Machine Tool Manufacturers Research Articles

Effect of coaxial nozzle wear on catchment efficiency in direct energy deposition built components

Laser based Direct Energy Deposition (DED) systems using metallic powder feedstock are recognized as a promising manufacturing method for their ability to shorten production cycles and create complex part geometries. Components are built by generating a melt pool with a high-power laser beam while material is coaxially injected and left to solidify. An impediment to large scale use of DED lies in poor powder catchment efficiency, the condition in which a portion of injected powder escapes the melt pool resulting in a ratio of decreased printed material mass to mass of supplied feedstock. The wear state of a coaxial nozzle on a DED system within a hybrid manufacturing machine tool has been observed to decrease catchment efficiency over time. This study investigates this effect by adapting flow visualization techniques to an in-situ process monitoring format, the implementation of a Computational Fluid Dynamics (CFD) simulation, and deposition testing. Nozzle geometric defects due to wear are identified and categorized, and the impact of nozzle tip wear, resulting in axial tip reduction, on powder catchment efficiency is proven by multiple calculation methods. A linear correlation between catchment efficiency and powder stream diameter is identified, causing a 15–20% loss in efficiency sustained over incremental nozzle tip reduction up to − 1 mm. These results provide a foundation for further study of wear effects and Zero defect manufacturing solutions for powder fed DED systems.

Cutting Forces in the Milling of Difficult-to-Machine Material used in the Aero Space Industry Using a Monolithic Ceramic Milling Cutter

The constantly developing aerospace industry places demands on increasing productivity and produc-tion efficiency. At present, new construction materials are being produced that have better physical and mechanical properties than conventional materials. In addition to new materials, new cutting materials and new machining technologies are being developed. The combination of suitable machin-ing technology, material and tool will achieve excellent product surface quality, long tool life and thus production efficiency. Due to its mechanical and physical properties, technical ceramics can be used in the machining of difficult-to-machine materials, in which there is mechanical stress on blows, impacts, abrasions and other damage. Thanks to these properties, ceramics as a material is very suit-able for the production of machine tools. The presented article deals with the applicability of ceramic milling cutters in high-speed machining of nickel alloy, which is used mainly in the aerospace indus-try. The evaluation of the experiment took place by means of DoE - analysis of cutting forces, the result of which is the creation of the dependence of cutting forces on cutting conditions. Based on the data obtained, it is possible to continue to further intensify the cutting conditions in the area of high-speed machining.

The Damping Effect of Particle-Filled Hollow Sphere Structures and their Application in Machine Tool Components

High speed feed axes are a key for increasing the productivity of machine tools. It requires high acceleration and causes jerk, which excites the machine structure and negatively affects the process quality. One approach to reduce those machine vibrations are passive dampers such as particle-filled hollow spheres (PHS). PHSs dissipate vibration energy through relative motion and friction between particles among themselves and the sphere. Compounds of PHS as core of sandwich materials allow structure-integrated damping of machine tool components and for maintaining a high specific stiffness at the same time. The complex interactions within each sphere lead to nonlinear damping. As of today, precise predictions on how PHSs influence the overall machine behavior are not possible. This prognosis is essential for establishing the material in any machine structure. The paper investigates the damping properties of PHSs in a spindle box of a machine tool. The experimental and numeric analysis demonstrates the nonlinear behavior and shows the reaction of the spindle box under external excitation. The result shows that the damping of the spindle box with PHSs is frequency and amplitude dependent. The damping of PHSs is domain with increased parts of them deformed during vibration.

Fuzzy decision-making model for process quality improvement of machine tool industry chain

Industry 4.0 has fostered innovation in industries around the world. Manufacturing industries in particular are advancing towards smart manufacturing by integrating and applying relevant technologies. The output value of machine tools in Taiwan is among the top of the world and the central region is a key area for this industry chain, which supplies manufacturers in Taiwan and their international downstream customers. To support innovation in this industry, the current study used the Six Sigma quality indices for smaller-the-better, larger-the-better, and nominal-the-best quality characteristics to construct a fuzzy decision-making model. Based on this model, we propose a process quality fuzzy analysis chart (PQFAC) for process quality improvement. Our use of fuzzy decision values to replace lower confidence limits decreases the probability of misjudgment made by sampling errors. The proposed fuzzy model also offers a more accurate assessment of process improvement requirements. We provide a real-world example to demonstrate the applicability of the proposed approach. Machine tool manufacturers can apply the platform and proposed model to evaluate their process capabilities for the vital parts suppliers and downstream customers, determine optimal machine parameter settings for processes with inadequate accuracy or precision, establish more suitable machine repair and maintenance systems, and combine the improvement experiences of customers to create an improvement knowledge base. This will enhance product value and industry competitiveness for the entire machine tool industry chain.

