Manufacture Of Cutting Tools Research Articles

Route to Carbon-Neutral

Sandvik Coromant’s Gimo plant is aiming to be carbon-neutral by 2035 and the cutting tool manufacturer is utilising the benefits of CGTech software to reach that goal

Tooling Moves Pay Off

Volz Engineering has seen the benefits of a bespoke step drill from Ceratizit and has reaped the rewards of installation of a vending machine from the cutting tool manufacturer

Sintering Technology of Cemented Carbide Cutting Tool Based on Digital-Twin

Cutting tool sintering process is one of the key links in cutting tool manufacturing process. Various physical quantities change with time during cutting tool sintering. As the sintering quality of cutting tool is directly affected by these changes, it is very difficult to predict and control the sintering quality of cutting tool. Due to the complex structure of sintering equipment, it is difficult to obtain high quality and sufficient data to train the sintering quality prediction model. In this paper, the real-time condition monitoring, prediction and control of carbide cutting tool during sintering process are studied. In this study, a digital-twin model of cemented carbide cutting tool sintering furnace was established. Based on this model, the change of heat distribution characteristics in sintering furnace during sintering process is precisely described. Firstly, the paper establishes the mapping architecture of cutting tool sintering digital-twin system. Based on this architecture, a digital-twin model of heat radiation in sintering furnace is established in this paper. Based on the temperature and pressure data in the sintering furnace, the radiation heat transfer in the furnace is analyzed in order to determine the temperature change of the cutting tool sintering position. In this paper, the relationship between the temperature change of cutting tool sintering position and cutting tool grain size is studied. Based on this relationship, a rolling data-driven digital-twin prediction model for cutting tool sintering has been constructed. In this paper, cutting tool sintering temperature control driven by digital-twin system is realized based on a fuzzy control model. The validity of the digital-twin system is verified by a series of comparative experiments. The test results show that the temperature error of the system control is less than ±1 °C. It effectively improves the qualified rate of cutting tool sintering.

An intelligent recommender system for tool selection in conventional machining

ABSTRACT Cutting tool manufacturers face a tough challenge in developing custom solutions for specific customer requirements. Several trials are required, encompassing the selection of materials, tool configuration parameters, manufacturing of tools and testing under target conditions to arrive at an acceptable solution. In this work, the authors present a recommender system that utilizes a hierarchical deep learning-based machine learning model, handcrafted using domain knowledge, to predict top N tool configurations for a given target requirement with a probability score. The authors also discuss methods for data augmentation to deal with limited data as well as a probabilistic approach to predict the top N tool configurations from the trained models. The proposed system is applied to a case of centerless cylindrical grinding wheel selection problem. The outcomes indicate an overall accuracy of 92.4% for single best-fit specification, with 100% within the top five recommendations for past designs. Some of the alternatives proposed by the model are observed to be potentially superior to what was chosen earlier by experts. Without the selection hierarchy, a deep learning model achieved a single best-fit accuracy of 83.5% and the probabilistic model achieved a top-five recommendation accuracy of 89.8%, highlighting the merit of the hierarchical approach.

Tool life and wear prediction of HSS and PVD material using ANFIS system

This paper proposes tool wear prediction of the cutting material using High Speed Steel (HSS) and Physical Vapor Deposition (PVD) coating using Adaptive Network-based fuzzy inference system (ANFIS) system. Even though machines have been studied and practiced for a long time, but quality and accuracy are still needed to improve at the factory level. Machinating data and cutting parameters are derived from the cutting tool manufacturing for recommendation and initial decision making. However, practical machining depends on the practitioners and specific cases of machining. Tool wear is a critical aspect for improvement of productivity. Unlike in the previous time, machinists were made decision by totally experiences whereas the modern technology provide usefully mathematical simulation. The advanced method is combining people’s experiences and computer system by heuristic rule based which is known as ANFIS system. Input membership functions are defined and fed into the MATLAB toolbox. The rules are captured by shop floor experts and created in the fuzzy inference system. It is found from the simulation that HSS tool effects extremely on the high cutting speed whereas the PVD is risky to occur the wear at the cutting speed and feed rate. It can conclude that the PVD can be used by the medium to high cutting speed whereas the HSS performs good at the low to medium cutting speed. However, the tool life prediction is limited to direct prediction, but it can be calculated by the Taylor tool life equation.

