The Open Design Lab at Penn State University

Research Areas

Designing for Human Variability encompasses a range of topics. Some areas of research at the Open Design Lab are described here. This page will likely grow as new areas of research are identified and pursued in the Lab.

Prof. Parkinson teaches a graduate-level course at Penn State that covers many of these topics. Read more about this class.

Allocation of Adjustability and Sizing

This is a broad container that encompasses many tools and concepts. The idea of optimally allocating adjustability is to prescribe only as much adjustability to a certain adjustable artifact as is necessary to accommodate a certain percentage of the target user population. Providing too little adjustability results in user discomfort and health/safety issues, whereas providing too much adjustability is costly or impractical.

Closely related to the allocation of adjustability is the specification of multiple sizes. For some artifacts, continuous adjustability is not possible or cost-effective, so the product is manufactured in multiple discrete sizes. In other cases, the amount of required adjustability is so great that multiple sizes of the adjustable artifact are manufactured. The goal of designing a product in multiple sizes is to determine the appropriate number of sizes and amount of adjustability per size (if applicable) for optimal accommodation and cost.

Prof. Parkinson was awarded a grant by the National Science Foundation (NSF) to research various aspects of the allocation of adjustability. Read more about this grant.

Related tools:
boundary manikins, digital human models, population models, hybrid models including residual variance, optimization

Synthesizing Anthropometry

Nearly all aspects of designing for human variability require the use of anthropometry, or body measurements. Sometimes, relevant body dimensions for the target population are known, but most often they are not. Therefore, standard databases of anthropometric data are used in place of data specific to the target population. Correctly applying known data to the problem at hand is critical for obtaining accurate solutions.

New methods have been developed in the Open Design Lab for synthesizing anthropometry that improve upon existing methods, such as Drillis and Contini proportionality constants. These new methods either synthesize a population of anthropometric data using linear regression (including residual variance) or provide more accurate and more useful proportionality constants (termed boundary ratios in the improved method).

Related tools:
anthropometric databases, proportionality constants, linear regression