Development of an additive manufacturing decision support system (AMDSS)

PhD ThesisAdditive manufacturing (AM) technology describes a set of processes capable of producing 3D physical products from CAD data directly. The rapid development of AM technologies and their wide applications makes the selection of the suitable process chains and materials a difficult task. Some researchers have tackled this problem by developing selectors that should assist users in their selections. The existing selector systems have some drawbacks: (і) often being outdated even before they were completely developed because new processes and materials are evolving continuously, (іі) representing only the point of view of their developers because users were not involved in the development process and (iii) not being holistic and able to help in all AM aspects for example process chains, materials, finishing methods and machines. This work has developed an updatable decision support system that assists users in their selections regarding AM process chains, materials, finishing methods, and machines. First, the study started by analyzing the available additive manufacturing selector systems and identifying their shortcomings. Secondly, the researcher identified target specifications for the new system, investigated different possible architectures for the system, selected knowledge based system (KBS) and database (DB) architecture to work together as a versatile tool that achieves the required target specifications. Next, the first version of the system was developed. Furthermore, verification and validation processes were made to test the developed system. Three case studies were used for the validation purpose: a typical consumer razor blade and two automotive components. These case studies were manufactured using AM technologies and then a comparison between real life decisions and the developed decision support system decisions were made. In addition, a number of interviews were performed in order to obtain users’ feedback about the first developed version. As a result of the feedback and evaluation a second version of the system was developed and evaluated. The results obtained from the second evaluation suggest that the second version is more effective than the first version during the selection process. To conclude, this study has shown that using KBS and DB together is effective to develop an updatable additive manufacturing decision support system. In addition, the user involvement in the development stage of the system enhances the system performance.The Arab Academy for Science & Technology & Maritime Transport

Assessing additive and subtractive manufacturing technologies for the production of tools in the automotive industry

Tooling is an integral component to the traditional manufacturing cycle, despite the fact that it’s both costly and time-consuming to produce. Additive manufacturing (AM) is currently considered viable in certain instances, often competing against subtractive manufacturing in the delivery of tools, on time, with the required quality. This paper considers the use of AM and computer numerical control (CNC) machining to manufacture an insert for the tooling of a vehicle headlight adjuster clip. The proposed methodology for manufacturing the insert is composed of two manufacturing techniques: AM using selective laser melting (SLM) technology and CNC milling. The tool material used to manufacture the inserts in both cases is Stainless Steel 316L, whilst the injected parts are manufactured in polypropylene. Performance tests were applied to each of the two inserts in the context of material chemical composition, microstructure, hardness, surface roughness, and dimensional accuracy. Furthermore, the injected parts produced were tested to determine dimensional accuracy, quality and functionality. Finally, it was concluded that both the SLM insert and CNC machined insert successfully produced functional parts. Moreover, the products from the SLM tool insert were more accurate dimensionally, but in terms of surface finish, the CNC product was perceived to be better quality

A Novel Feature-Based Manufacturability Assessment System for Evaluating Selective Laser Melting and Subtractive Manufacturing Injection Moulding Tool Inserts

Challenges caused by design complexities during the design stages of a product must be coordinated and overcome by the selection of a suitable manufacturing approach. Additive manufacturing (AM) is capable of fabricating complex shapes, yet there are limiting aspects to surface integrity, dimensional accuracy, and, in some instances, design restrictions. Therefore, the goal is essentially to establish the complex areas of a tool during the design stage to achieve the desired quality levels for the corresponding injection moulding tool insert. When adopting a manufacturing approach, it is essential to acknowledge limitations and restrictions. This paper presents the development of a feature-based manufacturability assessment system (FBMAS) to demonstrate the feasibility of integrating selective laser melting (SLM), a metal-based AM technology, with subtractive manufacturing for any given part. The areas on the tool inserts that hold the most geometrical complexities to manufacture are focused on the FBMAS and the design features that are critical for the FBMAS are defined. Furthermore, the structural approach used for developing the FBMAS graphical user interface is defined while explaining how it can be operated effectively and in a user-friendly approach. The systematic approach established is successful in capturing the benefits of SLM and subtractive methods of manufacturing, whilst defining design limitations of each manufacturing method. Finally, the FBMAS developed was validated and verified against the criteria set by experts in the field, and the system’s logic was proven to be accurate when tested. The decision recommendations proved to correlate with the determined recommendations of the field experts in evaluating the feature manufacturability of the tool inserts

Response surface method for optimisation of SLA processing parameters

In the current study, response surface method (RSM) was applied to correlate stereolithography (SLA) process parameters such as layer thickness, hatch overcure, and part orientation to SLA part characteristics such as density, surface finish and ultimate tensile strength (UTS). The results showed that density was directly proportional to the hatch overcure but inversely affecting the layer thickness. Besides, the hatch overcure was shown to have a positive effect on the UTS, while the layer thickness was found to influence the UTS adversely. Furthermore, the relationship between the layer thickness and surface roughness was suggested to be directly proportional. The optimised values of process parameters indicated by the response surface model were 90°, 0.12 mm and 0.1 µm for the part orientation, hatch overcure and layer thickness, respectively. The corresponding predicted density, UTS and surface roughness of an SLA part were 1,098 kg/m3, 42.8 MPa and 5.31 µm, respectively

