Layout design using an optimization-based human energy consumption formulation

Joo H. Kim, Karim Abdel-Malek, Zan Mi, Kyle Nebel

Research output: Contribution to journalConference articlepeer-review


An optimization-based method for layout design (also called equipment layout) is presented that is based upon kinetic functions also introduced in this paper. The layout problem is defined by the method whereby positions of target points are specified in the environment surrounding a human. The problem is of importance to ergonomists, vehicle/cockpit packaging engineers, designers of manufacturing assembly lines, and designers concerned with the placement of lever, knobs, and controls in the reachable workspace of a human, but also to users of digital human modeling code, where digital prototyping has become a valuable tool. The method comprises kinematically-driven constraints for reaching the target points and for satisfying the joint ranges of motion. The algorithm is driven by a cost function (also called objective function) that is kinetic in nature to minimize approximate energy consumption and visual discomfort. The formulation is not restricted by the number of degrees of freedom used to model the upper extremity or by the number of target points. A commercially available optimization code is used to implement the algorithm and to yield global optimum solutions. The method is demonstrated using a 15 degree-of-freedom model of the upper extremity. It is indeed shown that this method yields the most comfortable regions in space for a particular anthropometric model and for one or more cost function(s).

Original languageEnglish (US)
JournalSAE Technical Papers
StatePublished - 2004
EventDigital Human Modeling for Design and Engineering Symposium - Rochester, MI, United States
Duration: Jun 15 2004Jun 17 2004


  • Keywords Layout design
  • cost function
  • energy consumption
  • optimization
  • vision

ASJC Scopus subject areas

  • Automotive Engineering
  • Safety, Risk, Reliability and Quality
  • Pollution
  • Industrial and Manufacturing Engineering


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