Optimizing The Machining Process of IS 2062 E250 Steel Plates with The Boring Operation Using a Hybrid Taguchi-Pareto Box Behnken-teaching Learning-based Algorithm

In this article, a new method termed the Taguchi-Pareto-Box Behnken design teaching learning-based optimization (TPBBD–TLBO) was developed to optimize the boring process, which promotes surface roughness as the output. At the same time, the speed, feed, and depth of cut are taken as the inputs. The case examines experimental data from the literature on the boring of IS 2062 E250 steel plates. The proposed method draws from a recent idea on the Taguchi-Pareto-Box Behnken design method that argues for a possible relationship between the Taguchi-Pareto method and the Box Behnken design method. This idea was used as a basis for the further argument that teaching learning-based optimization has a role in the further optimization of the established TPBBD method. The optimal solutions were investigated when the objective function was generated using the Box Behnken design in a case. It was replaced with the regression method in the other case, and the python programming codes were used to execute the computations. Then the optimal solutions concerning the parameters of speed, feed rate, depth of cut, and nose radius were evaluated. With the Box Behnken as the objective function for the TLBO method, convergence was reached at 50 iterations with a class population of 5. The optimal parametric solutions are 800 rpm of speed, 0.06 min/min of feed rate, 1 min for depth of cut, and 0 min for nose radius. On the use of the regression method for the objective function, while the TLBO method was deployed, convergence was experienced after 50 iterations with a class population of 200 students. The optimal parametric solution is 1135rpm of speed, 0.06 min/min of feed rate, 1024 min of the depth of cut, and 0.61 min of nose radius. The speed, depth of cut, and nose radius showed higher values, indicating the use of more energy resources to accomplish the optimal goals using the regression method-based objective function. Therefore, the proposed method constitutes a promising route to optimize further the results of the Taguchi-Pareto-Box Behnken design for boring operation improvement

Modelling the integration between the design and inspection process of geometrical specifications for digital manufacturing

Geometrical Product Specifications (GPS) is a technical language which covers the standardization for micro/macro- geometry specifications. In today’s environment of globalization, out-sourcing and sub-contracting is increasing. Geometrical specifications of a product need to be detailed to a degree where nothing is left open to interpretation. To fulfil this, and to meet the requirements of digital manufacturing, it is necessary to integrate the design and inspection process of a geometrical specification. At the technical level, many functional operator/operations are employed in a geometrical specification. These functional operators/operations are based on rigorous mathematics, and they are intricately related and inconvenient to be used directly. Consequently, it is of practical utility to build an integrated information system to encapsulate and manage the information involved in GPS. This thesis focuses on geometrical tolerancing, including form/orientation/ location tolerancing, and its integrated geometry information system. The main contributions are: Firstly, a global data expression for modelling the integration between the design and inspection process of a geometrical tolerance is presented based on category theory. The categorical data model represents, stores and manipulates all the elements and their relationships involved in design and inspection process of a geometrical tolerance, by categories, objects and morphisms, flexibly; the relationships between objects were refined by pull back structures; and the manipulations of the model such as query and closure of query are realized successfully by functor structures in category theory. Secondly, different categories of knowledge rules have been established to enhance the rationality and the intellectuality of the integrated geometry information system, such as the rules for the application of geometrical requirement, tolerance type, datum and datum reference framework and, for the refinement among geometrical specifications. Finally, the host system for drawing indication of geometrical tolerances in the framework of GPS was established based on AutoCAD 2007 using ObjectARX.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Hybridization of modified sine cosine algorithm with tabu search for solving quadratic assignment problem

Sine Cosine Algorithm (SCA) is a population-based metaheuristic method that widely used to solve various optimization problem due to its ability in stabilizing between exploration and exploitation. However, SCA is rarely used to solve discrete optimization problem such as Quadratic Assignment Problem (QAP) due to the nature of its solution which produce continuous values and makes it challenging in solving discrete optimization problem. The SCA is also found to be trapped in local optima since its lacking in memorizing the moves. Besides, local search strategy is required in attaining superior results and it is usually designed based on the problem under study. Hence, this study aims to develop a hybrid modified SCA with Tabu Search (MSCA-TS) model to solve QAP. In QAP, a set of facilities is assigned to a set of locations to form a one-to-one assignment with minimum assignment cost. Firstly, the modified SCA (MSCA) model with cost-based local search strategy is developed. Then, the MSCA is hybridized with TS to prohibit revisiting the previous solutions. Finally, both designated models (MSCA and MSCA-TS) were tested on 60 QAP instances from QAPLIB. A sensitivity analysis is also performed to identify suitable parameter settings for both models. Comparison of results shows that MSCA-TS performs better than MSCA. The percentage of error and standard deviation for MSCA-TS are lower than the MSCA which are 2.4574 and 0.2968 respectively. The computational results also shows that the MSCA-TS is an effective and superior method in solving QAP when compared to the best-known solutions presented in the literature. The developed models may assist decision makers in searching the most suitable assignment for facilities and locations while minimizing cost

