Search results

A local company producing aluminum profile encounters frequent failures to bridge dies. In total, 22 dies failed within a year, entailing production disruptions and extensive downtimes. Bridges usually exhibit cracks on the ribs. The failure analysis of the failed parts has been performed in order to propose solution for correct and economical process. The paper aims to discuss these issues.

Recorded history was collected regarding tool’s material selection, manufacturing conditions, usage and service. A representative failed bridge was in depth analyzed. The piece was optically inspected. Rockwell hardness measurements and chemical analysis were performed. The paper is focussed on the microscopic examination of the failed parts. Specimens were cut from bridge’s ribs. Areas including cracks were analyzed on the cross section of the samples by optical and scanning electron microscopy. Local chemical analysis was made by X-ray microanalysis.

Design, deficiency and improper maintenance are considered to be responsible for the systematic die damage. Prolonged preheating duration and poor quality surfaces before nitriding render dies premature unusable. The preheating duration should be controlled and protective atmosphere should be used. Furthermore, it is suggested to protect the ribs during nitriding as a preventive measure against crack initiation. The bridge’s geometry can be improved by fabricating ribs with larger radii. A finer polishing is recommended.

The present analysis resolved a serious deficiency in extrusion production. Extended research has been conducted in the field of aluminum extrusion dies, nevertheless, the present work presents new metallographic aspects as well as some interesting notes regarding the repetitive nitriding of bridge dies.

In hot forging, a significant amount of forging force is used for overcoming frictional force at the die-billet interface. The high frictional force along with thermomechanical stress lead to wear, plastic deformation, mechanical fatigue and cracks, which reduce the service life of hot forging dies. Of all these different types of issues, wear is the predominant mode of failure in hot forging dies. This paper aims to describe mechanisms of wear transition in different loads at near forging temperature, occurring during sliding of chromium-based H11 tool steel specimens.

High temperature pin-on-disc tests are performed with pin specimens machined from bars of X38CrMoV5 steel, heat treated to surface hardness of 40-42 HRc. The disc is made of EN 31 steel with hardness of 60-62 HRc. Tests are performed at constant temperature of 500°C, and the normal load was varied from 20 to 70 N.

Scanning electron microscopy investigations on worn surface have revealed that wear is primarily due to abrasion and plastic deformation. The test results show an increasing trend in wear rate with increase in load up to 30 N, followed by a reversal in trend until 50 N. This transition in wear rate is caused by development of wear resistant layers, which are formed by compaction of wear debris particles on to the worn surfaces. These compact layers are found to be stable during load range from 40 and 50 N. However, with further increase in load, abrasive wear tracks are observed without any evidence of protective layers. As a result, there is an increase in wear rate with increase in loads above 50 N. In addition, plastic shearing was dominant over abrasive wear at this load regime.

The study on wear behaviour of H11 hot forging steel at 20 to 70 N will be an input to the research in hot forming industries.

This study aims to investigate the effect of vibration on ceramic tools under dry cutting conditions and find the optimum cutting condition for the hardened steel machining process in a computer numerical control (CNC) lathe machine.

In this research, an integrated fuzzy TOPSIS-based Taguchi L9 optimization model has been applied for the multi-objective optimization (MOO) of the hard-turning responses. Additionally, the effect of vibration on the ceramic tool wear was investigated using Analysis of Variance (ANOVA) and Fast Fourier Transform (FFT).

The optimum cutting conditions for the multi-objective responses were obtained at 98 m/min cutting speed, 0.1 mm/rev feed rate and 0.2 mm depth of cut. According to the ANOVA of the input cutting parameters with respect to response variables, feed rate has the most significant impact (53.79%) on the control of response variables. From the vibration analysis, the feed rate, with a contribution of 34.74%, was shown to be the most significant process parameter influencing excessive vibration and consequent tool wear.

The MOO of response parameters at the optimum cutting parameter settings can significantly improve productivity in the dry turning of hardened steel and control over the input process parameters during machining.

Most studies on optimizing responses in dry hard-turning performed in CNC lathe machines are based on single-objective optimization. Additionally, the effect of vibration on the ceramic tool during MOO of hard-turning has not been studied yet.

