Rapid machine tool verification

This paper describes work carried out to develop methods of verifying that machine tools are capable of machining parts to within specification, immediately before carrying out critical material removal operations, and with negligible impact on process times. A review of machine tool calibration and verification technologies identified that current techniques were not suitable due to requirements for significant time and skilled human intervention. A 'solution toolkit' is presented consisting of a selection circular tests and artefact probing which are able to rapidly verify the kinematic errors and in some cases also dynamic errors for different types of machine tool, as well as supplementary methods for tool and spindle error detection. A novel artefact probing process is introduced which simplifies data processing so that the process can be readily automated using only the native machine tool controller. Laboratory testing and industrial case studies are described which demonstrate the effectiveness of this approach.

Research on rework strategies for reconfigurable manufacturing system considering mission reliability

Rework strategies that involve different checking points as well as rework times can be applied into reconfigurable manufacturing system (RMS) with certain constraints, and effective rework strategy can significantly improve the mission reliability of manufacturing process. The mission reliability of process is a measurement of production ability of RMS, which serves as an integrated performance indicator of the production process under specified technical constraints, including time, cost and quality. To quantitatively characterize the mission reliability and basic reliability of RMS under different rework strategies, rework model of RMS was established based on the method of Logistic regression. Firstly, the functional relationship between capability and work load of manufacturing process was studied through statistically analyzing a large number of historical data obtained in actual machining processes. Secondly, the output, mission reliability and unit cost in different rework paths were calculated and taken as the decision variables based on different input quantities and the rework model mentioned above. Thirdly, optimal rework strategies for different input quantities were determined by calculating the weighted decision values and analyzing advantages and disadvantages of each rework strategy. At last, case application were demonstrated to prove the efficiency of the proposed method.

The effects of material variations in high value manufacturing industries

It has never been easy for manufacturing companies to understand their confidence level in terms of how accurate and to what degree of flexibility parts can be made. This brings uncertainty in finding the most suitable manufacturing method as well as in controlling their product and process verification systems. The aim of this research is to develop a system for capturing the company’s knowledge and expertise and then reflect it into an MRP (Manufacturing Resource Planning) system. A key activity here is measuring manufacturing and machining capabilities to a reasonable confidence level. For this purpose an in-line control measurement system is introduced to the company. Using SPC (Statistical Process Control) not only helps to predict the trend in manufacturing of parts but also minimises the human error in measurement. Gauge R&R (Repeatability and Reproducibility) study identifies problems in measurement systems. Measurement is like any other process in terms of variability. Reducing this variation via an automated machine probing system helps to avoid defects in future products.Developments in aerospace, nuclear, oil and gas industries demand materials with high performance and high temperature resistance under corrosive and oxidising environments. Superalloys were developed in the latter half of the 20th century as high strength materials for such purposes. For the same characteristics superalloys are considered as difficult-to-cut alloys when it comes to formation and machining. Furthermore due to the sensitivity of superalloy applications, in many cases they should be manufactured with tight tolerances. In addition superalloys, specifically Nickel based, have unique features such as low thermal conductivity due to having a high amount of Nickel in their material composition. This causes a high surface temperature on the work-piece at the machining stage which leads to deformation in the final product.Like every process, the material variations have a significant impact on machining quality. The main cause of variations can originate from chemical composition and mechanical hardness. The non-uniform distribution of metal elements is a major source of variation in metallurgical structures. Different heat treatment standards are designed for processing the material to the desired hardness levels based on application. In order to take corrective actions, a study on the material aspects of superalloys has been conducted. In this study samples from different batches of material have been analysed. This involved material preparation for microscopy analysis, and the effect of chemical compositions on hardness (before and after heat treatment). Some of the results are discussed and presented in this paper.

Experimental comparison of dynamic tracking performance of iGPS and laser tracker

External metrology systems are increasingly being integrated with traditional industrial articulated robots, especially in the aerospace industries, to improve their absolute accuracy for precision operations such as drilling, machining and jigless assembly. While currently most of the metrology assisted robotics control systems are limited in their position update rate, such that the robot has to be stopped in order to receive a metrology coordinate update, some recent efforts are addressed toward controlling robots using real-time metrology data. The indoor GPS is one of the metrology systems that may be used to provide real-time 6DOF data to a robot controller. Even if there is a noteworthy literature dealing with the evaluation of iGPS performance, there is, however, a lack of literature on how well the iGPS performs under dynamic conditions. This paper presents an experimental evaluation of the dynamic measurement performance of the iGPS, tracking the trajectories of an industrial robot. The same experiment is also repeated using a laser tracker. Besides the experiment results presented, this paper also proposes a novel method for dynamic repeatability comparisons of tracking instruments. © 2011 Springer-Verlag London Limited.

