Siglos X-XII".—En este tiempo la nobleaa evoluciona de

Digital human models (DHMs) are the names for a wide range of approaches to simulating human characteristics in the mechanical design of processes or systems. Recent overviews can be found in Chaffin (2005) and Delleman et al. (2004). The choice of model and the way a model is applied will depend on both the information available as model input, with more data being available in later design stages, as well as the nature (repetitiveness, variability, peak loading, kinematic profile, etc.) of the work to be evaluated.

3.3.1 Model types

In this chapter, we will consider biomechanical analysis and DHM at three different levels of complexity: load calculators and equations, simple mannequin models, and computer aided drafting (CAD) style mannequin models. There are many kinds of tools thatfit into these categories (and some that blur the lines); an‘‘inventory’’ listing a number of specific tools in these categories is available on the internet (Neumann et al., 2006).

Checklists and equation. Checklists and equation-based models are the least expensive (often free as pencil–paper tools) form of biomechanical assessment. These tools typically provide output in terms of‘‘points,’’ ‘‘red, yellow, green’’ risk levels, percent of population capable, or allowable load. The NIOSH equation (Waters et al., 1993), which calculates a

‘‘maximum permissible limit’’ for loads based on inputs of lifting characteristics like lift height, reach, frequency, and distance, is an example of this kind of ‘‘biomechanical model.’’ The ‘‘Snook’’ tables, psychophysically determined databases of human capability, which allow comparison of tasks to population perceptions of their capability, are another example (Snook and Ciriello, 1991). There are growing numbers of databases for many different tasks (e.g., Potvin et al., 2000). Any kind of checklist that integrates different aspects of the physical load can be considered as a kind of‘‘biomechanical model’’ as they provide means to evaluate the physical workload of a given situation. These tools have the advantage of being inexpensive (although costs rise when these are part of software packages) and can usually be applied quite quickly.

Simple mannequin models. Simple mannequin models are a step up in software sophisti-cation and usually include some form of virtual humanfigure whose posture the user can adjust to mimic the posture and load situation to be analyzed. These models may be two- or three-dimensional (3D) and are generally static. The software is usually stand-alone and the models will typically provide loading information in terms of moment, compression, and shear for the low back and other major joints. Models the authors are familiar with include WATBAK, Michigan's static strength prediction (3DSSP) software, and the BACKPAK model.

CAD style mannequins. CAD style mannequins are more sophisticated than simple man-nequins in their ability to connect with CAD software. These models allow a mannequin of a particular anthropometric size to be placed into a virtual workspace in order to judge reach andfit (What posture is necessary for a given body size to reach the component?), clearance (Does the operator have a clear reach or will something block the way?), and physical loading again in terms of moment, compression, and shear of the major joints. Once placed in a virtual workstation it is possible to see through the mannequin's eyes allowing the visibility of parts or joining-points that must be reached to be determined. Some models will include checklists such as RULA (McAtamney and Corlett, 1994), the NIOSH equation, or other calculation-type models as part of their ergonomics assessment suite. Examples of this kind of model include JACK, iGrip, Mannequin Pro (for more examples, see Neumann et al., 2006). CAD style mannequins are typically much more expensive than the simpler tools. If a CAD layout of the work systems to be analyzed exists, then analysis can proceed quite quickly (under 1 h). If, on the other hand, the virtual layout must be createdfirst, then the time required for a complete analysis may run to days.

3.3.2 Digital human models behavior

A major challenge for using biomechanical models in the design process is predicting the behavior of a human (or rather the DHM representing them) before material prototypes are available and before user trials can be performed. The exposure model presented previ-ously illustrated that the behavior of a person is a complex relationship of the environment, the description of goals and procedures, and idiosyncratic work methods. The relative contribution of these factors to behavior is not clear but substantial differences between persons can be observed for nominally the same job (Mathiassen et al., 2003). If a similar situation existed previously then future behavior can be predicted from it.

Working behaviors can be defined from a biomechanics viewpoint in terms of selected instants thought to represent peak loads, points of interest, static postures, or as a series of posture and load snapshots that correspond to work elements. A more complete

description of the activity would include the time histories of postures and loads. The importance of these time histories is presented in Wells et al. (in review). A number of ways for predicting behavior as tasks, postures, or time histories of loading have been developed.

A knowledge of cycle=task times, number of tasks, and object weights allows estimation of potential exposure; this can be available at early stages of the design process (stages 2–4 in Table 3.1). An example of this type of approach is seen in a study of the exposure of scaffolding workers. van der Beek and Frings-Dresen (1998) estimated exposure from administrative records and object weights. Although this was done when work was

Table 3.1 Summary of Design Stages, Ergonomic Parameters That Are Influenced by the Stage, Approaches to Manage Exposure Available at Each Stage

Development Stage 1. Project specifications Project specifications Similar systems analysis

Projected production volumes Embed assessment requirements into design process via

2. Product design Insert and fastening forces Ergonomic failure modes effects analysis (EFMEA)

Component weights and sizes Design for assembly=disassembly (DfA, DfD)

Action repetitions per product Strength and torque capability of users

Anthropometry 3. Logistics system Box sizes (layout and posture

implications) 4. Production strategy Generalflow pattern Flow simulation

Extent of manual assembly work

PTMS systems (e.g., ErgoSAM) Cycle=task times

Number of tasks per station 5. Layouts Reach distances for parts=tools

locations

Work-stop pattern DHM (for cumulative load) Task diversity

(continued)

already being performed, it could in principle have been estimated before scaffolding was available. Wells et al. review a range of methods that could be used to predict the time history of a job in the design stages based upon the then current engineering information (Wells et al., in review).

3.3.3 Mannequin positioning, inverse kinematics, and motion modeling

The interaction of a digital human mannequin with its environment offers designers a substantial challenge; how to position the mannequin to perform a given task? The mannequin may posses of the order 50 degrees of freedom. It is unreasonable to expect a designer to individually specify all these parameters for a given instant. Constraints in the form of functional ranges of motion or whole body balance and stability reduce the degrees of freedom of the mannequin, reducing the number of inputs required. Use of inverse kinematics (constraints in the form of relationships between segment movements) can help position the mannequin based, for example, upon foot position and hand position.

Even with these aids, positioning of even a single instant may be time-consuming. Once specified, these postures (and forces) are available for input into static biomechanical models.

Quasi-dynamic loading can be incorporated by adding inertial components to the

‘‘hand load’’ the model experiencing. This fails to include the dynamic loading due to the mass of the body segments themselves. New research models are beginning to include these inertial effects, although this requires more complicated data inputs since body accelerations must be measured.

A recent technique of motion modeling involves creating a library of tasks defined by gross posture and the start and end points of a segment, often the hand (Chaffin, 2005). The given task is then matched with a movement in a preexisting library and the kinematics is approximated from this movement library (e.g., Rider et al., 2005). The kinematics of the mannequin are then available for visualization and as input into a wide range of dynamic biomechanical models.

Table 3.1 (Continued) Summary of Design Stages, Ergonomic Parameters That Are Influenced by the Stage, Approaches to Manage Exposure Available at Each Stage

Development Stage

Note: Generally each method can also be applied in subsequent stages with increasing accuracy as more realistic and specific data or work task demands become available.