The study has been aimed to search an appropriate process environment for simultaneous optimization of quality‐productivity favorably. Various surface roughness parameters (of the machined product) have been considered as product quality characteristics whereas material removal rate (MRR) has been treated as productivity measure for the said machining process.

In this study, three controllable process parameters, cutting speed, feed, and depth of cut, have been considered for optimizing material removal rate (MRR) of the process and multiple surface roughness features for the machined product, based on L₉ orthogonal array experimental design. To avoid assumptions, limitation, uncertainty and imprecision in application of existing multi‐response optimization techniques documented in literature, a fuzzy inference system (FIS) has been proposed to convert such a multi‐objective optimization problem into an equivalent single objective optimization situation by adapting FIS. A multi‐performance characteristic index (MPCI) has been defined based on the FIS output. MPCI has been optimized finally using Taguchi method.

The study demonstrates application feasibility of the proposed approach with satisfactory result of confirmatory test. The proposed procedure is simple, and effective in developing a robust, versatile and flexible mass production process.

In the proposed model it is not required to assign individual response weights; no need to check for response correlation. FIS can efficiently take care of these aspects into its internal hierarchy thereby overcoming various limitations/assumptions of existing optimization approaches.

To explore a hybrid approach in order to attain optimal cutting conditions proficient of generating adequate dimensional accuracy in combination with virtuous surface finish during turning of commercially pure titanium (CP-Ti) grade 2.

In the present paper, an application of the hybrid fuzzy–VIKOR method has been proposed to estimate an optimal combination of process variables during turning of commercially pure titanium (CP-Ti) grade 2. Three distinct input factors, namely, cutting speed, feed rate and depth of cut, were selected, each varied at three levels. Thus, a series of experiments were performed based on Taguchi's 3-factor-3-level (L₂₇) orthogonal array. The major attention was given to acquire minimum cutting force and flank wear along with good surface finish. The adequacy of the proposed methodology was verified with the help of ANOVA test.

The results of the investigation revealed that the suggested hybrid technique is quite effective, easily understandable and time-saving approach, which can be successfully implemented to solve various problems either of similar or of different kinds.

Increasing demand of qualitative as well as low cost products is identified as the main challenging task in the current competitive market. Therefore, estimation and selection of the most suitable machining environment are of paramount importance in a real-time manufacturing system. Machining process involves both qualitative and quantitative factors, may be conflicting in nature, all to be considered together. Consequently, an appropriate combination of the machining variables is evidently desirable to meet the aforesaid challenges effectively.

This study reviews the extent of application of artificial intelligence (AI) tools in the construction industry.

A thorough literature review (based on 165 articles) was conducted using Elsevier's Scopus due to its simplicity and as it encapsulates an extensive variety of databases to identify the literature related to the scope of the present study.

The following items were extracted: type of AI tools used, the major purpose of application, the geographical location where the study was conducted and the distribution of studies in terms of the journals they are published by. Based on the review results, the disciplines the AI tools have been used for were classified into eight major areas, such as geotechnical engineering, project management, energy, hydrology, environment and transportation, while construction materials and structural engineering. ANN has been a widely used tool, while the researchers have also used other AI tools, which shows efforts of exploring other tools for better modelling abilities. There is also clear evidence of that studies are now growing from applying a single AI tool to applying hybrid ones to create a comparison and showcase which tool provides a better result in an apple-to-apple scenario.

The findings can be used, not only by the researchers interested in the application of AI tools in construction, but also by the industry practitioners, who are keen to further understand and explore the applications of AI tools in the field.

There are no studies to date which serves as the center point to learn about the different AI tools available and their level of application in different fields of AEC. The study sheds light on various studies, which have used AI in hybrid/evolutionary systems to develop effective and accurate predictive models, to offer researchers and model developers more tools to choose from.

The prime task of research in hot forging industry is to improve the service life of forging dies. The in-service microstructural changes that may occur in a die during hot forging is expected to significantly affect the service life. The purpose of this work is to analyse the microstructural evolution of double tempered hot forging dies in a real industrial environment, and the correlation of microstructural and microhardness evolution to the in-service wear and plastic deformation.

