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EAWS method

The EAWS method  was developed in Germany at the University of Darmstadt in order to materialize international standards for manual handling of loads (EN1005 and ISO 11228).

It is of workplace assessment that combines all aspects of manual load handling. It is a combination of posture, strength, weight and repetition.

Drawing EAWS method

the tools available for applying the EAWS method

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Worksheet  EAWS

Automate your ergonomic analyses with Nawo Live, with access to multiple methods and ergonomic standards.

THE EAWS QUOTATION GRID

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Indications

The EAWS method (Ergonomic Assessment Worksheet) is originally an extension of the Automotive Assembly Worksheet (AAWS) developed by IAD based on the “New Production Worksheet”, launched in 1997 by General Motor Europe (GME), and the “designCheck ”, produced simultaneously at Porsche. The development of the EAWS was carried out between 2006 and 2008 by international experts in occupational health, biomechanical engineering and industrial engineering from around the world, coordinated by the IMD (International MTM directorate).

It is a holistic system (covering all risk areas) that provides detailed results in four sections:

  • Body postures
  • Action forces
  • Manual handling of materials
  • Upper members
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Restrictions and limitations

This method was developed from the automotive industry, where one works with defined cycle times.

  • A task is constructed from standardized basic movements such as grasping, moving, walking.
  • Difficult and complex to use manually for measuring and adding posture times.
  • The process is long and tedious without software tools.

Interested in EAWS method ?

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Apply the EAWS method with Nawo Live

Nawo Live is your physical activity risk assessment tool for identifying risk factors for musculoskeletal disorders (MSDs).

In Nawo Live, automate and evaluate all biomechanical risk factors using reference methods (RULA, REBA, NIOSH, etc.).

Nawo Live guarantees you a reliability of the measurements acquired by our systems, including :

  • Automation of MSD risk factor calculations
  • Reliability of acquired data
  • Time saved by analysing thousands of postures
  • Exportable statistics in Excel format providing decision support