Experimental Method of Machining Gears with an Involute Profile Using CNC Lathe with Driven Tools.

There are many ways of machining gears; the world’s manufacturers of machine tools have patented many methods that allow for the production of gears in an accurate and efficient way. In general, the patented methods require the use of kinematically complex and expensive CNC machine tools. These tools, moreover, the production of the technology itself, including the machining code, require the use of dedicated software. Therefore, it seems justified to strive for the application of kinematically simple and relatively cheap machines in the machining processes so as to increase the universality and availability of new machining methods. This paper presents a method of machining a spur gear with straight teeth with an involute profile using a basic CNC lathe DMG MORI CLX350V4 equipped with driven tools. On the basis of the presented mathematical model, an algorithm was developed to generate a code that controls the machining of cylindrical gears with an involute profile of straight teeth, with the possibility of modifying the transition profile and the tooth root. The machining was experimental, and the gear was made of aluminium AlSi1MgMn using a solid carbide cylindrical cutter. In conclusion, the presented method was found to be very competitive with commercial methods and is able to provide very high quality gears. The accuracy of the machined profile form deviation in the entire processing did not exceed an average value of 10 μm; while assessing the tooth line, the basis average error was 5 μm. Finally, the gear was assessed as manufactured in accuracy class 6. This machining method guarantees very competitive machining cycle times, and thanks to the use of an uncomplicated CNC lathe and universal tools, it provides great flexibility, at the same time giving the possibility of machining gears with arbitrary profiles.

Implementation of Digital Twin-based Virtual Commissioning in Machine Tool Manufacturing

Virtual commissioning is not a new concept; However, it is all the rage with the introduction of Industry 4.0, in the field of product lifecycle management, computer-aided design (CAD), computer-aided manufacturing (CAM), and within the industrial automation programming frameworks. Although, this is a very active area of research and innovation, these technologies have little implementation in the machine tool industry [11]. There is still no integrated simulation environment for virtual commissioning in the market. In this context, digitalisation is a key driver. The aim of this paper is to describe the practice of virtual commissioning in the machine tool manufacturing industry by identifying available solutions in the market and addressing the challenges faced within the machine tool sector. As a result, a digital twin based virtual commissioning solution has been developed at Danobatgroup, the leading machine tool builder in Spain, which is a step forward towards the digitalisation of machine tool manufacturing.

Study on wear properties of Aluminium alloy for different mass of SiC particles

Owing to its excellent dimensional consistency, low weight, max strength ratio, cheap cost, and specific strength, aluminium 7075 has a wide range of applications in aircraft fittings, gears, worm wheels, shafts, missiles, and regulating valves. Considering the use aluminium alloy (Al 7075) in the aerospace and defence sectors, its wear qualities must be enhanced further to extend the life of the components used in these industries. Considering its wear resistance capabilities, silicon carbide (SiC) is commonly utilised in the production of wear-resistant blades, saws, surface coatings, and machine tools. The wear characteristics of Al 7075 alloy have been investigated in this study by fortifying it with varied weight percentages (1%, 2%, and 4%) of silicon carbide (SiC) and producing it using the stir casting technique. The experiment was carried out with a Taguchi L27 orthogonal array. A pin-on-disc wear measuring device is used to assess the dry sliding wear properties. SiC concentration, velocity, loading, and sliding length are the process parameters, and the outputs are the friction coefficient (CoF) and the rate of specific wear. The Signal-to-Noise (S/N) ratio was calculated with the help of Taguchi’s analysis to discover the optimum effective combination for minimising friction coefficient and rate of specific wear. According to the results, 4% SiC reinforcement results in a decreased friction coefficient and rate of specific wear under different dynamic conditions. A Scanning Electron Images (SEM) investigation was performed to detect the wear pattern, and it was discovered that the Al7075 strengthened with 4% SiC with a steady input variable shows the least wear. Investigation shows that increasing the weight percentage of SiC enhances the wear resistance of the Al 7075 alloy.

