6,209 research outputs found

    Active chatter control in high-speed milling processes

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    In present day manufacturing industry, an increasing demand for highprecision products at a high productivity level is seen. High-speed milling is a manufacturing technique which is commonly exploited to produce highprecision parts at a high productivity level for the aeroplane, automotive and mould and dies industry. The performance of a manufacturing process such as high-speed milling, indicated by the material removal rate, is limited by the occurrence of a dynamic instability phenomenon called chatter. The occurrence of chatter results in an inferior workpiece quality due to heavy vibrations of the cutter. Moreover, a high level of noise is produced and the tool wears out rapidly. Although different types of chatter exist, regenerative chatter is recognised as the most prevalent type of chatter. The occurrence of (regenerative) chatter has such a devastating effect on workpiece quality and tool wear that it should be avoidedat all times. The occurrence of chatter can be visualised in so-called stability lobes diagrams (sld). In an sld the chatter stability boundary between a stable cut (i.e. without chatter) and an unstable cut (i.e. with chatter) is visualised in terms of spindle speed and depth of cut. Using the information gathered in a sld, the machinist can select a chatter free operating point. In this thesis two problems are tackled. Firstly, due to e.g. heating of the spindle, tool wear, etc., the sld may vary in time. Consequently, a stable working point that was originally chosen by the machinist may become unstable. This requires a (controlled) adaptation of process parameters such that stability of the milling process is ensured (i.e. chatter is avoided) even under such changing process conditions. Secondly, the ever increasing demand for high-precision products at a high productivity level requires dedicated shaping of the chatter stability boundary. Such shaping of the sld should render working points (in terms of spindle speed and depth of cut) of high productivity feasible, while avoiding chatter. These problems require the design of dedicated control strategies that ensure stable high-speed milling operations with increased performance. In this work, two chatter control strategies are developed that guarantee high-speed chatter-free machining operations. The goal of the two chatter control strategies is, however, different. The first chatter control strategy guarantees chatter-free high-speed milling operations by automatic adaptation of spindle speed and feed (i.e. the feed is not stopped during the spindle speed transition). In this way, the high-speed milling process will remain stable despite changes in the process, e.g. due to heating of the spindle, tool wear, etc. To do so, an accurate and fast chatter detection algorithm is presented which predicts the occurrence of chatter before chatter marks are visible on the workpiece. Once the onset of chatter is detected, the developed controller adapts the spindle speed and feed such that a new chatter-free working point is attained. Experimental results confirm that by using this control strategy chatter-free machining is ensured. It is also shown experimentally that the detection algorithm is able to detect chatter before it is fully developed. Furthermore, the control strategy ensures that chatter is avoided, thereby ensuring a robust machining operation and a high surface quality. The second chatter control strategy is developed to design controllers that guarantee chatter-free cutting operations in an a priori defined range of process parameters (spindle speed and depth of cut) such that a higher productivity can be attained. Current (active) chatter control strategies for the milling process cannot provide such a strong guarantee of a priori stability for a predefined range of working points. The methodology is based on a robust control approach using µ-synthesis, where the most important process parameters (spindle speed and depth of cut) are treated as uncertainties. The proposed methodology will allow the machinist to define a desired working range (in spindle speed and depth of cut) and lift the sld locally in a dedicated fashion. Finally, experiments have been performed to validate the working principle of the active chatter control strategy in practice. Hereto, a milling spindle with an integrated active magnetic bearing is considered. Based on the obtained experimental results, it can be stated that the active chatter control methodology, as presented in this thesis, can indeed be applied to design controllers, which alter the sld such that a pre-defined domain of working points is stabilised. Results from milling tests underline this conclusion. By using the active chatter controller working points with a higher material removal rate become feasible while avoiding chatter. To summarise, the control strategies developed in this thesis, ensure robust chatter-free high-speed milling operations where, by dedicated shaping of the chatter stability boundary, working points with a higher productivity are attained

    An intelligent knowledge based cost modelling system for innovative product development