Guest editorial

Full text: With the rapid development of the aerospace industry, manufacturing technologies have to continuously develop and adjust themselves to ever-growing demands coming from more complex component designs and the use of highly engineered materials. Today there is an increased number of manufacturers contributing to the realization of final products, i.e. avionics, so it is easy to perceive the truly globalized dimension of the aerospace manufacturing business. With this comes the demand for further engineering developments on which the academic/industrial research institutes need to deliver solutions to real aerospace manufacturing problems. This is a challenging task since aerospace manufacturing technologies have to cover a wide range of materials (from composites to advanced Ni/Ti alloys), processes (from forging to non-traditional machining and assembly), and parts’ dimensions/batch sizes (from airframes to turbine blades). In this wide context, this Special Issue includes high quality theoretical and experimental scientific contributions on the following topics related to the aerospace manufacturing technology: (a) machining of advance aerospace alloys; (b) abrasive processes applied to aerospace components; (c) surface treatments to enhance fatigue performance of aerospace components; (d) joining and assembly of aerospace components; (e) laser machining of aerospace alloys; (f) automated/supervised manufacture of aerospace components; (g) quality supervision of aerospace manufacturing routes. The breadth of topics in this Special Issue is perhaps indicative of the complexity and challenges that the research related to aerospace manufacturing technology can offer. We hope that this issue will act as a catalyst for the development of further research, academic and industrial interactions, and publications related to aerospace manufacturing technologies for the benefit of the academic and industrial research communities.

Measurement assisted assembly and the roadmap to part-to-part assembly

Cycle times and production costs remain high in aerospace assembly processes largely due to extensive reworking within the assembly jig. Other industries replaced these craft based processes with part-to-part assembly facilitated by interchangeable parts. Due to very demanding interface tolerances and large flexible components it has not been possible to achieve the required interchangeability tolerances for most aerospace structures. Measurement assisted assembly processes can however deliver many of the advantages of part-to-part assembly without requiring interchangeable parts. This paper reviews assembly concepts such as interface management, oneway assembly, interchangeability, part-to-part assembly, jigless assembly and determinate assembly. The relationship between these processes is then detailed and they are organized into a roadmap leading to part-to-part assembly.

Integrated optimisation of surface roughness and tool performance when face milling 416 SS

Tool life is an important factor to be considered during the optimisation of a machining process since cutting parameters can be adjusted to optimise tool changing, reducing cost and time of production. Also the performance of a tool is directly linked to the generated surface roughness and this is important in cases where there are strict surface quality requirements. The prediction of tool life and the resulting surface roughness in milling operations has attracted considerable research efforts. The research reported herein is focused on defining the influence of milling cutting parameters such as cutting speed, feed rate and axial depth of cut, on three major tool performance parameters namely, tool life, material removal and surface roughness. The research is seeking to define methods that will allow the selection of optimal parameters for best tool performance when face milling 416 stainless steel bars. For this study the Taguchi method was applied in a special design of an orthogonal array that allows studying the entire parameter space with only a number of experiments representing savings in cost and time of experiments. The findings were that the cutting speed has the most influence on tool life and surface roughness and very limited influence on material removal. By last tool life can be judged either from tool life or volume of material removal.

Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351

In this work, different artificial neural networks (ANN) are developed for the prediction of surface roughness (R a) values in Al alloy 7075-T7351 after face milling machining process. The radial base (RBNN), feed forward (FFNN), and generalized regression (GRNN) networks were selected, and the data used for training these networks were derived from experiments conducted using a high-speed milling machine. The Taguchi design of experiment was applied to reduce the time and cost of the experiments. From this study, the performance of each ANN used in this research was measured with the mean square error percentage and it was observed that FFNN achieved the best results. Also the Pearson correlation coefficient was calculated to analyze the correlation between the five inputs (cutting speed, feed per tooth, axial depth of cut, chip°s width, and chip°s thickness) selected for the network with the selected output (surface roughness). Results showed a strong correlation between the chip thickness and the surface roughness followed by the cutting speed. © ASM International.

