- Original Article
- Open Access
Smart Cutting Tools and Smart Machining: Development Approaches, and Their Implementation and Application Perspectives
© The Author(s) 2017
- Received: 19 December 2016
- Accepted: 24 July 2017
- Published: 11 August 2017
Smart machining has tremendous potential and is becoming one of new generation high value precision manufacturing technologies in line with the advance of Industry 4.0 concepts. This paper presents some innovative design concepts and, in particular, the development of four types of smart cutting tools, including a force-based smart cutting tool, a temperature-based internally-cooled cutting tool, a fast tool servo (FTS) and smart collets for ultraprecision and micro manufacturing purposes. Implementation and application perspectives of these smart cutting tools are explored and discussed particularly for smart machining against a number of industrial application requirements. They are contamination-free machining, machining of tool-wear-prone Si-based infra-red devices and medical applications, high speed micro milling and micro drilling, etc. Furthermore, implementation techniques are presented focusing on: (a) plug-and-produce design principle and the associated smart control algorithms, (b) piezoelectric film and surface acoustic wave transducers to measure cutting forces in process, (c) critical cutting temperature control in real-time machining, (d) in-process calibration through machining trials, (e) FE-based design and analysis of smart cutting tools, and (f) application exemplars on adaptive smart machining.
- Smart cutting tool
- Smart machining
- Fast tool servo (FTS)
- Precision machining
- Micro manufacturing
- Smart tooling
Smart tooling and smart machining have tremendous potential and are drawing attention as one of next generation precision machining technologies particularly in the Industry 4.0 context [1–5]. In modern advanced manufacturing, it is becoming an essential trend for machining components with an ever increasing dimensional/form accuracy and finer surface roughness, even surface functionality requirement. In high precision machining, however, to position the cutting tool with such high accuracy and repeatability is the key and this is normally undertaken in a “passive” manner, i.e., the tool’s position relying on the slideways’ positioning accuracy but without measuring the tool cutting behaviour and process conditions. Furthermore, for many high value precision machining processes, it is important to use smart cutting tools to carry out the processes in a ‘proactive’ manner, in order to cope with machining dynamics, process variations and complexity. For instance, ultra-precision and micro machining, with the surface roughness normally at the nanometric scale and features/patterns at the micrometer level, is increasingly and continuously demanded particularly for high precision components and products with improved functionality and performance. The smart precision and micro manufacturing in a ‘proactive’ manner will be the way forward .
Aiming at high quality surfaces and dimensional/form accuracy, some monitoring methods have been proposed to monitor cutting forces with high precision and the process conditions. The variations of the cutting forces are most likely related to the tool wear or other process conditions and therefore will have direct influences on the machining outcomes [7–9]. Tool wear or tool breakage can also increase the cutting forces and vibrations in the machining system, which will result in poor surface roughness, loss of the form and dimensional accuracy, and even chatter marks on machined surfaces . In order to avoid such manufacturing defects or tool damages, some devices are designed and developed to measure the cutting forces and cutting dynamics. For instance, dynamometers are developed by researchers and industrial companies to measure cutting forces and the process dynamics in high precision and wide bandwidth. Currently, however, dynamometers have some limitations in their industrial application, such as their costs and reliability in stringent production environment. Furthermore, dynamometers are not applicable for layout-constrained machines and tooling setup, due to their size and weight. The dynamometer could also interfere with the cutting process and performance because of the tooling stiffness reduction in the machining system .
Some high value components require to be machined in a contamination-free environment, which means coolant cannot be applied during the machining. However, dry cutting condition would lead to tool wear and high cutting temperature, and poor surface quality would thus occur and tool life be shortened. Some materials, such as aluminum and magnesium alloys, are not recommended for applying direct dry-cutting, since the cutting tool is prone to suffering excessive built-up edge (BUE). So for high precision and micro machining, there is a need for new sensor technologies to be applied to further exploit and understand the cutting mechanics and machining process .
