Polymer-Based Additive Manufacturing

Polymer-Based Additive Manufacturing: Comparison

Please note this is a comparison between Version 1 by Kartikeya Walia and Version 2 by Dean Liu.

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.

industrial robotics
low cost
additive manufacturing
polymer materials

1. Introduction

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 ^[1][2][3][1,2,3]. This wide adoption has also seen a reduction in cost for industrial robots, but the entry barrier of cost [4] is still considered high for some applications. These applications can include the food, packaging, and electronics industries, where the payload can be relatively lightweight ^[5][6][5,6]. There are many potential applications where the industries outlined above can benefit if the appropriate robotic solutions are available [7].

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 ^[8][9][10,11]. 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 ^[10][12], 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 ^[11][12][13,14]. 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 ^[13][14][15][15,16,17].

Geometric Dimensioning and Tolerancing (GD&T) is a protocol ^[16][18] 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 ^[17][18][19,20]. 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 ^[19][20][21][21,22,23] 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 ^[22][23][24][24,25,26].

2. Optimisation of parameters

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.

3. Significance of AM Integration with Robotics

With a process that is no longer bound by the limitations of conventional manufacturing methods, the introduction of industrial 3D printing technologies has brought a positive disruption in transforming design and manufacturing methods. Additive manufacturing relies on steady, repetitive motion to build each infinitesimal layer. Robotics is renowned for its repeatability and control. Both technologies complement each other, and this can be used to achieve positive results that can be shared with customers to provide an improved and more effective robotic system.

In 2018, consultancy McKinsey and Company published ^[25][99] “The Next Horizon for Industrial manufacturing: Adopting Digital Technologies in Making and Delivering”, which summarised the importance of disruptive technologies and their impact on industrial manufacturing. An excerpt from the report is mentioned below:

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.

Two of those disruptions named in the McKinsey report were additive manufacturing (3D printing) and robotics. The intersection of both presents a newfound potential for robotics companies and their customers.

As the robotics design process can be complex with numerous design iterations, 3D printing is ideal for rapid prototyping. This begins with a concept and different design parameters that are used to meet an intended application or routine. Prototypes may be developed quickly, inexpensively, and with little overall risk, through a 3D printing process.

During the initial stage of robot development, exploiting 3D printing can not only improve the technological solution, but provide design freedom, customisation, improved responsiveness, and sustainability and provide overall cost benefits. With the availability of engineering grade and composite 3D printing materials, the ability to create custom parts uniquely suited for an industrial task is an open domain to be explored. Additionally, part consolidation ^[26][100] helps with easier and less time-consuming assemblies. Another huge benefit of using 3D printing for robots and robotic parts is producing smaller volumes with no upfront costs. Low-volume builds can be profitable as moulds are not required and, in addition to the multitude of applications 3D printing, can support in relation to the robotics industry, provides a wide-ranging potential for future innovation.

4. Adoption in Research and Industry

There are numerous 3D printable robotic arms ^[27][101], including BCN3D Moveo ^[28][102], Zortrax Robotic Arm ^[29][103], and HydraX ^[30][104], but most of these are imprecise and lack the robust design features required for industrial use.

One notable 3D printed robotics arm which has potential in industrial applications is ‘Dexter’. It was developed by Haddington Dynamics ^[31][105], and they initially prototyped the whole robot using PLA parts which were later replaced by 3D printed parts made with micro carbon-fibre-infused nylon material. As individual components were stronger, component volume was reduced in comparison with cutting individual parts saving on materials and therefore overall costs. Additionally, they were able to consolidate parts together and bring down the number of individual parts required, hence reducing assembly time. Another interesting research domain for the application of polymer-based additive manufacturing is in soft robotics ^{[15][32][33][34][35]}[17,106,107,108,109], which is finding industrial suitability for end effectors.