Prototyping Human-Centered Products in the Age of Industry 4.0

2021 ◽  
pp. 1-15
Author(s):  
Salman Ahmed ◽  
Lukman Irshad ◽  
Onan Demirel
Keyword(s):  
Computer Aided Design ◽  
Industry 4.0 ◽  
Product Development Process ◽  
Digital Human Modeling ◽  
Fidelity Level ◽  
Human Modeling ◽  
Computer Aided ◽  
Aided Design ◽  
Digital Human ◽  
Product Interaction

Abstract Industry 4.0 promises better control of the overall product development process; however, there is a lack of computational frameworks that can inject human factors engineering principles early in design. This shortage is particularly crucial for prototyping of human-centered products where the stakes are high. Thus, a smooth Industry 4.0 transformation requires bringing computational ergonomics into the loop, specifically to address the needs in the digitized prototyping process. In this paper, a computational prototyping approach is explored that focuses on various fidelity levels and different human-product interaction levels when conducting ergonomics assessments. Three computational prototyping strategies were explored, including (1) a digital sketchpad based tool, (2) computer-aided design and digital human modeling based approach, and (3) a combination of computer-aided design, digital human modeling, and surrogate modeling. These strategies are applied to six case studies to perform various ergonomics assessments (reach, vision, and lower-back). It is suggest that designers must determine which fidelity level prototype to employ after applying a trade-off study between the accuracy of the ergonomics outcomes and the available resources. Understanding the intricacies between the fidelity level, type of ergonomic assessment, and human-product interaction level helps designers in getting one step closer to digitizing the human-centered prototyping in meeting Industry 4.0 objectives.

Computational Prototyping Methods to Design Human Centered Products of High and Low Level Human Interactions

2019 ◽  
Author(s):  
Salman Ahmed ◽  
Lukman Irshad ◽  
H. Onan Demirel
Keyword(s):  
Human Computer Interaction ◽  
Computer Aided Design ◽  
High Fidelity ◽  
Digital Human Modeling ◽  
Low Level ◽  
Human Modeling ◽  
Computer Aided ◽  
High Level ◽  
Aided Design ◽  
Digital Human

Abstract Incorporating human factors engineering guidelines early in design has the potential to reduce the cost and product lead-time to market. Also, products that go through strict ergonomics assessments are associated with better comfort and safety ratings. However, designers are often caught in the dilemma of what prototyping method to use when assessing product ergonomics early in design. This is especially problematic during the conceptual design phase before the physical prototypes are available or built. In this research, we explore the computational prototyping dilemma for early design ergonomics assessments from both fidelity and human-product interaction perspectives. In this paper, three computational prototypes with different fidelity levels (low, medium-, and high-fidelity) are compared in their adequacy for evaluating designs that comprise low- to high-levels of human-product interactions. We used three computational prototyping strategies: (1) Method #1 is a low-fidelity methodology based a digital sketchpad tool; (2) Method #2 is a medium-fidelity methodology consisted of computer-aided design and digital human modeling; and, (3) Method #3 is a high-fidelity methodology composed of computer-aided design, digital human modeling, and surrogate modeling. In order to perform computational ergonomics analyses using above approach, we selected a generic wall mounted cabinet design and a simplified Boeing 767 cockpit model as case studies to illustrate designs that require low- and high-levels of human-product interactions. Our preliminary results show that low-, medium- and high-level prototyping strategies produce similar ergonomics outcomes when evaluating low-level human-computer interaction (e.g., cabinet model). On the other hand, both low- and medium-fidelity (Method #1 and Method #2) prototyping strategies are limited in terms of providing detailed information about human performance when compared to high-fidelity prototyping (Method #3) in evaluating designs with high-level human-computer interaction (e.g., cockpit model).