Based on the underlying principle and application requirements above, four types of smart tools are developed, including a cutting force based smart tool, a cutting temperature sensing oriented internally cooled cutting tool a fast tool servo (FTS), and smart collets for ultraprecision and micro machining purposes. This paper presents the design concept, development processes, application principles for the above smart tools, for high precision and micro machining in particular. The paper also explores and discusses the implementation and application perspectives of those smart tools against the smart machining requirements from a number of industrial applications, such as micromachining maintained with constant cutting force, extra-high speed micro drilling, and contamination-free machining of medical device or explosive materials [12, 13].
Minimizing the tool paths and machining time;
Improving the component surface finish;
Maximizing the cutting tool life and cutting performance;
Machining complex geometrized components with improved precision and efficiency, such as thin-wall structures, hollow cylinders or slender shafts;
Process optimization in light of autonomous sensing;
Self-learning and performance improvement in the process;
Sensing of the cutting process dynamically, covering cutting forces, chip formation, and interactions at the cutting zone.
3.1 Smart Cutting Tool Using Piezoelectric Films
3.1.1 Design Configuration
The metal shim as output electrode of the piezoelectric sensor;
Piezoelectric film (3 mm×3 mm×0.26 mm), to sensor the orthogonal cutting force;
The integral sensing unit is placed 6 mm from the cutting tip, between the cutting tool and spacer;
The wire and a part of the metal shim are exposed from the cutting insert surface, but there is a safe distance from the cutting insert tool tip.
3.1.2 Cross-talk Analysis
Cross-talk of the smart tool 1
Vertical impact hammer
Horizontal impact hammer
3.1.3 Cutting Force Measurement Using the Smart Cutting Tools
3.2 Smart Cutting Tool Development Using Surface Acoustic Wave (SAW) Sensors
3.2.1 Smart Tool Development Using SAW-Based Force Sensor and Its FEA Simulation
It is able to undertake wireless data transmission;
It is possibly powerless or energized externally;
Working in high frequency response;
It likely leads to plug-and-produce - smart integration and connectivity;
Therefore, SAW sensor technology is applicable to monitor the tool wear and machining processes through the in-process cutting force measurement, which is increasingly beneficial to smart machining and high value manufacturing automation in the context of Industry 4.0.
Geometry of the SAW sensor substrate and IDT
Periodicity of electrode
Width of electrode
Al electrode thickness
3.2.2 Experimental Implementation
For evaluating and validating the SAW-based smart cutting tool for cutting force measurement in real machining environment, calibration is carried out so as to establish the scientific understanding of the intrinsic relationship between the SAW strain and the cutting force.
3.2.3 Preliminary Machining Trials
The increase in cutting temperature normally causes the premature cutting tool failure or excessive tool wear, while most of the wear processes occurs at the major flank face and rake face of the cutting tool. There are four main wear mechanisms in association with tool failure, including: oxidation, abrasion, adhesion and diffusion. All of these wears are related to the temperature sensitivity even under normal cutting conditions [20, 21]. At low cutting temperature (due to soft cutting or high cooling efficiency), adhesive and abrasive wears are dominant. While the cutting temperature is higher than a certain threshold, thermal induced wear, such as oxidation and diffusion, are activated and dominate total wear. The utilization of cutting fluid, traditionally applied to remove heat generated from the cutting process, can additionally cause environmental pollution, health hazards, surface contamination and an increased cost of production . The above issues can be avoided by using an internally-cooled smart cutting tool.
Adaptive smart machining of high value components;
Contamination-free machining such as medical devices and explosive materials;
Machining of difficult-to-machine materials including titanium, magnesium and Inconel alloys, etc.
