(+61) 0404 405 396

Generative Ergonomics

Computation Design - Product Service System


Generative ergonomics is a new method of design that develops highly tailored hand tools based on individual anthropometric data. It achieves mass customisation through the advent of novel hardware, computation design and additive manufacturing.
Hand tools are the primary interface for many operations in the workplace – a means by which we can engage, shape and re-imagine our world. However, through the industrialisation and mass manufacturing of tools, the development of products has become dominated by the study of ergonomics and anthropometrics. These methods of study attempt to quantify the infinite diversity present within the human form by constructing a normative ideology of a person’s shape.

The impact of industrialisation and conforming to standardisation is exemplified through hand tools – almost all tools are specifically designed for the use by men, and do not cater to the smaller hands of women or the divergence of the differently abled or ageing.

In this sense, design has become tailored to the needs of mass manufacturing rather than the needs of people. By designing towards the 50th percentile (the normative ideology of the end user), other users become marginalised not only physically – unable to engage with an object that actively ignores their needs – but are also ostracised socially, as they are rendered unable to participate within the communities, work and social systems that are accessible through the use of tools.


Generative Ergonomics redesigns how we develop tools by focusing on the individual end user rather than a speculative average.
The design of a handle is made through the construction of a mesh framework that inputs two data sets. The first is an individual end user’s anthropometrics hand data.The second is made up of the identified and controlled design variables that dictate how a hand should be positioned around the working end of a tool.

The user’s anthropometric data is collected by commonly used hand-tracking devices, such as a Leap Motion [TM] controller or Intel RealSense [TM]. These devices are capable of recording the spatial xyz location of individual bone lengths – such as the metacarpals and phalanges – as well as a user’s palm width up to a hundredth of a millimetre.

By combining these data sets, it is possible to build the initial mesh framework for the user’s end of the tool. This mesh framework can be subdivided multiple times to create a smooth surface.
Importantly, through each subdivision, the coordinate space and geometry of the handle have a direct correlation to both user data and design variables that dictate form and can be tested. Through this process, the form of a product gains clarity as its physical structure is given a direct and quantifiable relationship.

The construction of the framework can be understood as a common algorithm that is shared and tested among participating users; although the handle’s form will change based on an individual’s input, the experience and evaluation of design variables will be common.

By this process, the development of an object is pluralistic in nature, shifting the discussion away from the diversity of human form and towards the design variables that inform the shape of the object. Doing so maps the individual end user’s engagement and, through iteration, clarifies how best to arrange a product’s shape to inform a user’s interaction.

Subdivision of a cube


To test the framework, three divergent users were asked to participate and test secateurs designed by this method. Two 95th percentile right-handed male users and one 5th percentile left-handed female user were selected. Their unique anthropometric data was fed into the framework and the design variables were kept constant for the production of three separate tools.
Rather than 3D-print the handles, they were instead machined out of solid aluminium. This was done to ensure accuracy within the production and to avoid lower resolution in surface texture that may have impacted perceptions of comfort. The above illustration communicates the framework’s ability to cater to divergent hand shapes. Although the design variables were constant, the outcomes produced were widely dependant upon the anthropometric data.

This design research illustrates the inefficiency of designing products towards the 50th percentile and communicates the diversity that exists even within similar user groups, such as two different 95th percentile male right-handed users.


Generative ergonomics offers a new practice of design that has the potential to influence the way we develop products and understand human hand interactions.
The implementation of this method overcomes the restrictions of mass manufacturing that focuses on target user groups, instead placing the individual end users at the center of a product’s development and validification. Furthermore, it removes cultural bias and the designer’s own subjective perceptions of comfort by directly informing design decision making (variables) through the end user’s iteration and feedback.

By this innovation, it is possible to enrich the working lives of our citizens through redistributing product characteristics quickly and effectively based on unique anthropometrics and contextual use. Rapid design development and the tailoring of products has the capability of challenging diseases such as arthritis, repetitive strain injuries and musculoskeletal disorders by empowering users to continue rich working lives and aging in place. This is possible through understanding end-user capabilities and redistributing product characteristics to better suit their needs.  Through this design practice we can challenge the current methods of developing the everyday tool and no longer work within the container of standardisation. Advancements in manufacturing have empowered new production capabilities that rather than remove us from interaction will instead encourage mindful ritual engagement – it is a process of design that builds clarity through computation.



1) Purchase
A user engages the product system service, seeking to buy a new tool.

2) Scan and survey
The user is asked to complete a short survey – divulging their age, intended use of the tool, in what context and industry. The user’s preferred or working hand is scanned by a hand-tracking device gathering anthropometric data. This information is then passed on to the framework as input variables.

3) Framework
The user’s data is combined with the contextual design variables that have been aggregated from similar stakeholders, context and industry use. The outcome of these inputs produces a digital file that can then be fabricated.
4) OEM
Traditional methods of mass manufacturing are used to fabricate the working end of the tool, such as the weighted end of a hammer or the metric of a wrench. These elements are produced through traditional processes as they benefit from speed of production, material strength and reduced cost and fit with standardised hardware.

5) Additive manufacturing
The user end of the tool is produced through additive manufacturing. This process can quickly produce unique forms tailored to individual needs. Additive manufacturing facilitates complex 3D surfaces without high tooling cost and also allows exploration of density, texture and feel through a unique layering and patternation.

6) Assembly
The OEM components and handle are then shipped to the user with clear assembly instructions. This allows the user to develop a richer understanding of the product and empowers them to fix and repair the tool in the future if required.

7) Use
Through the use of tools, users are able to work, participate in leisure activities and join communities which, in their absence, would not be possible. This process of customisation of everyday products would empower users to have richer and longer working lives, facilitate greater productivity, mindful engagement and ageing in place.

8) Reflection
People’s bodies change due to age, disease and ritual behaviour. If subjective perceptions of comfort or discomfort are felt, a user will reflect on a tool and attempt to augment its structure to better suit their needs. For example, when we see someone wrap a cloth around a wrench to reduce the pressure of a tool so that it won’t dig into their hand. If the tool is not comfortable, it is possible to augment the user end to better suit an individual’s needs.
9) Survey
If a tool is not comfortable, the user can log online and complete a survey using a local perceived-discomfort hand map through an app. This mapping of discomfort is utilised to better understand pressure points and how a product is affecting the user’s subjective experience. This method couples qualitative and quantitative data, which will directly inform the design variables of the framework and builds clarity within product design development by establishing direct links between user testing, consumer feedback, product design variables and form. Once the review is complete, a new handle can be printed and shipped to the user.

10) Disassembly
As the tool has been designed for disassembly it is possible to recycle to components is facilitated. This is in stark contrast with current tools on the market, which are commonly manufactured through multi-material injection-moulding. The OEM component can be reused for future tools. If the handle is additive manufactured from one material it can recycled. If printed out of bio-polymer it can be composted.