Strong Foundations Ensures Strong Bounce Back At Kyocera SGS

Carbide cutting tool manufacturer Kyocera SGS Precision Tools Europe continues to innovate and had a stellar year in 2022, and is looking forward to exhibiting at EMO 2023 in Hanover, Germany this September. Justin Burns visited the Wokingham-based company to hear more

Improving Process Efficiency

Team Inc (UK) achieves a five-fold increase in machine productivity with the help of reamers from cutting tool manufacturer Ceratizit

APPLICATION OF FRACTIONAL FACTORIAL DESIGN FOR ANALYSIS OF CUTTING ENERGY IN TURNING

Energy consumption in machining processes is a very important aspect that has been given increased importance in recent times. This article, therefore, proposes an approach for identification of the most important main and interaction effects of turning parameters regarding the cutting energy in dry longitudinal single-pass turning of low-alloyed and high-alloyed steels. Fractional factorial design was applied to arrange five parameters, namely, depth of cut, feed rate, cutting speed, rake angle and cutting edge angle at two levels. Based on the cutting tool manufacturer’s machining calculator and well-known analytical relationships, cutting energy was estimated for sixteen cutting regimes for both workpiece material groups. The analysis of obtained results involved the analysis of main and interaction effects, determination of statistically significant effects and development of cutting energy prediction models.

An appraisal of the cradle-to-gate energy demand and carbon footprint of high-speed steel cutting tools

The awareness of the environmental impact of the manufacturing sector has increased over the last few decades. This paper presents the results of an LCA-based approach used to evaluate the production of a threading tool (i.e., an M10 × 1.25 spiral point tap) made of high-speed steel. The cumulative energy demand and CO2-equivalent emissions have been quantified throughout the entire tool manufacturing process. Both the pre-manufacturing steps and the upstream/downstream flows of the used material have been accounted for, considering cradle-to-gate (plus end-of-life) system boundaries. The results show that the share of primary energy employed to produce the tool is mainly imputable to the manufacturing processes. Therefore, this analysis could contribute to fostering the development of structured assessment frameworks that would allow cutting tool manufacturers to identify the weak points of their production routes to be optimized.

Cast WC-Co alloy-based tool manufacturing using a polymeric mold prepared via digital light processing 3D printing

Tungsten carbide-Cobalt (WC-Co), also known as cemented carbide, is a widely used alloy to manufacture high-performance tools for mining, drilling, cutting, and machining applications. Due to the high melting point of WC, it is challenging to cast it to manufacture products. Therefore, in this study, we investigated a method for manufacturing cutting tools from WC-Co alloy using high-precision digital light processing-based three-dimensional (3D) printing technology. The high refractive index of WC renders it difficult to directly apply it to photocurable 3D printing. Therefore, a polymer mold was fabricated via 3D printing to obtain a WC-Co slurry cast. Rheological studies were performed to optimize the slurry composition. After slurry casting and drying, a green body was formed, which was sintered at 1400 °C to obtain a defect-free sample with a shape identical to that of the 3D model. The cast sample exhibited identical characteristics (microstructure, hardness, and fracture toughness) to those of conventional press-molded sample. The results of this study confirm that complex cutting tool manufacturing is possible without using expensive metal molds. The presented approach is expected to significantly reduce the cost and time incurred during the product development stage involving multiple designs.

The Combination of Taguchi and Proximity Indexed Value Methods for Multi-criteria Decision Making When Milling

Milling is a commonly used method in mechanical machining. This is considered to be the method for the highest productivity among cutting methods. Moreover, the quality of the machined surface is increasingly improved as well as the machining productivity is increasingly enhanced thanks to the development of machine tool and cutting tool manufacturing technology. Therefore, in each specific processing condition (about machine, tool and part material, and other conditions), specific studies are required to determine the value of technological parameters in order to improve productivity and machining accuracy. Only in this way can we take full advantage of the capabilities of modern equipment. The process parameters in the milling method in particular and in the machining and cutting methods in general can be easily adjusted by the machine operator as the parameters of the cutting parameters or the change of tool types. In this article, the combination of Taguchi and Proximity Indexed Value (PIV) methods is presented for multi-criteria decision making in milling. An experimental matrix was designed according to Taguchi method with five input parameters, including the insert materials (TiN, TiCN, and TiAlN), nose radius, cutting velocity, feed rate and depth of cut. The total number of experiments that were performed was twenty-seven. The workpiece used during the experiment was SCM440 steel. At each experiment, the surface roughness was measured and the Material Removal Rate (MRR) was calculated. The weights of these two parameters have been chosen by the decision maker on the basis of consultation with experts. The PIV method was applied to determine the experiment at which the minimum surface roughness and the maximum MRR were simultaneously guaranteed. In addition, the influence of input parameters on surface roughness was also found in this study.

