The Integration of Artificial Intelligence and Robotics in Production Optimization of 3D Polymer Printing

The Integration of Artificial Intelligence and Robotics in Production Optimization of 3D Polymer Printing

A Study on Chennai Precision Engineering and Technology Cluster

E. Bhaskaran, Doctor of Science Scholar Mechanical Engineering,

Manipur International University, Manipur, India

Harikumar Pallathadka,

Vice Chancellor, Manipur International University, Manipur, India

S.Baskara Sethupathy

Professor and Head

Automobile Engineering, Velammal Engineering College, Chennai, India.

Abstract The Precision Engineering and Technology Centre (PETC) have Common Facility Centre namely EOS M 396 Selective Laser Sintering (SLS) Machine which is an Industrial Grade 3D Polymer Printing installed for use of all 40 Automotive Components Manufacturers at Tirumudivakkam, Chennai, Tamil Nadu, India. The objective is to study the technical efficiency for 6 input and 6 output variables related to SLS for traditional and AI integrated. The methodology adopted is collection of data from 40 automotive components manufacturers at Chennai. It is found that all the 40 ACM use the SLS with less service charge when compared to market price since they are all members in PETC. The technical efficiency of integrated AI is greater than traditional DMLS. The Design Softwares, Product Development Machines and Testing Machines are available in PETC, CFC so that 40 Automotive components Manufacturers can make use of with less service charge which leads to cost minimisation and profit maximisation. To conclude AI based usage leads to cost minimization and profit maximization of individual Automotive Components Manufacturers when compared to traditional usage of SLS.

Keywords Selective Laser Sintering, Precision Engineering Cluster, Technical Efficiency.

I. INTRODUCTION

The Precision Engineering and Technology Centre (PETC), an initiative of the Thirumudivakkam Industrial Estate Manufacturers Association in Chennai, is supported by the Government of Tamil Nadu under the Precision Manufacturing Mega Cluster Scheme. PETC is dedicated to empowering Micro, Small, and Medium Enterprises (MSMEs) by fostering innovation and facilitating new product development in the fields of precision engineering and automotive components manufacturing.

To accelerate product development, PETC offers industrial- grade 3D printing solutions that enable the creation of complex, customized, and organic-shaped components directly

from CAD models. This significantly reduces lead times and allows manufacturers to focus more on innovation.

All 3D printed parts achieve superior mechanical properties and dimensional accuracy, supported by advanced software features such as Smart Scaling, EOSAME, and continuous temperature monitoring. Exceptional productivity is delivered through a powerful laser, along with high-speed scanning and recoating capabilities. The system supports a wide range of industrial applications, enabled by 14 material types and 26 customizable parameter sets. Seamless integration into the Industrial Internet of Things (IIoT) via EOSCONNECT Core ensures a fully digital process chainfrom CAD model to ERP/MES systems, and finally to the finished part. Maximum machine uptime is ensured through remote digital track-and-trace capabilities, accessible anytime, anywhere. Comprehensive evaluation and documentation of every build cycle enables continuous optimization of the entire production workflow. [1]

Figure 1: Selective Laser Sintering for Polymer

A. Reliable Production with the Industrys Most Extensive Material Portfolio

The EOS P 396, a medium-sized and best-selling 3D printing system, supports seamless integration into Industrial Internet of Things (IIoT) environments. It enables flexible, tool-free productionfrom on-demand spare parts to full-scale serial manufacturing, ensuring high reliability and adaptability across applications. [1]

Source [1]

The Additive Manufacturing Lab at PETC is equipped with advanced 3D printing technologies capable of producing customized products, intricate tooling, and end-use parts with high added value. Notably, the facility includes a Selective Laser Sintering (SLS) machineEOS P396housed within the Common Facility Centre (CFC) as shown in figure 1. This system supports flexible, tool-free production of polymer parts, from prototypes to full-scale serial manufacturing. Materials processed include PA 2200 and Thermoplastic Polyurethane (TPU).

manufacturing. These characteristics align well with the goals of sustainable manufacturing and innovation in smaller-scale industrial settings.[5]

Government-supported initiatives, such as the Precision Manufacturing Mega Cluster Scheme, further strengthen the ecosystem by providing shared access to advanced manufacturing technologies.[6] Facilities like the Precision Engineering and Technology Centre (PETC) in Thirumudivakkam serve as key enablers, empowering MSMEs with state-of-the-art infrastructure, including the EOS P396, to develop high-value components for the automotive and precision engineering industries.[7]

III OBJECTIVE OF THE STUDY

1. To study and compare constant returns to scale technical efficiency (crtse) of Traditional and AI + Robotics Integrated SLS.