Intelligent Machinery Product Service Blueprint Development and Verification: An Empirical Study of Machine Tool Industry

Integrating of products and services is regarded as an effective strategy to meet the rapidly changing needs of customers and to create more value for customers. The academic community is also paying more and more attention to the study of product and service integration. In order to verify whether the development of the product service blueprint is suitable for the machine tool industry, this study is divided into four sub-studies, namely service attributes analysis, service requirement analysis, service innovation modeling, and service establishment and validation. Through qualitative and quantitative study and design, product service blueprints of universal standard machines, customized special machines, and composite machining machines for metal deposition are constructed in this study. At the same time, the three dimensions of smart manufacturing of machine tools are constructed in this study, namely virtual factory design and automation system integration, massive data and cloud computing, and smart systems and smart devices. Furthermore, the reliability, validity and importance of the development of new services in this study have been verified.

Reduction of planning efforts for decision making under uncertainty in global production network design

Continuous design of production networks is an essential element to overcome historically grown, inefficient production networks, as they are common for manufacturing companies. In order to enable continuous network design, fast and low-effort methods for investment and allocation decision making are required without losing decision quality. This paper introduces a decision making approach that reduces planning efforts by systematically focusing on main influencing factors and reducing their uncertainty. The approach was applied to a real allocation decision of a machine tool manufacturer.

A New Evaluation Method for Product Service System Scheme Based on Analytic Network Process and Niche Theory

In reservation to enhance the enforceability of the product service system scheme and avoid the waste of time and resources caused by the improper design of the scheme, it is necessary to evaluate the scheme effectively before the implementation of the product service system scheme. Therefore, this study proposes a product service system scheme evaluation method based on the analytic network process and niche theory and evaluates the product service system scheme with customer value as the evaluation index. First, an analytic network process is used to calculate the relative importance of various customer value types and stages of the customer activity cycle. Second, niche theory is used to calculate the relative advantages of different product service system schemes in delivering all types of customer value. Then, based on customer value perception, the customer’s evaluation of the value delivered by different product service system schemes is obtained, and the schemes are ranked according to the amount of value delivered. Finally, the proposed method is verified by evaluating the CNC machine tool product service system scheme as an example and comparing it with other evaluation methods. The results demonstrate that the proposed method is more accurate and effective.

Развитие технологии низкочастотной вибрационной обработки сварных металлических конструкций судо- и машиностроения

Residual welding strains and stresses affect strength, lifetime and reliability of shipbuilding hull structures and a wide spectrum of welded metal structures applied in manufacturing of machine tools, machines and railroad cars, as well as in building industry. Welding strains also increase man-hours required for manufacturing. A traditional way of residual stress mitigation in shipbuilding and other industries is thermal processing which is known to be a costly and labour-intensive operation. An alternative process is low-frequency vibration processing that is relatively easy and highly cost-efficient. Low-frequency vibration processing basically means that metal structures are subjected to alternating-sign loads at resonant or near-resonant frequencies by means of an electromechanical vibration exciter. Size stabilization in this kind of processing is achieved through mitigation and re-distribution of the first-kind residual stresses, i.e. those equilibrating over the entire product or its large elements, so that material structure comes to a more stable equilibrium. This paper discusses SSTC experience in the induction of low-frequency vibration processing of welded metal structures to the practice of shipyards and machine manufacturing enterprises, as well as describes state-of-the-art equipment for its performance and the equipment used to assess and check its results.

