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The purpose of this paper is to communicate a method to perform simultaneous topology optimization of component and support structures considering typical metal additive manufacturing (AM) restrictions and post-print machining requirements.

An integrated topology optimization is proposed using two density fields: one describing the design and another defining the support layout. Using a simplified AM process model, critical overhang angle restrictions are imposed on the design. Through additional load cases and constraints, sufficient stiffness against subtractive machining loads is enforced. In addition, a way to handle non-design regions in an AM setting is introduced.

The proposed approach is found to be effective in producing printable optimized geometries with adequate stiffness against machining loads. It is shown that post-machining requirements can affect optimal support structure layout.

This study uses a simplified AM process model based on geometrical characteristics. A challenge remains to integrate more detailed physical AM process models to have direct control of stress, distortion and overheating.

The presented method can accelerate and enhance the design of high performance parts for AM. The consideration of post-print aspects is expected to reduce the need for design adjustments after optimization.

The developed method is the first to combine AM printability and machining loads in a single topology optimization process. The formulation is general and can be applied to a wide range of performance and manufacturability requirements.

The purpose of this paper is to present a new method for automated post machining process planning for a hybrid manufacturing process. The manufacturing process is expected to generate complex functional parts by taking advantage of free form surface creation from additive manufacturing and high-quality surface finishing from CNC milling.

The hybrid process starts with additive manufacturing to generate a near net shape part with pre-defined machining allowances on surfaces requiring high quality surface or tight tolerances, along with integrated fixture geometry. The next step is to conduct automated machining process planning to determine critical parameters such as setup angle, tool selection, depth, tool containment, and consequently, the NC code to machine the part.

This method is shown to be a feasible solution for rapidly creating functional parts. The tests have been conducted to validate the method developed in this paper.

This paper introduces a new automated post machining process planning method for integrating additive manufacturing with a rapid milling process.

This paper aims to present an experimental investigation of improving the surface corrosion resistance of sintered neodymium-iron-boron (NdFeB) magnets by electrical discharge machining (EDM) in different dielectric fluids.

Scanning electron microscope and X-ray diffraction were used to analyze the surface morphology and chemical structure of recast layers formed by EDM using kerosene and distilled water as the dielectric fluids. Polarization scans and electrochemical impedance spectroscopy were applied to investigate the post-machining corrosion resistance.

The test results indicated that the recast layer produced during EDM had amorphous characteristics, and the newly formed amorphous structure could improve the corrosion resistance of the NdFeB material. The corrosion resistance of the recast layer formed in kerosene was better than that formed in distilled water.

Surface corrosion modification of sintered NdFeB magnets by means of electrical discharge with an ordinary copper electrode is proposed in this paper. The layer formed by EDM exhibits different behavior to that of the interior of the bulk material and improves the anti-corrosion performance of NdFeB magnets.

P.R.Webb, of the Cranfield School of Management, describes three case histories of the successful application of small computer systems

Experimental research was conducted on the effects of surface roughness on ultrasonic non-destructive testing of electron beam melted (EBM) additively manufactured Ti-6Al-4V. Additive manufacturing (AM) is a developing technology with many potential benefits, but certain challenges posed by its use require further research before AM parts are viable for widespread use in the aviation industry. Possible applications of this new technology include aircraft battle damage repair (ABDR), small batch manufacturing to fill supply gaps and replacement for obsolete parts. This paper aims to assess the effectiveness of ultrasonic inspection in detecting manufactured flaws in EBM-manufactured Ti-6Al-4V. Additively manufactured EBM products have a high surface roughness in “as-manufactured” condition which is an artifact of the manufacturing process. The surface roughness is known to affect the results of ultrasonic inspections. Experimental data from this research demonstrate the ability of ultrasonic inspections to identify imbedded flaws as small as 0.51 mm at frequencies of 2.25, 5 and 10 MHz through a machined surface. Detection of flaws in higher surface roughness samples was increased at a frequency of 10 MHz opposed to both lower frequencies tested.

The approach is to incorporate ultrasonic waves to identify flaws in an additive manufactured specimen

A wave frequency of 10 MHz gave good results in finding flaws even with surface roughness present.

To the best of the authors’ knowledge, this was the first attempt that was able to identify small flaws using ultrasonic sound waves in which surface roughness was present.

Submarine propeller shaft seals operate under onerous conditions in an aggressive environment and their effective life is vitally dependent upon the durability of the seal face materials. The combination of physical and mechanical properties of certain carbon‐carbon composites makes them potentially suitable for this critical service, but a literature search revealed no prior reference to their deployment in any liquid sealing application nor, indeed, to their behaviour in an aqueous environment. In consequence, a programme of work has been carried out to determine the effect of prolonged exposure to high‐pressure sea water upon their properties, and to assess their performance when run in a seal test rig against a variety of counter surfaces. The assessments were made under a reproducible condition of boundary lubrication stabilised by control of interface torque. The effects of composite anisotrophy and of graphitisation have been examined using specimen rings with the direction of fibre lay‐up either in, or normal to, the rubbing plane, and in the graphitised or non‐graphitised condition. It has been shown that the carbon‐carbon composites are stable in water and perform well as a seal face material; however, current high procurement cost will probably restrict their use to the more exacting applications.

The goal of this study is to carry out multi‐objective optimization by considering minimization of surface roughness (Ra) and build time (T) in selective laser sintering (SLS) process, which are functions of “build orientation”. Evolutionary algorithms are applied for this purpose. The performance comparison of the optimizers is done based on statistical measures. In order to find truly optimal solutions, local search is proposed. An important task of decision making, i.e. the selection of one solution in the presence of multiple trade‐off solutions, is also addressed. Analysis of optimal solutions is done to gain insight into the problem behavior.

The minimization of Ra and T is done using two popular optimizers – multi‐objective genetic algorithm (non‐dominated sorting genetic algorithm (NSGA‐II)) and multi‐objective particle swarm optimizers (MOPSO). Standard measures from evolutionary computation – “hypervolume measure” and “attainment surface approximator” have been borrowed to compare the optimizers. Decision‐making schemes are proposed in this paper based on decision theory.

The objects are categorized into groups, which bear similarity in optimal solutions. NSGA‐II outperforms MOPSO. The similarity of spread and convergence patterns of NSGA‐II and MOPSO ensures that obtained solutions are (or are close to) Pareto‐optimal set. This is validated by local search. Based on the analysis of obtained solutions, general trends for optimal orientations (depending on the geometrical features) are found.

A novel and systematic way to address multi‐objective optimization decision‐making post‐optimal analysis is shown. Simulations utilize experimentally derived models for roughness and build time. A further step could be the experimental verification of findings provided in this study.

This study provides a thorough methodology to find optimal build orientations in SLS process. A route to decipher valuable problem information through post‐optimal analysis is shown. The principles adopted in this study are general and can be extended to other rapid prototyping (RP) processes and expected to find wide applicability.

This paper is a distinct departure from past studies in RP and demonstrates the concepts of multi‐objective optimization, decision‐making and related issues.

The development by SIFCO Selective Plating of special Chromic and Phosphoric Acid in gel form is set to revolutionise the surface treatment of Aluminium, especially for its bonding and corrosion resistance.