Sustained CAD/CAE Application Integration: Supporting Simplified Models

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Robert Kirkwood ◽  
James A. Sherwood
Keyword(s):  
Computer Aided Design ◽  
Ad Hoc ◽  
Product Development Process ◽  
Solid Models ◽  
Computer Aided ◽  
Major Subset ◽  
Cad Cam ◽  
Cad Models ◽  
Manual Interaction ◽  
Aided Design

Abstract Computer-aided design/computer-aided manufacturing/computer-aided engineering (CAD/CAM/CAE) integration offers designers, analysts, and manufacturers the opportunity to share the data throughout the product development process. Finite element (FE) meshing applications integrated with the solid model data from CAD systems represent a major subset of CAD/CAM/CAE integration. In an earlier paper, it was demonstrated that virtual persistent identifiers (VPIs) can be used to assure or repair sustained integration with successive versions of neutral-format solid models. From that article, several follow-on issues become apparent. The geometry as per the CAE model often differs from the CAD model, so even with cross-format issues resolved, significant obstacles to sustained CAD/CAE integration remain. Along with simplification, the current article investigates additional techniques for further automating the recognition of changes between CAD models, reducing the manual interaction to just a few minutes. The article goes on to demonstrate how associativity can be sustained when using current versions of neutral formats like STEP and IGES. The overall point of the paper is to show that given a precise recognition of the differences between two solid models, a generalized means of ad-hoc integration is possible. This point is demonstrated through two case studies where simplifications of the CAD geometry are made to facilitate the meshing of the part. The integration is shown to be maintained across successive versions and to address a range of simplification processing. A summary of best practices for efficiently accommodating sustained CAD/CAE integration is also presented.

Digital Human Modeling for Workspace Design

2008 ◽  
Vol 4 (1) ◽  
pp. 41-74 ◽  
Author(s):  
Don B. Chaffin
Keyword(s):  
Computer Aided Design ◽  
Human Performance ◽  
Digital Human Modeling ◽  
Cad Systems ◽  
Work Settings ◽  
Biomechanical Models ◽  
Human Modeling ◽  
Digital Human Models ◽  
Manual Tasks ◽  
Digital Human

Digital human modeling (DHM) technology offers human factors/ergonomics specialists the promise of an efficient means to simulate a large variety of ergonomics issues early in the design of products and manufacturing workstations. It rests on the premise that most products and manufacturing work settings are specified and designed by using sophisticated computer-aided design (CAD) systems. By integrating a computer-rendered avatar (or hominoid) and the CAD-rendered graphics of a prospective workspace, one can simulate issues regarding who can fit, reach, see, manipulate, and so on. In this chapter, I briefly describe the development of various DHM methods to improve CAD systems. Past concerns about early DHM methods are discussed, followed by a description of some of the recent major developments that represent attempts by various groups to address the early concerns. In this latter context, methods are described for using anthropometric databases to ensure that population shape and size are well modeled. Efforts to integrate various biomechanical models into DHM systems also are described, followed by a section that outlines how human motions are being modeled in different DHM systems. In a final section, I discuss recent work to merge cognitive models of human performance with DHM models of manual tasks. Much has been accomplished in recent years to make digital human models more useful and effective in resolving ergonomics issues during the design of products and manufacturing processes, but much remains to be learned and applied in this rapidly evolving aspect of ergonomics.

Tetrahedral Mesh-Based Embodiment Design

2010 ◽  
Author(s):  
Sebastian Pena Serna ◽  
Andre Stork ◽  
Dieter W. Fellner
Keyword(s):  
Computer Aided Design ◽  
Development Process ◽  
Product Development Process ◽  
Tetrahedral Mesh ◽  
Semantic Features ◽  
Cad System ◽  
Embodiment Design ◽  
Computer Aided ◽  
High Level ◽  
Aided Design

The engineering design is a systematic approach implemented in the product development process, which is composed of several phases and supported by different tools. Computer-Aided Design (CAD) and Computer-Aided Engineering (CAE) tools are particularly dedicated to the embodiment phase and these enable engineers to design and analyze a potential solution. Nonetheless, the lack of integration between CAD and CAE restricts the exploration of design variations. Hence, we aim at incorporating functionalities of a CAD system within a CAE environment, by means of building a high level representation of the mesh and allowing the engineer to handle and manipulate semantic features, avoiding the direct manipulation of single elements. Thus, the engineer will be able to perform extruding, rounding or dragging operations regardless of geometrical and topological limitations. We present in this paper, the intelligence that a simulating mesh needs to support, in order to enable such operations.

