Adaptive control optimization in micro-milling of hardened steels-evaluation of optimization approaches

Nowadays, the miniaturization of many consumer products is extending the use of micro-milling operations with high-quality requirements. However, the impacts of cutting-tool wear on part dimensions, form and surface integrity are not negligible and part quality assurance for a minimum production cost is a challenging task. In fact, industrial practices usually set conservative cutting parameters and early cutting replacement policies in order to minimize the impact of cutting-tool wear on part quality. Although these practices may ensure part integrity, the production cost is far away to be minimized, especially in highly tool-consuming operations like mold and die micro-manufacturing. In this paper, an adaptive control optimization (ACO) system is proposed to estimate cutting-tool wear in terms of part quality and adapt the cutting conditions accordingly in order to minimize the production cost, ensuring quality specifications in hardened steel micro-parts. The ACO system is based on: (1) a monitoring sensor system composed of a dynamometer, (2) an estimation module with Artificial Neural Networks models, (3) an optimization module with evolutionary optimization algorithms, and (4) a CNC interface module. In order to operate in a nearly real-time basis and facilitate the implementation of the ACO system, different evolutionary optimization algorithms are evaluated such as particle swarm optimization (PSO), genetic algorithms (GA), and simulated annealing (SA) in terms of accuracy, precision, and robustness. The results for a given micro-milling operation showed that PSO algorithm performs better than GA and SA algorithms under computing time constraints. Furthermore, the implementation of the final ACO system reported a decrease in the production cost of 12.3 and 29 % in comparison with conservative and high-production strategies, respectively

Multi-objective optimisation of product quality in the manufacture of Ti-6AI-4V prostheses

[EN] This paper presents a multi-objective optimisation procedure for optimising the quality of prostheses and manufacturing productivity. The aim of this procedure is to develop machining performance models through a minimal and progressive Design of Experiment (DoE), which models the variables of interest by linear regressions or Surface Response Models (SRMs). The multi-objective optimisation is based on desirability functions, which are defined according to the relative importance of each variable of interest. The procedure was implemented to optimise a process of manufacturing spherical turned components for Ti-6Al-4V hip prostheses with special requirements as regards surface roughness Ra, Rz and geometrical form toleranceThis work has been partially supported by Fundació Caixa-Castelló Bancaixa under the research project INV-2009-39. The authors are grateful to Miguel Angel Aymerich and Arcadi Sanz, who assisted in the experimental part. The authors extend their acknowledgements to Lafitt Company for its collaboration. Additional support was provided by Tecnológico de Monterrey through the research group in Mechatronics and Intelligent Machines.Abellán Nebot, JV.; Siller Carrillo, HR.; Vila, C.; Rodríguez González, CA. (2010). Multi-objective optimisation of product quality in the manufacture of Ti-6AI-4V prostheses. Journal of Manufacturing Technology Research. 5(3):353-369. https://doi.org/10.1504/IJMR.2010.033471S3533695

Micro-injection Moulding of Polymer Locking Ligation Systems

AbstractIn recent years, there has been an increment on micro-components for medical purposes, diseases treatment and surgical equipment, requiring biocompatible materials such as some engineering polymers. Nonetheless, the micro size of these parts impose challenges for fabrication using high production processes, like polymer injection moulding submitted to high cooling rates and variability of the process, in addition to the complex design of precise mould micro-cavities. This paper presents the development of a complete mould for a polymer locking ligation system fabrication, a medical device selected as a case study for micro-injection moulding tooling. This development includes the prediction of appropriate injection parameters and process conditions using computer simulations and a comparison with real values of pressure and temperature during the process, due to data acquisition with piezoelectric sensors. The results show a moderate error between experimental and simulated results, in terms of pressure (0.05% prediction error) and average cycle temperature at the sensor location (13% prediction error), which proves that the proposed approach can be used for precision micro-injection moulding applications

Fiber Laser Microcutting of AISI 316L Stainless Steel Tubes- influence of Pulse Energy and Spot Overlap on Back Wall Dross

AbstractThe design of coronary stents imposes high demands in terms of dimensional tolerance and surface finish. These devices are manufactured by laser microcutting of miniature tubes in materials such as stainless steel, cobalt chromium alloys and Nitinol. The work presented here is focused on fiber laser microcutting for coronary struts in AISI 316L stainless steel. This work studies the influence of gases such compressed air and argon passing through the tube in order to drag molten material while laser microcutting is performed. The experimental work studies the influence of beam spot overlap and pulse energy on back wall dross and average surface roughness, using response surface methodology. The results indicate that the introduction of compressed air or argon gas is a relevant method to reduce the amount of dross adhered in the back wall of the miniature tube

Process Chain for the Fabrication of a Custom 3D Barrier for Guided Bone Regeneration

Guided Bone Regeneration (GBR) is a surgical procedure that consists in the use of barrier membranes to cover bone defects caused by trauma, periodontal disease and other pathologies. These barriers allow the proliferation of bone cells, and prevent the invasion of the defect by non-osteogenic cells (connective and epithelium) in patients with a lack of horizontal and/or vertical bone. This process is essential for the successful dental implant placement. Additive manufacturing (AM) is emerging as an important tool for biomedical applications, especially for regenerative medicine and tissue engineering. This paper proposes a process chain for the fabrication of a custom barrier from cone beam computed tomography (CBCT) as Digital Imaging and Communication in Medicine (DICOM) files obtained from a patient with vertical bone resorption of the anterior maxilla.DICOM files have been processed with Invesalius 3.0 to obtain the tridimensional (3D) anatomy of the region of interest. This 3D model was cleaned, fixed, and smoothed. The prototyped model of the patient’s bone defect was further processed in Rhinoceros to offer a 3D architecture for cell growth. To obtain information of the thermal and mechanical properties a finite element method (FEM) was assessed. The prototype obtained was produced with fused deposition modeling (FDM) an additive manufacturing technology

Design Concepts of Polycarbonate-Based Intervertebral Lumbar Cages: Finite Element Analysis and Compression Testing

This work explores the viability of 3D printed intervertebral lumbar cages based on biocompatible polycarbonate (PC-ISO® material). Several design concepts are proposed for the generation of patient-specific intervertebral lumbar cages. The 3D printed material achieved compressive yield strength of 55 MPa under a specific combination of manufacturing parameters. The literature recommends a reference load of 4,000 N for design of intervertebral lumbar cages. Under compression testing conditions, the proposed design concepts withstand between 7,500 and 10,000 N of load before showing yielding. Although some stress concentration regions were found during analysis, the overall viability of the proposed design concepts was validated

Fuzzy logic scheme for tip-sample distance control for a low cost near field optical microscope

This article proposes a fuzzy logic control scheme for a control algorithm used with a scanning near field optical microscope

Optical method for distance and displacement measurements of the probe-sample separation in a scanning near-field optical microscope

This article presents an alternative optical method to determine the probe-sample separation distance in a scanning near-field optical microscope

Xurography as a Rapid Fabrication Alternative for Point-of-Care Devices: Assessment of Passive Micromixers

This article evaluates the viability of xurography as a rapid fabrication tool for the development of ultra-low cost microfluidic technology for extreme Point-of-Care (POC) micromixing devices

Cooperative Analysis of Production Systems with Simulation Techniques

In this work we present an analysis of simulation tools and modelling technologies for production systems. The use of these tools within a collaborative environment will be a mainstay for distributed manufacturing companies which require the integration of design, manufacturing resources and processes across the product lifecycle