Геоэкологические аспекты углепородной добычи в Донбассе

Donets Coal Basin (the Donbass Coalfield) with its multi-million population is a concentration of all kinds of industries. These include iron and steel industry, machine-tool manufacture, mining production, byproduct coke industry, and also agriculture. Above all others it is coal-mining industry which coming of age and subsequent development is invariably connected with the evolutionary existence of this region. Coal mining, like any production, has its own negative aspects that adversely affect ecology of the region. The article overviews a number of essential geoecological aspects related to deep coal mining and shale gas production in Donets Basin which, taken as a whole and in isolation from one another, deform ground surface and surface buildings, flood the near-surface area, affect underground water inflow, dewater surface watercourses, increase background radiation, etc. The vast majority of harmful geoecological impacts are accounted for by legal operating coal mines and illegal ones – the so-called kopanki. Primarily just mines deform and kopanki sometimes distort surface landscape, creating at the same time a hazard to the safety of surface buildings. Faulty operation and the same kind abandonment of such industries lead to an increase in inflow of aggressive groundwater, pollution of safe drinking water sources, drying of surface watercourses that only worsen the environmental geology of the region. A catastrophe waiting to happen in the region is the so-called old mine workings abandoned at coal seam outcrops since early days through present of coal industry. They are hazardous due to their sinkhole collapse and deformation unpredictability for ground surface areas that fall within their affected zone. The more so because at most mining plans of old mines have not been preserved. Just as either there are no plans or they are completely lack for operating illegally private shallow mines, including kopanki. The planned shale gas production in Donets Coal Basin to be commenced since that year will significantly put a strain on environmental geology of the region with far-reaching negative consequences.

A two-stage reliability allocation method for remanufactured machine tools integrating neural networks and remanufacturing coefficient

Reliability allocation is an important task that needs to be done in the design phase of machine tool remanufacturing to ensure that remanufactured machine tools meet the reliability target. However, unlike new machine tool products, remanufactured machine tools have high uncertainty and small samples, and traditional reliability methods are not suitable for remanufactured machine tools. This paper aims to propose an improved reliability allocation method for remanufactured machine tools integrating neural networks and remanufacturing coefficient. With the fault tree analysis (FTA) model constructed, the fault of remanufactured machine tools can be divided into three levels: system-level, subsystem-level, and part-level. The three-layer feedforward artificial neural network is adopted to allocate system reliability to subsystem-level. When reliability is allocated from subsystem-level to part-level, the remanufacturing comprehensive evaluation system and a remanufacturing coefficient that takes into account the characteristics of remanufactured components are introduced. Finally, the proposed method is illustrated in a case of reliability allocation for remanufactured NC gear hobbing machines. Moreover, the results show that the reliability target can be achieved and the growth of reliability can be guaranteed through the proposed method.

Business Efficiency Evaluation of Machine Tool Manufacturers by Data Envelopment Analysis (DEA): A Case Study of Taiwanese Listed Machine Tool Companies

Data envelopment analysis (DEA) is widely used to measure the business efficiency of many industries, among which the Taiwanese machine tool industry is well-known for its complete supply-chain system. Relying on DEA and Malmquist Productivity Index to analyze the business efficiency of Taiwanese listed machine tool manufacturers from 2018 to 2019, this study compared the changes in their business efficiencies and productivities. According to the five change indicators of Malmquist, only the technical efficiency, pure technical efficiency, and scale efficiency of the overall industry posted some growth during the research period, showing that the whole industry is actively improving its technical efficiency and striving to achieve the scale efficiency. However, technical change and total factor productivity declined slightly, indicating that the industry still makes more technical progress. Thus, companies should adjust their inputs and outputs to improve the production boundary for technical progress. The purposes of this study are to identify the success factors of the excellent performance of manufacturers and the benchmarking indicators of the decision-making unit on the efficient frontier results to provide some references for formulating future business strategies and direction.

Business Efficiency Evaluation of Machine Tool Manufacturers by Data Envelopment Analysis (DEA): A Case Study of Taiwanese Listed Machine Tool Companies

Data envelopment analysis (DEA) is widely used to measure the business efficiency of many industries, among which the Taiwanese machine tool industry is well-known for its complete supply-chain system. Relying on DEA and Malmquist Productivity Index to analyze the business efficiency of Taiwanese listed machine tool manufacturers from 2018 to 2019, this study compared the changes in their business efficiencies and productivities. According to the five change indicators of Malmquist, only the technical efficiency, pure technical efficiency, and scale efficiency of the overall industry posted some growth during the research period, showing that the whole industry is actively improving its technical efficiency and striving to achieve the scale efficiency. However, technical change and total factor productivity declined slightly, indicating that the industry still makes more technical progress. Thus, companies should adjust their inputs and outputs to improve the production boundary for technical progress. The purposes of this study are to identify the success factors of the excellent performance of manufacturers and the benchmarking indicators of the decision-making unit on the efficient frontier results to provide some references for formulating future business strategies and direction.