scholarly journals Virtual Reality and Digital Human Modeling for the Physical Ergonomic Analysis in Product Development in Industry: A Systematic Review

2021 ◽  
Author(s):  
Adailton da Silva ◽  
Marcus Mendes ◽  
Ingrid Winkler
Keyword(s):  
Systematic Review ◽  
Virtual Reality ◽  
Product Development ◽  
Development Process ◽  
Product Development Process ◽  
Digital Human Modeling ◽  
Human Modeling ◽  
Physical Ergonomics ◽  
Development Phases ◽  
Digital Human

The efficacy of the product development process is measured by the ability to launch a project with product and production process specifications that could guarantee that the manufacturing can produce it with the least impact. If a problem is detected late, they bring consequences beyond the high cost of the solution, if related to physical ergonomics, which will influence the well-being of operators, productivity, and quality. Virtual Reality (VR) and Digital Human Modeling (DHM) are ones of the enabling technologies of Industry 4.0 and has already been applied on a large scale in industries such as automotive, construction, and aeronautics. However, even though the huge applications, these technologies are not yet applied by these industries for the analysis of physical ergonomics during product development phases. This study aims to characterize the state of the art and technology about the application of Virtual Reality and Digital Human Modeling for the physical ergonomics analysis in the during product development phases in the industry through a systematic review of the literature and patents. In patent documents recovery, we used Derwent Innovation database. The research is based on searching the selected terms in the title, summary, and claims of the documents through a search strategy containing IPC code and keywords. In articles recovery, we searched ScienceDirect, Springer, and IEEExplore databases for scientific publications. The search resulted in 311 patents documents and 16 articles in the scientific database. This study analyzed the patents to map out the technological progress in this area, where we found in the charts and data an increasing number of publications per year and a spread application with a considerable number of new technologies presented in these recent patents. The literature review indicated that Virtual Reality technology complements the Digital Human Modeling during physical ergonomics analysis for manufacturing process already designed. The majority of research on the use of VR and DHM technologies for physical ergonomics analysis focus on the automotive industry and the ergonomic assessment of workstations and current processes. Further research is needed to investigate how Virtual Reality and Digital Human Modeling might assist in the understanding of physical ergonomics in certain tasks throughout the product development process, such as the simulation of worker posture or effort when assembling parts.

Integration Infrastructure for a Simulation-Based Design Environment

1995 ◽  
Author(s):  
Chung-Shin Tsai ◽  
Kuang-Hua Chang ◽  
Jia-Yi Wang
Keyword(s):  
Mechanical System ◽  
Computer Aided Design ◽  
Large Scale ◽  
Product Development Process ◽  
Design Stage ◽  
Simulation Based Design ◽  
Simulation Based ◽  
Computer Aided ◽  
Aided Design ◽  
Functional Components

Abstract In this paper, the integration infrastructure for a simulation-based design (SBD) environment for mechanical system design developed at Center for Computer-Aided Design at the University of Iowa is presented. The SBD environment comprises the integration infrastructure and workspaces/tools that exploit Computer Aided Design (CAD)/Computer Aided Engineering (CAE) and software engineering technologies in support of design of large scale mechanical systems. The principal functional components of the SBD environment are engineering workspaces and CAD/CAE tools that bring engineers, servicemen, and customers early in the product development process to assess design of the product concurrently. The infrastructure is based on the newly invented engineering views that allow engineers from various disciplines to view the product with their own perspectives. The infrastructure allows engineers to create CAD and simulation models of the mechanical system, access engineering workspaces and CAD/CAE tools to perform multidisciplinary engineering analyses, use planning tools to create and manage simulation processes, communicate and exchange engineering data, and conduct design trade-off analyses and make informed decisions to yield a robust optimum design. The presentation given in this paper assumes that simulation-based design activities are performed in the product detailed design stage. The environment is being extended to support concept design.

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