2. To study and compare variable returns to scale technical efficiency (vrtse) of Traditional and AI + Robotics Integrated SLS.

3. To study and compare scale efficiency (which is crtse divided by vrtse) of Traditional and AI + Robotics Integrated SLS.

4. To study on Design Softwares, Product Development Machines and Testing Machines available at CFC, PETC.

IV MATERIALS AND METHODS

II LITERATURE SURVEY

Additive Manufacturing (AM), also known as 3D printing, has revolutionized product development by enabling rapid, tool- free production of complex and customized components directly from digital CAD models. Among the various AM technologies, Selective Laser Sintering (SLS) stands out for its ability to produce high-strength, functional polymer parts suitable for both prototyping and end-use applications.

Studies by Gibson et al. (2015) have emphasized the advantages of SLS in producing geometrically complex parts without the need for molds or dies, making it ideal for low to medium-volume production. This is particularly beneficial for Micro, Small, and Medium Enterprises (MSMEs), which often face resource and time constraints in conventional manufacturing.[2]

The EOS P396 is a widely recognized SLS system, offering high precision, repeatability, and the ability to process materials such as PA 2200 and Thermoplastic Polyurethane (TPU). As highlighted in the Wohlers Report (2023), such systems have gained significant traction in the automotive sector due to their ability to reduce lead times and support lightweight, customized part production.[3]

Research by Dimitrov et al. (2006) demonstrates that SLS technology significantly shortens product development cycls by allowing quick iteration and testing of design variants. This rapid development capability enables MSMEs to stay competitive and responsive to market demands.[4]

In addition, Petrovic et al. (2011) discussed the environmental and economic benefits of AM technologies, noting their material efficiency and potential for decentralized

In PETC, the materials processed include PA 2200 and Thermoplastic Polyurethane (TPU).

A. Exceptional Materials Expertise for Additive Manufacturing EOS offers deep expertise in materials science and a comprehensive portfolio of advanced materials tailored for additive manufacturing. The materials, systems, and process parameters are precisely aligned to ensure optimal performance. By selecting the right material, one can achieve the ideal property profiles required for their products efficiently and reliably.

The methodology of the study is collection of input variables like Machine Operating Hours (Moh), Material Consumption (kg) (Mc),Energy Consumption (kWh) (Eckwh), Labor Hours (Lh), Setup Time (min) (Sut), and Maintenance Downtime (hrs) (Mdt) and output variables like Number of Parts Produced (Ppn), Part Accuracy / Tolerance Achievement (%) (Pata), First-Pass Yield (%) (Fpy), Production Lead Time (inverse) (Plt), Utilization Rate (%) (Ur) and Customer Delivery Compliance (%) (Cdc) for SLS from 40 Automotive Components Manufacturers. The description are given in table 2 and 3. The data are analysed using Output Oriented Multi Stage Data Envelopment Analysis (DEA) to find constant returns to scale (crste), variables return to scale (vrste) and scale efficiency.

CONCEPTUAL FRAME WORK

Source: Developed by Researcher

Source: Developed by Researcher

V RESULTS AND DISCUSSION

The Raw Materials used and Product Range produced by PETC are as given in table 4.

1. Raw Material usage in the cluster: The major raw materials used in the cluster include mild steel, carbon steel, alloy steel, stainless steel, aluminium, super alloy, special steels, non- ferrous metals, titanium, Chrome, nickel and Copper and so on. Most of these raw materials are available locally or obtained from other domestic markets and are manufactured in India.

2. Products produced by Cluster Members

Source: PETC, Chennai

The Technical Efficiency is calculated in table 5 and 6 for the input and output variables for traditional and AI integrated SLS respectively.

