An Integrated Approach for Fixture Layout Design and Clamping Force Optimization

Fixture Layout Design (FLD) determines the specific position of locators and clamps to orient and holds the workpiece with respect to a machine tool. The FLD approaches that use Finite Element Analysis (FEA) have been widely used in previous works and have become computationally expensive and specific to a particular problem. Further, the FLD and clamping force optimization were often performed separately by ignoring their interdependence. In the present work, the locators' contact forces are uniformly distributed by suitably varying the fixture layout and clamping force to maximize the part dimensional and form quality. The parametric rigid body model is used to depict the behaviour of the workpiece-fixture system, and it is incorporated with the genetic algorithm to optimize the design variables. A prismatic workpiece with pocket milling operation is considered to validate the proposed methodology. Stability criterion and tool-fixture interference are considered constraints. Subsequently, FEA is used to verify the integrity of the proposed approach. The results infer that the uniform distribution of maximum elastic deformation is achieved due to the uniform distribution of contact forces. The suggested approach is proven effective for designing a milling fixture to manufacture components with high dimensional and form precision

Adaptiver Suchansatz zur multidisziplinären Optimierung von Leichtbaustrukturen unter Verwendung hybrider Metaheuristik

Within the last few years environmental regulations, safety requirements and market competitions forced the automotive industry to open up a wide range of new technologies. Lightweight design is considered as one of the most innovative concepts to fulfil environmental, safety and many other objectives at competitive prices. Choosing the best design and production process in the development period is the most significant link in the automobile production chain. A wide range of design and process parameters needs to be evaluated to achieve numerous goals of production. These goals often stand in conflict with each other. In addition to the variation of the concepts and following the objectives, some limitations such as manufacturing restrictions, financial limits, and deadlines influence the choice of the best combination of variables. This study introduces a structural optimization tool for assemblies made of sheet metal, e.g. the automobile body, based on parametrization and evaluation of concepts in CAD and CAE. This methodology focuses on those concepts, which leads to the use of the right amount of light and strong material in the right place, instead of substituting the whole structure with the new material. An adaptive hybrid metaheuristic algorithm is designed to eliminate all factors that would lead to a local minimum instead of global optimum. Finding the global optimum is granted by using some explorative and exploitative search heuristics, which are intelligently organized by a central controller. Reliability, accuracy and the speed of the proposed algorithm are validated via a comparative study with similar algorithms for an academic optimization problem, which shows valuable results. Since structures might be subject to a wide range of load cases, e.g. static, cyclic, dynamic, temperature-dependent etc., these requirements need to be addressed by a multidisciplinary optimization algorithm. To handle the nonlinear response of objectives and to tackle the time-consuming FEM analyses in crash situations, a surrogate model is implemented in the optimization tool. The ability of such tool to present the optimum results in multi-objective problems is improved by using some user-selected fitness functions. Finally, an exemplary sub-assembly made of sheet metal parts from a car body is optimized to enhance both, static load case and crashworthiness.Die Automobilindustrie hat in den letzten Jahren unter dem Druck von Umweltvorschriften, Sicherheitsanforderungen und wettbewerbsfähigem Markt neue Wege auf dem Gebiet der Technologien eröffnet. Leichtbau gilt als eine der innovativsten und offenkundigsten Lösungen, um Umwelt- und Sicherheitsziele zu wettbewerbsfähigen Preisen zu erreichen. Die Wahl des besten Designs und Verfahrens für Produktionen in der Entwicklungsphase ist der wichtigste Ring der Automobilproduktionskette. Um unzählige Produktionsziele zu erreichen, müssen zahlreiche Design- und Prozessparameter bewertet werden. Die Anzahl und Variation der Lösungen und Ziele sowie einige Einschränkungen wie Fertigungsbeschränkungen, finanzielle Grenzen und Fristen beeinflussen die Auswahl einer guten Kombination von Variablen. In dieser Studie werden strukturelle Optimierungswerkzeuge für aus Blech gefertigte Baugruppen, z. Karosserie, basierend auf Parametrisierung und Bewertung von Lösungen in CAD bzw. CAE. Diese Methodik konzentriert sich auf die Lösungen, die dazu führen, dass die richtige Menge an leichtem / festem Material an der richtigen Stelle der Struktur verwendet wird, anstatt vollständig ersetzt zu werden. Eine adaptive Hybrid-Metaheuristik soll verhindern, dass alle Faktoren, die Bedrohungsoptimierungstools in einem lokalen Minimum konvergieren, anstelle eines globalen Optimums. Das Auffinden des globalen Optimums wird durch einige explorative und ausbeuterische Such Heuristiken gewährleistet. Die Zuverlässigkeit, Genauigkeit und Geschwindigkeit des vorgeschlagenen Algorithmus wird mit ähnlichen Algorithmen in akademischen Optimierungsproblemen validiert und führt zu respektablen Ergebnissen. Da Strukturen möglicherweise einem weiten Bereich von Lastfällen unterliegen, z. statische, zyklische, dynamische, Temperatur usw. Möglichkeit der multidisziplinären Optimierung wurde in Optimierungswerkzeugen bereitgestellt. Um die nichtlineare Reaktion von Zielen zu überwinden und um den hohen Zeitverbrauch von FEM-Analysen in Absturzereignissen zu bewältigen, könnte ein Ersatzmodell vom Benutzer verwendet werden. Die Fähigkeit von Optimierungswerkzeugen, optimale Ergebnisse bei Problemen mit mehreren Zielsetzungen zu präsentieren, wird durch die Verwendung einiger vom Benutzer ausgewählten Fitnessfunktionen verbessert. Eine Unterbaugruppe aus Blechteilen, die zur Automobilkarosserie gehören, ist optimiert, um beide zu verbessern; statischer Lastfall und Crashsicherheit