Specific hot forging tests were carried out on double tempered AISI H11 chromium tool steel for 100, 500 and 1,000 forging strokes. Macro analysis was conducted on die cross section to analyse the wear and plastic deformation at different stages of forging cycles. Microhardness and microstructural analyses were performed on the die surface after these forging tests.

The macro analysis on the transverse section of dies shows that wear is predominant during initial forging strokes, whereas plastic deformation is observed in later stages. Microstructural analyses demonstrate that during first 500 forging cycles, carbide population decreases at 63 per cent higher rate as compared to corresponding drop during 501 to 1,000 forging cycles. Additionally, the carbide size increases at all stages of forging cycle. Further, microstructural images from dies after 1,000 forging strokes show clustering and spherodisation of carbides by which the “blocky”-shaped carbides in pre-forging samples had spherodised to form “elongated spherical” structures.

The findings of this work can be used in hot forging industries to predict amount of wear and plastic deformation at different stages of service. From the results of this work, the service life of double tempered H11 hot forging dies used in forging without lubrication is within 501 to 1,000 forgings.

Most of the literatures are focussed on the cyclic softening of material at constant temperature. This work analyses the microstructural evolution of double tempered hot forging dies in a real industrial environment and correlates the microstructural and microhardness evolution to the in-service wear and plastic deformation.

The main purpose of the study was to analyze the relationship between cutting forces and tool wear during turning of steel 30CrNiMo8.

It is very important to find the optimal machining conditions to increase the tool life and to improve product quality. Width of tool wear was measured by universal microscope.

During experimental procedure, one chip shape was obtained for the given machining parameters. Results showed negligible tool wear for the given experimental conditions. In other words, the tool wear is negligible for one chip shape.

To increase tool wear, there are different chip shapes.

The purpose of this paper is to investigate the performance of powder-mixed electric discharge machining (PMEDM) using three different powders which are aluminium (Al), silicon carbide (SiC) and aluminium oxide (Al₂O₃). Besides that, the influence of different tool materials was also studied in this experimental investigation. Hence, the work material selected for this purpose was AISI P20 steel and tool materials were copper, brass and tungsten. The performance measures considered in this work were material removal rate (MRR), tool wear rate and radial over cut (ROC).

The process variables considered in this study were powder types, powder concentration, tool materials, peak current and pulse on time. The experimental design, based on Taguchi’s L₂₇ orthogonal array, was adopted to conduct experiments. Significant parameters were identified by performing the analysis of variance on the experimental data.

Based on the analysis of results, it was observed that copper tool combined with Al powder produced maximum MRR (58.35 mm³/min). Similarly, the Al₂O₃ powder combined with tungsten tool has resulted least ROC (0.04865 mm). It was also observed that wear rate of tungsten tool was very low (0.0145 mm³/min).

The experimental investigation of PMEDM involving three different powders (Al, SiC and Al₂O₃) was not attempted before. Moreover, the study of influence of different tool materials (Cu, brass and W) together with the different powders on the electric discharge machining performance was very limited.

This study aims to investigate the high-temperature wear behavior of the TiN- and AlTiN/TiSiN-coated WC materials.

The coating process was carried out using the physical vapor deposition (PVD) method. Wear tests were performed by a ball-on-disc wear device with a high-temperature wear module. In microstructural investigation of the materials, it was benefited from traditional characterization methods such as, SEM, EDX analysis and microhardness measurement.

The best wear performance was obtained with AlTiN/TiSiN-coated WC materials at all loads and temperatures, followed by TiN-coated and uncoated WC samples. An important wear was not observed on the samples tested at room temperature tests. It was found that the temperature increase is an effective parameter on the decrease of the wear resistance of the samples. In addition, it was seen that the increasing load and temperature change the wear mechanism on the uncoated WC sample. The wear mechanisms observed at high temperatures were delamination and oxidation for the WC, fatigue for AlTiN/TiSiN-coated WC and micro-scratch and micro-spalling for TiN-coated WC.

The results of the experimental studies demonstrated that hard coatings improving wear resistance of WC.