Guest editorial:special issue on digitial enterprise technology

Full text This Proceedings volume contains selected papers from the Fourth International CIRP-sponsored, Conference on Digital Enterprise Technology (DET2007), which was held at the University of Bath, UK, 19–21 September 2007. All selected papers have been suitably enhanced for publication in the Journal and have undergone full review. Digital enterprise technology (DET) is ‘the collection of systems and methods for the digital modelling and analysis of the global product development and realization process, in the context of lifecycle management.’ The principal aim of the DET concept is to provide a coherent context for the development and integration of the various digital technologies that underpin modern design and manufacturing. These technologies can be classified according to the following five key areas. 1. Distributed and collaborative design. 2. Process modelling and process planning. 3. Advanced factory design and modelling. 4. Physical-to-digital environment integrators–verification. 5. Enterprise integration technologies. This special issue is representative of the wide breadth of the DET concept including; a comprehensive review of digital engineering, design processes, digital modelling of machine tools, forming, robotics and machining processes, verification and metrology, and dynamic networks. It is particularly pleasing to see the development of metrology as a key aspect of modern manufacturing technology, linking design intent to process capability. The papers published herein will facilitate the exploration of new and evolving research concepts by the international research community and will influence the development of international standards for the application of DET technologies.

Operation sequencing optimization for five-axis prismatic parts using a particle swarm optimization approach

Operation sequencing is one of the crucial tasks in process planning. However, it is an intractable process to identify an optimized operation sequence with minimal machining cost in a vast search space constrained by manufacturing conditions. Also, the information represented by current process plan models for three-axis machining is not sufficient for five-axis machining owing to the two extra degrees of freedom and the difficulty of set-up planning. In this paper, a representation of process plans for five-axis machining is proposed, and the complicated operation sequencing process is modelled as a combinatorial optimization problem. A modern evolutionary algorithm, i.e. the particle swarm optimization (PSO) algorithm, has been employed and modified to solve it effectively. Initial process plan solutions are formed and encoded into particles of the PSO algorithm. The particles 'fly' intelligently in the search space to achieve the best sequence according to the optimization strategies of the PSO algorithm. Meanwhile, to explore the search space comprehensively and to avoid being trapped into local optima, several new operators have been developed to improve the particle movements to form a modified PSO algorithm. A case study used to verify the performance of the modified PSO algorithm shows that the developed PSO can generate satisfactory results in optimizing the process planning problem. © IMechE 2009.

Influence of cutting parameters and tool wear on martensitic stainless steel surface integrity after a face milling process

Surface finish is one of the most relevant aspects of machining operations, since it is one of the principle methods to assess quality. Also, surface finish influences mechanical properties such as fatigue behavior, wear, corrosion, etc. The feed, the cutting speed, the cutting tool material, the workpiece material and the cutting tool wear are some of the most important factors that affects the surface roughness of the machined surface. Due to the importance of the martensitic 416 stainless steel in the petroleum industry, especially in valve parts and pump shafts, this material was selected to study the influence of the feed per tooth and cutting speed on tool wear and surface integrity. Also the influence of tool wear on surface roughness is analyzed. Results showed that high values of roughness are obtained when using low cutting speed and feed per tooth and by using these conditions tool wear decreases prolonging tool life. Copyright © 2009 by ASME.

Empirical expression of tool wear when face milling 416 SS

During a machining process, cutting parameters must be taken into account, since depending on them the cutting edge starts to wear out to the point that tool can fail and needs to be change, which increases the cost and time of production. Since wear is a negative phenomenon on the cutting tool, due to the fact that tool life is reduced, it is important to optimize the cutting variables to be used during the machining process, in order to increase tool life. This research is focused on the influence of cutting parameters such as cutting speed, feed per tooth and axial depth of cut on tool wear during a face milling operation. The Taguchi method is applied in this study, since it uses a special design of orthogonal array to study the entire parameters space, with only few numbers of experiments. Also a relationship between tool wear and the cutting parameters is presented. For the studies, a martensitic 416 stainless steel was selected, due to the importance of this material in the machining of valve parts and pump shafts. Copyright © 2009 by ASME.

Effects in ultrafast laser micromachining PMMA-based optical fibre grating

Ultrafast laser owns extreme small beam size and high pulse intensity which enable spatial localised modification either on the surface or in the bulk of materials. Therefore, ultrafast laser has been widely used to micromachine optical fibres to alter optical structures. In order to do the precise control of the micromachining process to achieve the desired structure and modification, investigations on laser parameters control should be carried out to make better understanding of the effects in the laser micromachining process. These responses are important to laser machining, most of which are usually unknown during the process. In this work, we report the real time monitored results of the reflection of PMMA based optical fibre Bragg gratings (POFBGs) during excimer ultraviolet laser micromachining process. Photochemical and thermal effects have been observed during the process. The UV radiation was absorbed by the PMMA material, which consequently induced the modifications in both spatial structure and material properties of the POFBG. The POFBG showed a significant wavelength blue shift during laser micromachining. Part of it attributed to UV absorption converted thermal energy whilst the other did not disappear after POFBG cooling off, which attributed to UV induced photodegradation in POF.