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    This research work aims to develop an intelligent knowledge-based system for product cost modelling and design for automation at an early design stage of the product development cycle, that would enable designers/manufacturing planners to make more accurate estimates of the product cost. Consequently, a quicker response to customers’ expectations. The main objectives of the research are to: (1) develop a prototype system that assists an inexperienced designer to estimate the manufacturing cost of the product, (2) advise designers on how to eliminate design and manufacturing related conflicts that may arise during the product development process, (3) recommend the most economic assembly technique for the product in order to consider this technique during the design process and provide design improvement suggestions to simplify the assembly operations (i.e. to provide an opportunity for designers to design for assembly (DFA)), (4) apply a fuzzy logic approach to certain cases, and (5) evaluate the developed prototype system through five case studies. The developed system for cost modelling comprises of a CAD solid modelling system, a material selection module, knowledge-based system (KBS), process optimisation module, design for assembly module, cost estimation technique module, and a user interface. In addition, the system encompasses two types of databases, permanent (static) and temporary (dynamic). These databases are categorised into five separate groups of database, Feature database, Material database, Machinability database, Machine database, and Mould database. The system development process has passed through four major steps: firstly, constructing the knowledge-based and process optimisation system, secondly developing a design for assembly module. Thirdly, integrating the KBS with both material selection database and a CAD system. Finally, developing and implementing a ii fuzzy logic approach to generate reliable estimation of cost and to handle the uncertainty in cost estimation model that cannot be addressed by traditional analytical methods. The developed system has, besides estimating the total cost of a product, the capability to: (1) select a material as well as the machining processes, their sequence and machining parameters based on a set of design and production parameters that the user provides to the system, and (2) recommend the most economic assembly technique for a product and provide design improvement suggestion, in the early stages of the design process, based on a design feasibility technique. It provides recommendations when a design cannot be manufactured with the available manufacturing resources and capabilities. In addition, a feature-by-feature cost estimation report was generated using the system to highlight the features of high manufacturing cost. The system can be applied without the need for detailed design information, so that it can be implemented at an early design stage and consequently cost redesign, and longer lead-time can be avoided. One of the tangible advantages of this system is that it warns users of features that are costly and difficult to manufacture. In addition, the system is developed in such a way that, users can modify the product design at any stage of the design processes. This research dealt with cost modelling of both machined components and injection moulded components. The developed cost effective design environment was evaluated on real products, including a scientific calculator, a telephone handset, and two machined components. Conclusions drawn from the system indicated that the developed prototype system could help companies reducing product cost and lead time by estimating the total product cost throughout the entire product development cycle including assembly cost. Case studies demonstrated that designing a product using the developed system is more cost effective than using traditional systems. The cost estimated for a number of products used in the case studies was almost 10 to 15% less than cost estimated by the traditional system since the latter does not take into consideration process optimisation, design alternatives, nor design for assembly issue

    Probabilistic machine learning and artificial intelligence.

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    How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.The author acknowledges an EPSRC grant EP/I036575/1, the DARPA PPAML programme, a Google Focused Research Award for the Automatic Statistician and support from Microsoft Research.This is the author accepted manuscript. The final version is available from NPG at http://www.nature.com/nature/journal/v521/n7553/full/nature14541.html#abstract

    Aggregate assembly process planning for concurrent engineering

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    In today's consumer and economic climate, manufacturers are finding it increasingly difficult to produce finished products with increased functionality whilst fulfilling the aesthetic requirements of the consumer. To remain competitive, manufacturers must always look for ways to meet the faster, better, and cheaper mantra of today's economy. The ability for any industry to mirror the ideal world, where the design, manufacturing, and assembly process of a product would be perfected before it is put mto production, will undoubtedly save a great deal of time and money. This thesis introduces the concept of aggregate assembly process planning for the conceptual stages of design, with the aim of providing the methodology behind such an environment. The methodology is based on an aggregate product model and a connectivity model. Together, they encompass all the requirements needed to fully describe a product in terms of its assembly processes, providing a suitable means for generating assembly sequences. Two general-purpose heuristics methods namely, simulated annealing and genetic algorithms are used for the optimisation of assembly sequences generated, and the loading of the optimal assembly sequences on to workstations, generating an optimal assembly process plan for any given product. The main novelty of this work is in the mapping of the optimisation methods to the issue of assembly sequence generation and line balancing. This includes the formulation of the objective functions for optimismg assembly sequences and resource loading. Also novel to this work is the derivation of standard part assembly methodologies, used to establish and estimate functional tunes for standard assembly operations. The method is demonstrated using CAPABLEAssembly; a suite of interlinked modules that generates a pool of optimised assembly process plans using the concepts above. A total of nine industrial products have been modelled, four of which are the conceptual product models. The process plans generated to date have been tested on industrial assembly lines and in some cases yield an increase in the production rate