DATA ENVELOPMENT ANALYSIS

BCC-O Model

Source: Developed by Researcher

Max Z0 = Ø + 1 S+ + 1 S- Ø, , S+ , S-

Subject to

Ø Y0 – Y + S+ = 0 X + S- = X0

1 1 , , S+ , S- 0

Computing Methodology

Initially we consider First DMU as the studied DMU and the Linear Programming (LP) Model is formulated as given below Max Ø 0

Subject to

Y11 1 + Y12 2 + Y40 40 Y11 Output Constraints Y21 1 + Y222 +.. Y40 40 Y21 Output Constraints Y31 1 + Y322+.. Y40 40 Y31 Output Constraints Y41 1 + Y422+.. Y40 40 Y41 Output Constraints Y51 1 + Y522+.. Y40 40 Y51 Output Constraints Y61 1 + Y622+.. Y40 40 Y61 Output Constraints

X11 Ø 0 – X 11 – X12 2- .. X40 40 0 Input Constraints X21 Ø 0 X21 1- X222- X40 40 0 Input Constraints X31 Ø 0 X31 1- X322- X40 40 0 Input Constraints X41 Ø 0 X41 1- X422- X40 40 0 Input Constraints X51 Ø 0 X51 1- X522- X40 40 0 Input Constraints X61 Ø 0 X61 1- X622- X40 40 0 Input Constraints 1+2+ 40 =1.

1,2, 40 0, Ø 0 is unrestricted.

By solving the above equations and continuously changing the studied DMUs the value of is and Øis

The constant returns to scale technical efficiency (crste) for traditional is 0.992 and that of AI is 0.992. The variable returns to scale technical efficiency (vrste) for traditional is 0.992 and that of AI is 0.999. From the table 5 and 6, it is found that Scale Technical Efficiency for using AI integrated DMLS is 0.993 which is greater than traditional DMLS is 0.992.

The summary of Lamba peer weights is given in table 7.

EOS P 396: Productive mid-volume polymer laser sintering system is given in figure 3.

Usable build size: Width 340 mm

Depth 340 mm

Figure 3: SLS

Height 600 mm

Max. volume: 69.4l per build Main properties:

The workhorse in the mid-volume segment High mechanical homogeneity across full build

volume thanks to EOSAME feature

The raw materials used by Automotive Components Manufacturers at Tirumudivakkam are given in figure 4.

Figure 4: Raw Materials Used

Figure 5: Parts printed in SLS for Automotive Components

Manufacturers

The Parts printed in SLS for Automotive Components Manufacturers at PETC are shown in Figure 5.

3D Scanner

A 3D scanner is used to scan any physical object in three dimensions and provide the scan data into a digital format that can be used for the design, development, analysis, and

development process. The digital CAD file can be exported into different file formats. It can also export files in Standard Triangulae Language (STL) format and produce prototypes using 3D printers. Here, the granularity of scan data significantly decreases the manual time taken to produce a robust model. Early in the reverse engineering phase, high- quality CAD files' development significantly enhances the results through mitigating time and devaluation from improper data. 3D scanning enables any item to be studied in greater depth.

Figure 6 : 3 D Scanner

3D optical scanning technology as shown in figure 6 and technical specification in table 8, can deliver accuracy for complex machine parts used in various industrial sectors and how reverse engineering can be useful for manufacturing from existing products as reverse engineering is one of the best forms to manufacture prototypes or short productions.

Applications of 3D scanner includes digitize physical object, reverse engineering, designing of complex curved surfaces, calculation of tool wear, aerospace, development of industrial tools, prototyping, metrology, quality management, etc.

Technology Interventions

The key technologies that are required in the cluster along with the proposed intervention to be set up under the CFC are as shown in the figure 7 and the same is detailed in the table 9.

Figure 7 : Technology Intervention

Equipment and Technology options

For the proposed precision engineering cluster, following are the major Equipment and Technology options. The CFC will provide various machining support to MSMEs in the region. The machines in the production area would be the latest in its class and will have accuracies in the range of 10 microns or less on a case-to-case basis.

Due care has been taken during the identification of machines for production systems and associated services, processes, plants and equipment in the CFC. This will make the CFC environmentally friendly and energy efficient and would be better equipped to manufacture more products with less material, energy and waste.