Emerging Trends in Mechatronics

Mechatronics is a multidisciplinary branch of engineering combining mechanical, electrical and electronics, control and automation, and computer engineering fields. The main research task of mechatronics is design, control, and optimization of advanced devices, products, and hybrid systems utilizing the concepts found in all these fields. The purpose of this special issue is to help better understand how mechatronics will impact on the practice and research of developing advanced techniques to model, control, and optimize complex systems. The special issue presents recent advances in mechatronics and related technologies. The selected topics give an overview of the state of the art and present new research results and prospects for the future development of the interdisciplinary field of mechatronic systems

Advanced cutting tools and technologies for drilling carbon fibre reinforced polymer (CFRP) composites: a review

Carbon fibre reinforced polymer (CFRP) composites have excellent specific mechanical properties, these materials are therefore widely used in high-tech industries like the automobile and aerospace sectors. The mechanical machining of CFRP composites is often necessary to meet dimensional or assembly-related requirements; however, the machining of these materials is difficult. In an attempt to explore this issue, the main objective of the present paper is to review those advanced cutting tools and technologies that are used for drilling carbon fibre reinforced polymer composites. In this context, this paper gives a detailed review and discussion of the following: (i) the machinability of CFRP including chip removal mechanisms, cutting force, tool wear, surface roughness, delamination and the characteristics of uncut fibres; (ii) cutting tool requirements for CFRP machining; and (iii) recent industrial solutions: advanced edge geometries of cutting tools, coatings and technologies. In conclusion, it can be stated that advanced geometry cutting tools are often necessary in order to effectively and appropriately machine required quality features when working with CFRP composites.publishe

FITTING A PARAMETRIC MODEL TO A CLOUD OF POINTS VIA OPTIMIZATION METHODS

Computer Aided Design (CAD) is a powerful tool for designing parametric geometry. However, many CAD models of current configurations are constructed in previous generations of CAD systems, which represent the configuration simply as a collection of surfaces instead of as a parametrized solid model. But since many modern analysis techniques take advantage of a parametrization, one often has to re-engineer the configuration into a parametric model. The objective here is to generate an efficient, robust, and accurate method for fitting parametric models to a cloud of points. The process uses a gradient-based optimization technique, which is applied to the whole cloud, without the need to segment or classify the points in the cloud a priori. First, for the points associated with any component, a variant of the Levenberg-Marquardt gradient-based optimization method (ILM) is used to find the set of model parameters that minimizes the least-square errors between the model and the points. The efficiency of the ILM algorithm is greatly improved through the use of analytic geometric sensitivities and sparse matrix techniques. Second, for cases in which one does not know a priori the correspondences between points in the cloud and the geometry model\u27s components, an efficient initialization and classification algorithm is introduced. While this technique works well once the configuration is close enough, it occasionally fails when the initial parametrized configuration is too far from the cloud of points. To circumvent this problem, the objective function is modified, which has yielded good results for all cases tested. This technique is applied to a series of increasingly complex configurations. The final configuration represents a full transport aircraft configuration, with a wing, fuselage, empennage, and engines. Although only applied to aerospace applications, the technique is general enough to be applicable in any domain for which basic parametrized models are available

Modelling and controlling variation propagation in mechanical assembly of high speed rotating machines