New Opportunities

The arrival of new technology, in one case a Rollomatic at UK tool grinding firm Marlor and in another an enhancement to ANCA’s EDGe-related software, is, or will, deliver capability to that promises to enhance their users’ cutting tool manufacturing capabilities

METHOD OF PROCESSING EMPIRICAL DATA IN THE STUDY OF THE INFLUENCE OF TECHNOLOGICAL PARAMETERS ON THE SUPPLY OF TOOLS FOR THE FINAL PROCESSING OF STEEL AND CAST IRON WORKPIECES

When implementing a multi-variant design of the machining process, one of the important tasks is to select rational technological parameters at the final transitions of the shaping process that ensure the specified surface quality on the finished part made of the appropriate material. When modeling most of the design procedures at all stages of machining, there are problems associated with algorithmization of the solution method, adequate choice of the regression equation and the range of acceptable solutions at the specified processing stages. In this paper, as an algorithm for solving the problem, we propose the use of a wellknown method of rational planning of the experiment, which allows us to obtain a mathematical model of the multi-factor process under study. In the process of implementing this algorithm, based on a priori information, the object of research was selected, its factors and the main levels of change of these factors were established. Next, a two-factor experiment plan was implemented using a numeric array from the wellknown CoroKey catalog by SANDVIK Coromant. At the next step, the experimental data was processed using the existing method and on the basis of this information, private graphical dependencies of the studied parameter on the levels of factors were constructed. At the final stage, using the types of graphical dependencies, the regression equation of the investigated value of the cutting tool feed from two independent factors at three levels of each of them was formulated. To implement this algorithm, the least squares method was used, and the system of normal equations obtained on its basis. The proposed algorithm for obtaining the regression equation for solving problems in the field of machining production can be effectively used in computer-aided design systems for selecting technological parameters in the modes of processing parts with a blade tool, using numerical data from technological directories and catalogs of cutting tool manufacturers.

Empirical data processing technique for studying the influence of technological parameters on tool feed during the final processing of steel and cast-iron workpieces

When implementing a multi-variant design of the machining process, one of the important tasks is to select rational technological parameters at the final transitions of the forming process, ensuring the specified quality of surfaces on the finished part made of the appropriate material. When modeling most design procedures at all stages of machining, there are problems associated with algorithmization of the solution method, adequate selection of the regression equation and the range of acceptable solutions at the specified processing stages. In this paper, as an algorithm for solving the problem, we propose the use of a well-known method of rational planning of the experiment, which allows us to obtain a mathematical model of the multi-factor process under study. In the process of implementing this algorithm, based on a priori information, the research object was selected, its factors and the main levels of changes in these factors were determined. The proposed algorithm for obtaining the regression equation for solving problems in the field of machining production can be effectively used in computer-aided design systems for selecting technological parameters in the modes of processing parts with a blade tool, using numerical data from technological reference books and catalogs of cutting tool manufacturers.

Experimental research of picosecond laser based edge preparation of cutting tools

In this study, using ultrafast lasers of 10 ps pulse duration as a precise and efficient method for cutting edge preparation is researched. Cutting edge preparation is an important step within cutting tool manufacturing, while unprepared sharp cutting edges show low stability, which leads to tool failure by high mechanical and thermal loads during the turning processes [C. F. Wyen, W. Knapp, and K. Wegener, Int. J. Adv. Manuf. Technol. 59, 899–914 (2012)]. The rounding of the edges requires laser manufacturing with high precision and minimal heat accumulation; thus, ultrafast lasers have been used in other investigations [M. Stolze, T. Herrmann, and J. L'huillier, Proceedings of ICALEO, Orlando, USA, ICALEO, Orlando, FL, October 23–27 (J. Laser Applications, Orlando, 2011)]. In the authors’ study, the effects of edge roundness on the cutting tool material WC-Co alloy were experimentally investigated. Samples with three different grain sizes and percentages of cobalt were used in the authors’ study. The experiments were carried out on the free surfaces of cutting tools under varying laser parameters including laser wavelength, fluence, and spatial pulse overlap (PO) in air or by using process gases (helium and oxygen). The impact of all these different laser parameters on the various material sorts was investigated. As a result, no reduction of the hardness of the original material was observed that could have a negative effect on the cutting ability of laser rounded cutting tools. By analyzing the surface quality of the ablated areas processed with different laser parameters mentioned above, a surface roughness below Ra = 0,15 μm was generated by using optimal fluence at both wavelengths of 1064 nm (IR) and 532 nm (VIS) and using a 70% spatial PO. Thus, a well-defined cutting edge with radii of 20–40 μm could be prepared.

