is a choice that needs to be made considering a range of capabilities that have been identified in the paper that includes consideration of what best supports the engineering discipline in question and regional industrial influence. A case study conducted using 3DExperience in an advanced CAD and analysis class within a Manufacturing Engineering program has shown that the system can handle a broad range of complex data used in product design and analysis. Further, student experiences to date in this class have favored use of this platform over the desktop version used for their introduction to CAD class, though a majority would prefer that they had this type of introduction first. Instructor experiences indicated a steep learning curve that requires continual engagement to maintain proficiency and at times trial-and-error to identify best practices that are currently not clearly documented. Familiarity of the program with CATIA, the broad range of manufacturing related apps available out-of-the-box, and the regional aerospace influence that favors the Dassault Systemes products are influencing factors in the decision to adopt this platform. The next step would include expanding use to other CAx intensive classes in the curriculum in particular those that teach CAM for machining. References 1. Wu, D., Rosen, D.W., Wang, L. and Schaefer, D., 2015. Cloud-based design and manufacturing: A new paradigm in digital manufacturing and design innovation. Computer- Aided Design, 59, pp.1-14. 2. Vila, C., Ugarte, D., Ríos, J. and Abellán, J.V., 2017. Project-based collaborative engineering learning to develop Industry 4.0 skills within a PLM framework. Procedia Manufacturing, 13, pp.1269-1276. 3. Barrie, J., 2016. Applications for cloud-based CAD in design education and collaboration. In DS 83: Proceedings of the 18th International Conference on Engineering and Product Design Education (E&PDE16), Design Education: Collaboration and Cross-Disciplinarity, Aalborg, Denmark, 8th-9th September 2016 (pp. 178-183). 4. Junk, S. and Kuen, C., 2016. Review of open source and freeware CAD systems for use with 3D-printing. Procedia CIRP, 50, pp.430-435. 5. Wu, D., Terpenny, J. and Schaefer, D., 2017. Digital design and manufacturing on the cloud: A review of software and services. AI EDAM, 31(1), pp.104-118. 6. Le, N., 2018. "Product Design with Cloud Based and Desktop CAD software: A comparison between SolidWorks and Onshape." Degree Thesis, Plastics Technology, Arcada University, Finland. 7. Wu, D., Terpenny, J. and Schaefer, D., 2016, August. A Survey of Cloud-Based Design and Engineering Analysis Software Tools. In ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers Digital Collection. 8. Zamani, N., 2017. CAD Modeling Essentials in 3DEXPERIENCE 2017x Using CATIA Applications. SDC Publications. 9. Zamani, N., 2017. Finite Element Essentials in 3DEXPERIENCE 2017x Using SIMULIA/CATIA Applications. SDC Publications. 10. Zamani, N., 2017. Mechanism Design Essentials in 3DEXPERIENCE 2016x Using CATIA Applications. SDC Publications. 11. Yip-Hoi, D., “Teaching Surface Modeling to CAD/CAM Technologists”. The Proceedings of the 2011 ASEE Annual Conference, Vancouver, B.C., Canada, June 2011. 12. Yip-Hoi, D., Newcomer, J., “Conforming a New Manufacturing Engineering Curriculum to the SME Four Pillars”. The Proceedings of the 2015 ASEE Annual Conference and Exposition, Seattle, Washington, June 14th – 17th. 13. Yip-Hoi, D., Gill, D., “Use of Model-Based Definition to Support Learning of GD&T in a Manufacturing Engineering Curriculum”, Proceedings of the ASEE 2017 Annual Conferences, June 25th – 28th, Columbus, OH, USA. 14. Yip-Hoi, D., “Using Simulation to Improve the Efficiency of CAM and CNC Instruction”. The proceedings of the 2013 ASEE Annual Conference, Atlanta, Georgia, June 2013. 15. Yip-Hoi, D., “Strategies for Teaching CAD Automation to Engineers and Technologists”. The Proceedings of the 2010 ASEE conference, Louisville, Kentucky, USA, June 2010.