Assembly plays a vital role in the quality of a final product and has a great impact on the manufacturing cost. The mechanical assemblies consist of parts that inevitably have variations from their ideal dimensions. These variations propagate and accumulate as parts are assembled together. Excessive amount of variations in an assembly may cause improper functionality of the product being assembled. Improving assembly quality and reducing the assembly time and cost are the main objectives of this thesis. The quality of an assembly is determined in terms of variations in critical assembly dimensions, also known as Key Characteristics (KCs). Key Characteristics are designated to indicate where excess variation will affect product quality and what product features and tolerances require special attention. In order to improve assembly quality and reduce assembly time and cost, it is necessary to: (1) model non-ideal parts based on tolerances defined in design standards or current industrial practice of component inspection, (2) model assemblies and their associated assembly processes to analyse tolerance stack-up in the assembly, (3) develop probabilistic model to predict assembly variation after product assembly, and (4) implement control strategies for minimising assembly variation propagations to find optimum configuration of the assembly. Two assembly models have been developed, a linear model and a fully non-linear model for calculating assembly variation propagations. The assembly models presented in this thesis also allows for inclusion of geometric feature variation of each assembly component. Methods of incorporating geometric feature variations into an assembly variation model are described and analysis techniques are explained. The assembly variation model and the geometric variation models have been developed for 20 and 3D assemblies. Modelling techniques for incorporating process and measurement noise are also developed and described for the nonlinear assembly model and results are given to demonstrate the calculation of assembly variations while considering part, process and measurement errors. Two assembly case studies originating in sub-assemblies of aero-engines have been studied: Case Study 1, representing the rotating part (rotor) of an aero-engine, and Case Study 2, representing non-rotating part (stator) of an aero-engine. A probabilistic method based on the linear model is presented as a general analytical method for analysis of 3D mechanical assemblies. Probability density functions are derived for assembly position errors to analyse a general mechanical assembly, and separate probability functions are derived for the Key Characteristics (KCs) for assembly in Case Studies 1 and 2. The derived probability functions are validated by using the Monte Carlo simulation method based on the exact (full non-linear) model. Results showed that the proposed probabilistic method of estimating tolerance accumulation in mechanical assemblies is very efficient and accurate when compared to the Monte Carlo simulation method, particularly if large variations at the tails of the distributions are considered. Separate control strategies have been implemented for each case study. Four methods are proposed to minimise assembly variations for Case Study 1, and one error minimisation method is suggested for assemblies of Case Study 2. Based on the developed methods to optimise assembly quality, the two case studies were investigated, and it was found that the proposed optimisation methods can significantly improve assembly quality. The developed optimisation methods do not require any special tooling (such as fixtures) and can easily be implemented in practice

Battery Systems and Energy Storage beyond 2020

Currently, the transition from using the combustion engine to electrified vehicles is a matter of time and drives the demand for compact, high-energy-density rechargeable lithium ion batteries as well as for large stationary batteries to buffer solar and wind energy. The future challenges, e.g., the decarbonization of the CO2-intensive transportation sector, will push the need for such batteries even more. The cost of lithium ion batteries has become competitive in the last few years, and lithium ion batteries are expected to dominate the battery market in the next decade. However, despite remarkable progress, there is still a strong need for improvements in the performance of lithium ion batteries. Further improvements are not only expected in the field of electrochemistry but can also be readily achieved by improved manufacturing methods, diagnostic algorithms, lifetime prediction methods, the implementation of artificial intelligence, and digital twins. Therefore, this Special Issue addresses the progress in battery and energy storage development by covering areas that have been less focused on, such as digitalization, advanced cell production, modeling, and prediction aspects in concordance with progress in new materials and pack design solutions

Industrial case study-driven innovative optimised engineering design.

Optimisation research is a vast and comprehensive field of study in academia, but its application to complex real life problems is much more limited. This thesis presents an exploration into the use of optimisation in the weight reduction problems of three industrial case studies. The work sought to find robust and practical solutions that could be exploited in the current commercial environment. The three case studies comprised the housing of a vertical axis wind turbine, a titanium jet engine lifting bracket and a casing for an aircraft cargo release system. The latter two were to be built using additive layer manufacture, while the housing, with initially no prescribed manufacturing method, was required to conform to British Standards for design. Based on commercially available optimisation and analysis packages e.g. Altair Optistruct, ANSYS, Microsoft Excel and MatLab, methodologies were developed to enable solutions to be found within realistic time-scales. Techniques to improve computational efficiency using the Kreisselmieier Steinhauser functions were also investigated. Good weight reduction was achieved in all cases. For the housing, a trend showing the relationship between the overall size of the housing and the material requirement was also developed. Extensive data for the lifting bracket was retrieved and analysed from a crowd-sourced design challenge. This highlighted important elements of design for additive layer manufacture and also gave an indication of the efficacy of different optimisation algorithms. The casing design methodology obtained simplified the material selection for the design. Build orientation software was developed to exploit the advantages of additive layer manufacture. The initial objective to solve the optimisation problems for all three case studies was accomplished using topology and size optimisation with both gradient-based and evolutionary methods. Data analysis and optimisation increased design capability for additive layer manufacture build and orientation

EXPERIMENTAL STUDIES FOR DEVELOPMENT HIGH-POWER AUDIO SPEAKER DEVICES PERFORMANCE USING PERMANENT NdFeB MAGNETS SPECIAL TECHNOLOGY

In this paper the authors shows the research made for improving high-power audio speaker devices performance using permanent NdFeB magnets special technology. Magnetic losses inside these audio devices are due to mechanical system frictions and to thermal effect of Joules eddy currents. In this regard, by special technology, were made conical surfaces at top plate and center pin. Analysing results obtained by modelling the magnetic circuit finite element method using electronic software package,was measured increase efficiency by over 10 %, from 1,136T to13T