Expert System Based on Integrated Fuzzy AHP for Automatic Cutting Tool Selection

Cutting tool selection plays an important role in achieving reliable quality and high productivity work, and for controlling the total cost of manufacturing. However, it is complicated for process planners to choose the optimal cutting tool when faced with the choice of multiple cutting tools, multiple conflict criteria, and uncertain information. This paper presents an effective method for automatically selecting a cutting tool based on the machining feature characteristics. The optimal cutting tool type is first selected using a proposed multicriteria decision-making method with integrated fuzzy analytical hierarchy process (AHP). The inputs of this process are the feature dimensions, workpiece stability, feature quality, specific machining type, and tool access direction, which determine the cutting tool type priority after evaluating many criteria, such as the material removal capacity, tool cost, power requirement, and flexibility. Expert judgments on the criteria or attributes are collected to determine their weights. The cutting tool types are ranked in ascending order by priority. Then, the rule-based method is applied to determine other specific characteristics of the cutting tool. Cutting tool data are collected from world-leading cutting tool manufacturer, Sandvik, among others. An expert system is established, and an example is given to describe the method and its effectiveness.

Tool wear rate of the PCBN, mixed ceramic, and coated cemented carbide in the hard turning of the AISI 52100 steel

The hard turning process is generally performed by PCBN or mixed ceramics tools, which have the mechanical properties that withstand the tribological conditions of the process imposed by the hardened machined material. Coated cemented carbides are also an option for hard machining processes, although relying on the coating deterioration. This paper aims to evaluate the tool wear rate in function of the cutting speed in the hard turning of the steel AISI 52100 with a hardness of 50 HRC for three different types of cutting tool materials: coated cemented carbide, mixed ceramic, and PCBN. The methodology applied to assess the tool wear is based on three-dimensional parameters (volumetric) obtained from a focus variation microscope (FVM). The tool wear rate (WRRM) is calculated based on ordinary least squares (OLS) adopting five values of WRM in five machining time intervals. The face turning experiments were performed at four cutting speeds: vc = 120, 150, 187.5, and 234 m/min. At vc = 120 m/min, the PCBN presented the lowest tool wear rate (182 μm3/s); at vc = 150 m/min, the coated cemented carbide (tool wear rate on the coating) had the best performance (417 μm3/s). The mixed ceramic tool presented a better performance at the higher cutting speeds of vc = 187.5 and 234 m/min, 1206 and 1878 μm3/s, respectively. The methodology applied was reliable to understand and discuss the performance of the machining process through the tool wear rate (WRRM), which is based on the volume of removed material from the tool (WRM). The three-dimensional tool wear parameters can also be applied to machining process optimization, cutting tool wear model creation, benchmarking, and development of new cutting tool materials and grades. Furthermore, the methodology can be considered more agile and precise when compared to the current industrial methodology of tool performance evaluation. Thus, this innovative methodology promotes important information for cutting tool manufacturers and for its customers such as automotive and aeronautic industry.

Ingrained Innovation

USA-headquartered solid carbide round shank cutting tool manufacturer MA Ford is celebrating 100 years, with its UK subsidiary having notched up just over 20. Andrew Allcock visited the UK operation’s new location in Derby and heard about the company’s strengths, new products and latest initiatives

Modeling the machined surface quality of an aluminum alloy using the active experiment type

The surface roughness obtained by the cutting processes has always been a subject of great interest when it is intended to improve the quality of the final product requested by the customer. The objective of this scientific paper involves a comparative study on the tracking of the surface roughness measured both longitudinally and transversely in the direction of the cutting feed movement, following the end-milling process of an aluminum alloy used in the aerospace industry worldwide. Practical experiments have conducted in a prestigious company in the aerospace industry of Romania. Regarding the cutting regime, in terms of milling, a cutting speed was adopted to maintain its constant value at 570 m/min, and the cutting depth and feed per tooth are within the range recommended by the cutting tool manufacturer in aluminum machining. The measuring and control devices used to obtain the experimental data were chosen after careful analysis, such as the surface tester and the electronic microscope. With the help of the obtained data, it was possible to interpret the surface roughness results measured longitudinally in the direction of the feed motion, compared to the roughness measured transversally in the same direction of the cutting tool. Different variations of the surface roughness have highlighted with the help of profiles and microscopic analyses of the machined surfaces. This study is in the category of scientific papers with an extremely high level of applied scientific research using experimental statistical modeling of active type.

Reliability-Based Design Optimization of Surface-to-Surface Contact for Cutting Tool Interface Designs

Abstract In recent years, cutting tool manufacturers are moving toward improving the robustness of the positioning of an insert in the tool body interface. Increasing the robustness of the interface involves designs with both chamfered and serrated surfaces. These designs have a tendency to overdetermine the positioning and cause instabilities in the interface. Cutting forces generated from the machining process will also plastically deform the interface, consequently, altering the positioning of the insert. Current methodologies within positioning and variation simulation use point-based contacts and assume linear material behavior. In this paper, a first-order reliability-based design optimization framework that allows robust positioning of surface-to-surface-based contacts is presented. Results show that the contact variation over the interface can be limited to predefined contact zones, consequently allowing successful positioning of inserts in early design phases of cutting tool designs.