VIRTUAL COMMISSIONING IN MACHINE TOOL MANUFACTURING: A SURVEY FROM INDUSTRY

Virtual commissioning has acquired a major interest with the introduction of Industry 4.0. It is demonstrated that virtual commissioning can significantly reduce the commissioning time, error rate and costs. However, industry is still experiencing difficulties with the integration of these new technologies. This paper is one of the first empirical surveys conducted in the industry that aims at understanding the challenges and current practices with respect to virtual commissioning, with special focus on the machine tool manufacturing sector. The survey contextualizes the practice of virtual commissioning and the digital twin in industry, and benchmarks the results with academia, in which main gaps are identified. Keywords: empirical survey, virtual commissioning, digital twin, machine tool manufacturing, testing

A novel identification technique of machine tool support stiffness under the variance of structural weight

The preload-dependent stiffness of machine tool support was investigated in this study. A novel identification method of support stiffness has been proposed through the experimental modal analysis and finite element method. The support stiffness was identified with different machine weight during the assembling process of a machining center. Specifically, the structure weight increase of a machine tool in the assembly process causes its center of gravity to shift. Accordingly, the variance of support reaction affects the support stiffness. To explore the variance of support stiffness, the researchers of this study collaborated with a machine tool manufacturer. Impact testing was performed on each assembly stage. Additionally, finite element analysis was used to establish equations between the reaction force versus stiffness of supports under the structural weight variance. The obtained equations were used to predict the natural frequency and vibration mode of structures in various assembly stages. The maximum error between the experimental and simulated natural frequencies was 7.1%, and the minimum modal assurance criterion was 0.77. Finally, a modal analysis model that updates support stiffness automatically, which could be adopted by machine builders to develop new machine tool, is proposed.

Research on Big Data Acquisition Bus Technology of NC Machine Tool

Big data technology has strongly promoted the development of social productive forces, and commercial applications are continuously expanding in all walks of life. It also uses the power of Internet technology to provide strong technical support for the development of the entire industry. In terms of the production of CNC machine tools, due to the use of big data technology, CNC machine tools have been rapidly produced on a large scale, which has played an important role in the upgrading of the entire CNC machine tools and the improvement of quality and efficiency. This article takes the technology of big data acquisition bus for CNC machine tools as the topic, through researching and discussing its concept, meaning and related strategies, in order to effectively improve the production scale and reference.Chinese Library Classification number : TP23 Document Identification code : A

The Thermal Error Estimation of the Machine Tool Spindle Based on Machine Learning

Thermal error is one of the main sources of machining error of machine tools. Being a key component of the machine tool, the spindle will generate a lot of heat in the machining process and thereby result in a thermal error of itself. Real-time measurement of thermal error will interrupt the machining process. Therefore, this paper presents a machine learning model to estimate the thermal error of the spindle from its feature temperature points. The authors adopt random forests and Gaussian process regression to model the thermal error of the spindle and Pearson correlation coefficients to select the feature temperature points. The result shows that random forests collocating with Pearson correlation coefficients is an efficient and accurate method for the thermal error modeling of the spindle. Its accuracy reaches to 90.49% based on only four feature temperature points—two points at the bearings and two points at the inner housing—and the spindle speed. If the accuracy requirement is not very onerous, one can select just the temperature points of the bearings, because the installation of temperature sensors at these positions is acceptable for the spindle or machine tool manufacture, while the other positions may interfere with the cooling pipeline of the spindle.

Surface Qualification Toolpath Optimization for Hybrid Manufacturing

Hybrid manufacturing machine tools have great potential to revolutionize manufacturing by combining both additive manufacturing (AM) and subtractive manufacturing (SM) processes on the same machine tool. A prominent issue that can occur when going from AM to SM is that the SM process toolpath does not account for geometric discrepancies caused by the previous AM step, which leads to increased production times and tool wear, particularly when wire-based directed energy deposition (DED) is used as the AM process. This work discusses a methodology for approximating a part’s surface topology using on-machine contact probing and formulating an optimized SM toolpath using the surface topology approximation. Three different geometric surface approximations were used: triangular, trapezoidal, and a hybrid of both. SM toolpaths were created using each geometric approximation and assessed according to three objectives: reducing total machining time, reducing surface roughness, and reducing cutting force. Different prioritization scenarios of the optimization goals were also investigated. The optimal surface approximation that yielded the most improvement in the optimization was determined to be the hybrid surface topology approximation. Furthermore, it was shown that when the machining time or cutting force optimization goals were prioritized, there was little improvement in the other optimization goals.