Numerous publications are available in relation to several strategies for Design for Additive Manufacturing (DfAM). Achieving a very high degree of complexity and detail in a final product has become a possibility that has led to the restructuring and diversification of design ideas. With the additional freedom in the design workspace, there are supplementary design considerations/limitations as well for additively manufactured forms and optimising these provide the best outcome for specific design needs.
Robots are deployed for numerous applications and in various industries, with a continuous demand for more companies and manufacturers trying to integrate robotics and automation into their production lines . This wide adoption has also seen a reduction in cost for industrial robots, but the entry barrier of cost  is still considered high for some applications. These applications can include the food, packaging, and electronics industries, where the payload can be relatively lightweight . There are many potential applications where the industries outlined above can benefit if the appropriate robotic solutions are available .
With the development of innovative manufacturing solutions, additive manufacturing (AM), or more popularly known as 3D printing, provides a realistic approach to the design of lightweight and customised designs . In addition, its throughput and low-cost approach for initial prototyping solutions have drawn increasing research interest during the last decade. Therefore, integrating polymer-based 3D printing for manipulator fabrication with lightweight applications is central for further investigation concerning this study.
According to the ISO/ASTM 52900:2015 , additive manufacturing processes have been broadly classified into seven categories: (1) binder jetting; (2) directed energy deposition; (3) material extrusion; (4) material jetting; (5) powder bed fusion; (6) sheet lamination; and (7) vat photopolymerisation. The design specification and the choice of material influence the properties of the output . The wide availability of materials, with different mechanical and thermal properties, for various AM processes, provides better control of the desired characteristics of the design .
Geometric Dimensioning and Tolerancing (GD&T) is a protocol  at the centre of any mechanical design and is complemented by a multitude of manufacturing processes and material selection allowing for the exploitation of numerous opportunities. A CAD model’s mesh file manufactured using any of the above-mentioned different 3D printing processes tends to differ in dimensions, usually in a range of less than ± 0.5 mm . However, this value still represents a significant variation in dimensions for the robotics applications or for any other application requiring assembly of various 3D printed or off-the-shelf components. Hence, this dimensional deviation needs to be compensated  for at the design stage which adds to the overall design complexity. There has been some effort to standardise the GD&T characteristics of additively manufactured parts .
The whole process from CAD development to manufacturing of the final output includes several steps, each with a lot of options/variables and decisions to be made that affect the outcome's properties. These include- design considerations for AM, optimum quality for mesh export, various mesh file formats, slicing and printing parameters, multiple printing processes and materials etc. The research provides a method of discreetly weighting the qualitative variables and quantifying them for comparison to identify suitability.
In the past few years, advanced industrial companies have made solid progress in improving productivity along the manufacturing value chain. In the U.S., for instance, the productivity of industrial workers has increased by 47% over the past 20 years. However, the traditional levers that have driven these gains, such as lean operations, Six Sigma, and total quality management, are starting to run out of steam, and the incremental benefits they deliver are declining. As a result, leading companies are now looking to disruptive technologies for their next horizon of performance improvement.