Presently, the units in the Cluster do not have access to the facilities proposed as they are capital intensive.

Design

NX Mach 2 & Macp Product Design (Floating) NX Macp Mold Design (Floating)

NX Macp Progressive Design ( Floating) NX Easy Fill Analysis (Advanced)

NX Total Machining

CATIA Sheet Metal

CATIA Mechanical & Shape Designer CATIA Mold & Tooling

CATIA Stamping Die Designer CATIA Electrical 3D Designer

Figure 8 : Design Software

Analysis & Simulation

Figure 9: Analysis and Simulation

NX Easy Fill Analysis

CATIA Function Driven Generative Designer CATIA SIMULA Abaqus

Product Development

Figure 10: Product Development

Metal Additive -DIrect Metal Laser Sintering – -(DMLS) Machine

Polymer Additive -Selective Laser Sintering (SLS)

Testing

Figure 11: Testing

Universal Testing Machine for Plastic Material & Mechanical Optical Emission Spectrometer

Metallurgical Microscope Hot/cold Thermal Analysis X-ray Machine

Rubber tensile tester Chemical testing for Metals Salt Spray Test Chamber Shot Blast Testing

Standardization

Figure 12: Standardization

Co-ordinate Measuring Machine (CMM) Other Measuring Equipment

The above Design Softwares, Product Development Machines and Testing Machines are available in PETC, CFC so that 40 Automotive components Manufacturers can make use of with less cost which leads to profit maximisation.

VI. CONCLUSION

The Precision Engineering and Technology Centre (PETC) have Common Facility Centre namely EOS P 396 Selective Laser Sintering (SLS) Machine which is an Industrial-Grade 3D Polymer Printing installed for use of all 40 Automotive Components Manufacturers at Tirumudivakkam, Chennai, Tamil Nadu, India. The technical efficiency is calculated for 6 input and 6 output variables related to SLS for traditional and AI integrated. It is found that all the 40 ACM use the machine with less service charge when compared to market price since they are all members in PETC. The technical efficiency of integrated AI is greater than traditional SLS. The Design Softwares, Product Development Machines and Testing Machines are available in PETC, CFC so that 40 Automotive components Manufacturers can make use of with less service charge which leads to cost minimisation and profit maximisation. To conclude AI based usage leads to cost minimisation and profit maximisation of individual Automotive Components Manufacturers when compared to traditional usage of SLS.

ACKNOWLEDGMENT

The author acknowledges Department of Industries and Commerce, Government of Tamil Nadu where the author is working as Joint Director (Engineering) for giving permission to do Doctor of Science on Artificial Intelligence and Robotics. The author thanks Technical Staff of Precision Engineering Clusters, Tirumudivakkam for giving valuable guidance on 3 D printing plastics and metals, Scanner etc.

REFERENCES

1. https://www.eos.info/polymer-solutions/polymer-printers/data- sheets/sds-eos-p-396 accessed on 25.04.2025.

2. Gibson, I., Rosen, D. W., & Stucker, B. (2015). Additive Manufacturing Technologies: 3D Printing, Rapid Prototyping, and Direct Digital Manufacturing (2nd ed.). Springer. https://doi.org/10.1007/978-1-4939- 2113-3

3. Wohlers Associates. (2023). Wohlers Report 2023: 3D Printing and Additive Manufacturing Global State of the Industry. Wohlers Associates, Inc.

4. Dimitrov, D., Schreve, K., & de Beer, N. (2006). Advances in three- dimensional printing state of the art and future perspectives. Rapid Prototyping Journal, 12(3), 136147. https://doi.org/10.1108/13552540610670717

5. Petrovic, V., González, J. V. H., Ferrando, O. J., Gordillo, J. D., Puchades, J. R. M., & Díaz, C. A. (2011). Additive layered manufacturing: Sectors of industrial application shown through case studies. International Journal of Production Research, 49(4), 10611079. https://doi.org/10.1080/00207540903479786

6. http://www.tiema.co.in/images/PETC%20Presentation%20Public2024.p df assessed on 25.04.2025.

7. https://www.tansidco.tn.gov.in/pdf/tender/03-05- 2023/PETC%20Interior%201B-Tender%20Conditions.pdf