Based on the design criterion discussed above, the FTS developed can achieve a natural frequency of 1866.5 Hz (FEA simulation), as shown in Figure 15(c). In the experimental testing and implementation, impact force is horizontally applied onto the hinge of the FTS structure with an impact hammer and the corresponding dynamic response is acquisited using the capacitive displacement sensor as shown in Figure 15(e). In Figure 15(f), the fundamental natural frequency is 1840.3 Hz as detected using the impact hammer testing technique. There is a close agreement on the fundamental natural frequency between the FEA and experimental results with an error of 1.4%. Multi-physics analysis is investigated on the interaction between the piezoelectric actuator and FTS structure. As the piezoelectric actuator is driven by a DC voltage 30 V, the corresponding stroke length is 3.829 µm as shown in Figure 15(d). Moreover, the static stiffness of the FTS developed is computed in 10.88 N/µm. The machine stiffness loop of the micro turning machine can be estimated as shown in Figure 14.
Axial stiffness of the spindle: K spinlde = 40.00 N/μm
Lateral stiffness of the air bearing slide: K X_Slide_Z = 40.00 N/μm
Axial stiffness of the tool holder: K Tool_holder = K Flexure + K Piezo= 10.88 N/μm + 20.00 N/μm=30.88 N/μm
Preliminary cutting trials are carried out for machining micro-featured surface pattern on an Al workpiece using the FTS in the face turning process shown in Figure 15(b). The FTS can be considered as one type of smart tool systems to position the tool precisely and dynamically, which is essential for machining micro-structured surfaces and special-featured components.
Protecting and enhancing the tool when the measured force is greater than the reference force;
Maintaining high productivity when the measured force is less than the reference force, and;
The improved reliability of the smart cutting tools in smart machining applications .
to operate autonomously (Intelligent) in a smart manner.
to avoid and correct processing errors in process (Secured).
to self-learn from the real-time data and anticipate the dynamic changes (Managed).
to interact with other machines and systems (Connected), while operating on the shop-floor manufacturing cell and system.
ISMC (Intelligent, Secured, Managed and Connected) represents the essential features of smart machining processes enabled by smart toolings (smart cutting tools, smart collets and smart fixtures, etc.). ISMC is the essential and dispensable design rules and fundamentals in developing smart toolings and adaptive smart machining systems.
A number of smart tools, including cutting force-based smart cutting tools, cutting temperature-based tools, FTS and smart collets/fixtures are presented in this paper. The design concepts of the force-based smart cutting tools are proposed using the piezoelectric film based on the force shunt measurement and the indirect force measurement methods. With the depth of cut from 0.1 mm to 0.8 mm, a close agreement on the orthogonal cutting force measurement can be achieved by using Kistler dynamometer and the two respective smart cutting tools developed. In order to achieve higher accuracy and more reliable measurement, SAW-based smart tooling development is exploited with the application to ultraprecision machining. Based on modelling and simulation analysis, a better understanding of SAW-based sensors is obtained and used to optimize the practical design of the SAW-based smart cutting tool. The experimental results from machining trials show close agreement between the Kistler dynamometer and the SAW-based smart cutting tool on the main cutting force measurement. The preliminary cutting trials using the internally cooled smart cutting tool have demonstrated the temperature of the cutting tip can be reduced by pumping the coolant through internal micro-channels within the smart cutting tool. Smart collets are also presented in line with requirements for smart spindles and high precision micro drilling and milling application. Further in-depth research for the internally cooled cutting tool is carried out particularly on its applications in adaptive machining. In the final part of this paper, one of the presented smart tools was used in smart machining by using adaptive control to maintain the cutting force constant with varied depths of cut by adapting the federate, which can be used particularly in machining components made from hybrid materials or hybrid structures, such as composite-aluminum-titanium structures, in aerospace industry.
This paper presents the smart cutting tools which act as the essential interface devices between smart machine tools and smart machining processes. The smart tooling can also be extended into smart fixtures and jigs, which are indispensable parts of smart machining systems particularly applicable in the context of Industry 4.0 and beyond .
The authors gratefully acknowledge the committed support of all the technical staff of the AMEE Department at Brunel University London. Particular gratitude is expressed to Dr Saiful Anwar Bin Che Ghani, Dr Hui Ding and Mr Paul Yates.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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