Selective Laser Melting for improving quality characteristics of a prism shaped topology injection mould tool insert for the automotive industry

Manufacturing process constraints and design complexities are the main challenges that face the aftermarket automotive industry. For that reason, recently, selective laser melting (SLM) is being recognised as a viable approach in the fabrication of injection moulding tool inserts. Due to its versatility, SLM technology is capable of producing freeform designs. For the first reported time, in this study SLM is recognized for its novel application in overcoming fabrication complexities for prism shaped topology of a vehicle headlamp’s reflector injection moulding tool insert. Henceforth, performance measures of the SLM-fabricated injection mould tool insert is assessed in comparison to a CNC-milled counterpart to improve quality characteristics. Tests executed and detailed in this paper are divided into two stages; the first stage assesses both fabricated tool inserts in terms of manufacturability; the second stage assesses the functionality of the end-products by measuring the surface roughness, dimensional accuracy and light reflectivity from the vehicle reflectors. The results obtained show that employing SLM technology can offer an effective and efficient alternative to subtractive manufacturing, successfully producing tool inserts with complex surface topology. Significant benefits in terms of surface roughness, dimensional accuracy and product functionality were achieved through the use of SLM technology. it was concluded that the SLM-fabricated inserts products proved to have relatively lower values of surface roughness in comparison to their CNC counterparts

Effect of Casting Conditions on the Fracture Strength of Al-5 Mg Alloy Castings

During the transient phase of filling a casting running system, surface turbulence can cause the entrainment of oxide films into the bulk liquid. Previous research has suggested that the entrained oxide film would have a deleterious effect on the reproducibility of the mechanical properties of Al cast alloys. In this work, the Weibull moduli for the ultimate tensile strength (UTS) and % elongation of sand cast bars produced under different casting conditions were compared as indicators of casting reliability which was expected to be a function of the oxide film content. The results showed that the use of a thin runner along with the use of filters can significantly eliminate the surface turbulence of the melt during mould filling which would lead to the avoidance of the generation and entrainment of surface oxide films and in turn produce castings with more reliable and reproducible mechanical properties compared to the castings produced using conventional running systems

Tool Life Performance of Injection Mould Tooling Fabricated by Selective Laser Melting for High-Volume Production

Rapid Tooling processes are developing and proving to be a reliable method to compete with subtractive techniques for tool making. This paper investigates large volume production of components produced from Selective Laser Melting (SLM) fabricated injection moulding tool inserts. To date, other researchers have focused primarily on investigating the use of additive manufacturing technology for injection moulding for low-volume component production rather than high volume production. In this study, SLM technology has been used to fabricate four Stainless Steel 316L tool inserts of a similar geometry for an after-market automotive spare part. The SLM tool inserts have been evaluated to analyse the maximum number of successful injections and quality of performance. Microstructure inspection and chemical composition analysis have been investigated. Performance tests were conducted for the four tool inserts before and after injection moulding in the context of hardness testing and dimensional accuracy. For the first reported time, 150,000 injected products were successfully produced from the four SLM tool inserts. Tool inserts performance was monitored under actual operating conditions considering high-level demands. In the scope of this research, SLM proved to be a dependable manufacturing technique for most part geometries and an effective alternative to subtractive manufacturing for high-volume injection moulding tools for the aftermarket automotive sector

A FULL PROOF OF UNIVERSAL INEQUALITIES FOR THE DISTRIBUTION FUNCTION OF THE BINOMIAL LAW

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Improving Quality Characteristics and Structural Integrity of Parts by SLA

Stereolithography is one of the most popular techniques of the additive manufacturing process that produces parts from a 3D CAD model by scanning an ultra violet laser beam over a resin liquid. This work studied the SLA parameters such as layer thickness, hatch overcure, and part orientation, which result in better part characteristics such as density, surface finish, and ultimate tensile strength. The optimum process parameters to achieve these part characteristics were also determined through an optimization study. Standard tensile test bars were manufactured using the SLA 5000 machine with different process parameters, and then the part properties were tested. For each part, the density was calculated through water immersion Archimedes method. Next, the surface roughness was measured using an Alicona Infinite Focus G4 optical scanner. Moreover tensile tests were carried out on each specimen using a MecmesinMultiTest5-Xt machine to find out the ultimate tensile strength. Design of experiments (DOE) was then used to correlate the process parameters to the part characteristics. Finally, the experimental data was analysed using design-expert software to predict the optimum process parameters based on the objective function which is to maximize the density and UTS of the SLA parts, while achieving minimum surface roughness