    Surface roughness modelling in super duplex stainless steel turning

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    Super duplex stainless steels are alloys that have good corrosion resistance properties and are intended for applications in corrosive environments. Due to their chemical composition and microstructure providing high strength and thermal resistance as well as high ductility, the machinability of these alloys is difficult, resulting in longer production cycles and higher costs in terms of more frequent replacement of tools. In this paper, the machinability of the super duplex EN 1.4410 was investigated under environmentally friendly machining process by using cold compressed air as a coolant. Experimental data were generated using the range of selected input parameters and correspondingly analysed surface roughness as output data. Predictive models were developed in order to make a comparison of their prediction performance. In addition, this paper also describes the methodology for optimised development of a particular predictive model. Finally, comparative analysis of the accuracy of predictive models was performed in order to define which model represents the best fit for the analysed experimental data, and also to show validity of the optimisation process

    Optimisation of welding parameters to mitigate the effect of residual stress on the fatigue life of nozzle–shell welded joints in cylindrical pressure vessels.

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    Doctoral Degree. University of KwaZulu-Natal, Durban.The process of welding steel structures inadvertently causes residual stress as a result of thermal cycles that the material is subjected to. These welding-induced residual stresses have been shown to be responsible for a number of catastrophic failures in critical infrastructure installations such as pressure vessels, ship’s hulls, steel roof structures, and others. The present study examines the relationship between welding input parameters and the resultant residual stress, fatigue properties, weld bead geometry and mechanical properties of welded carbon steel pressure vessels. The study focuses on circumferential nozzle-to-shell welds, which have not been studied to this extent until now. A hybrid methodology including experimentation, numerical analysis, and mathematical modelling is employed to map out the relationship between welding input parameters and the output weld characteristics in order to further optimize the input parameters to produce an optimal welded joint whose stress and fatigue characteristics enhance service life of the welded structure. The results of a series of experiments performed show that the mechanical properties such as hardness are significantly affected by the welding process parameters and thereby affect the service life of a welded pressure vessel. The weld geometry is also affected by the input parameters of the welding process such that bead width and bead depth will vary depending on the parametric combination of input variables. The fatigue properties of a welded pressure vessel structure are affected by the residual stress conditions of the structure. The fractional factorial design technique shows that the welding current (I) and voltage (V) are statistically significant controlling parameters in the welding process. The results of the neutron diffraction (ND) tests reveal that there is a high concentration of residual stresses close to the weld centre-line. These stresses subside with increasing distance from the centre-line. The resultant hoop residual stress distribution shows that the hoop stresses are highly tensile close to the weld centre-line, decrease in magnitude as the distance from the weld centre-line increases, then decrease back to zero before changing direction to compressive further away from the weld centre-line. The hoop stress distribution profile on the flange side is similar to that of the pipe side around the circumferential weld, and the residual stress peak values are equal to or higher than the yield strength of the filler material. The weld specimens failed at the weld toe where the hoop stress was generally highly tensile in most of the welded specimens. The multiobjective genetic algorithm is successfully used to produce a set of optimal solutions that are in agreement with values obtained during experiments. The 3D finite element model produced using MSC Marc software is generally comparable to physical experimentation. The results obtained in the present study are in agreement with similar studies reported in the literature

    A comparison of processing techniques for producing prototype injection moulding inserts.

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    This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

    Reducing risk in pre-production investigations through undergraduate engineering projects.

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    This poster is the culmination of final year Bachelor of Engineering Technology (B.Eng.Tech) student projects in 2017 and 2018. The B.Eng.Tech is a level seven qualification that aligns with the Sydney accord for a three-year engineering degree and hence is internationally benchmarked. The enabling mechanism of these projects is the industry connectivity that creates real-world projects and highlights the benefits of the investigation of process at the technologist level. The methodologies we use are basic and transparent, with enough depth of technical knowledge to ensure the industry partners gain from the collaboration process. The process we use minimizes the disconnect between the student and the industry supervisor while maintaining the academic freedom of the student and the commercial sensitivities of the supervisor. The general motivation for this approach is the reduction of the entry cost of the industry to enable consideration of new technologies and thereby reducing risk to core business and shareholder profits. The poster presents several images and interpretive dialogue to explain the positive and negative aspects of the student process
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