Robust multi-criteria optimisation of welded joints

Civilisation has depended on welded structures to facilitate production and improve the quality of life. Welds are used to create infrastructure upon which we rely, such as transportation, oil and gas piping, shipbuilding, bridges and buildings, and to produce the equipment that makes all of this happen. In short, the joining of two metals through welding has immensely contributed to our society. A critical factor in the strength of welded joints is the geometry of the joints, and for this reason a robust optimisation of geometrical parameters of welded joints has been conducted in order to establish the optimum and most robust design in the presence of variation amongst geometrical parameters. A parametric finite element analysis, using Python script, has been performed with the objective to investigate the effect of the welded joint parameters on the stress concentration factors under tensile and bending load. The results indicate that the parametric model, which is generated by Python script, can be used in a wide range of welded geometry, and has the capacity to reduce the time of computation. Additionally, an experimental study, including the geometrical identification of the welded joints, tensile test, hardness test and fatigue, has also been performed. In order to select the best optimisation algorithms, different optimisation algorithms and performance metrics with various types of problem were examined in this study. The results from this part show the accuracy of Circumscription Metric (CM) in comparison to Pair wise Metric (PW) - which is used widely in optimisation studies. Furthermore, the results show that the Fast Multi-objective Optimisation Algorithm (FMOGA-II) outperformed other optimisation algorithms used during this study. In this study, a new methodology for selecting the most robust designs from within the Pareto set has been developed. Finally, a traditional and robust optimisation of a butt welded joint has been performed by establishing a link between an optimisation software package and parametric finite element, the results of which show the ability of this approach to extract the robust optimal designs from the Pareto front

Determining Sequence of Image Processing Technique (IPT) to Detect Adversarial Attacks

Developing secure machine learning models from adversarial examples is challenging as various methods are continually being developed to generate adversarial attacks. In this work, we propose an evolutionary approach to automatically determine Image Processing Techniques Sequence (IPTS) for detecting malicious inputs. Accordingly, we first used a diverse set of attack methods including adaptive attack methods (on our defense) to generate adversarial samples from the clean dataset. A detection framework based on a genetic algorithm (GA) is developed to find the optimal IPTS, where the optimality is estimated by different fitness measures such as Euclidean distance, entropy loss, average histogram, local binary pattern and loss functions. The "image difference" between the original and processed images is used to extract the features, which are then fed to a classification scheme in order to determine whether the input sample is adversarial or clean. This paper described our methodology and performed experiments using multiple data-sets tested with several adversarial attacks. For each attack-type and dataset, it generates unique IPTS. A set of IPTS selected dynamically in testing time which works as a filter for the adversarial attack. Our empirical experiments exhibited promising results indicating the approach can efficiently be used as processing for any AI model

An approach to multi-objective life cycle cost optimization of wind turbine tower structures

Thesis (MEng)-- Stellenbosch University, 2013.ENGLISH ABSTRACT: Support tower structures of Wind Energy Conversion Systems (WECS) are major cost items and by means of integrated design and optimization, the Life-Cycle Cost (LCC) can be reduced substantially. In this thesis, Horizontal Axis Wind Turbine (HAWTs) tower structures are investigated by means of a technique or tool that can bene t in decision making related situations to reduce the LCC of such WECS support towers from inception to disposal. Often, during the conceptual design phase a certain level of uncertainty or fuzziness exists and plays a role. The central focus in this project is on lattice type towers; however an account on tapered, tubular monopole towers is given as well. The problem is identi ed to be of a multi-objective nature, where a variety of criteria or objectives that are identi ed play a role in the possible reduction of the total LCC of the structure. The study also entails the delineation and discussion of the factors and components that a ect the LCC of a steel structure. The decision maker has control over only a few of these factors and components as identi ed, and these can be formulated by means of an objective to be minimized (or maximized in several other cases). Some of the objectives are incommensurable and others are commensurable with each other. In other words, several of these objectives either `compete' or don't `compete' against each other, respectively. The investigation resulted in the development of a multi-objective LCC optimization using the λ-formulation (or min-max formulation) as the objective aggregating approach for the four objectives identi ed (varied during analysis for sensitivity checks). The objectives are user-de ned in terms of membership functions that grade the degree of membership from total acceptance to total rejection by means of boundary values. This formulation is Non-Pareto based and the decision maker obtains the best trade-o or best compromise solution. The detailed discussion around these objectives is included in the literature study. The objectives in the multi-objective study are weight, cost, perimeter and nodal deflections, and a weighting of the objectives is possible but this is excluded from this study. A Genetic Algorithm (GA), coded in MATLAB, is implemented as the optimization tool or technique. The algorithm uses a quadratic penalty function approach and a natively written Finite Element Analysis (FEA) tool is used for the response model in the tness evaluation process, where the performance for stability, capacity and overall deflections of an individual in the population is quanti ed. A GA has the advantage that it operates on an entire population of individuals using basic principles such as genetics, crossover, mutation, selection and survival of the ttest from biology and Darwinian principles. GAs are very robust and e ective global search methods that can be applied to most elds of study. GAs have previously been e ectively applied in structural, single objective optimization (structural weight) problems. The GA is adopted and modi ed and veri ed with results on academic problems obtained from literature. Satisfactory performance was observed, although room for improvement is identi ed. A case study on a full scale model is performed, using circular hollow sections and equal leg angle sections. These are commonly used steel profi les for lattice type towers. The results obtained are as expected. The structural mass was used as a measure to compare the results. A heavier structure is obtained using the equal leg angle sections compared to the CHS structure with a di fference of up to 20% in weight. The best compromise solutions are feasible and near optimal, given the conditions of the equally weighted objectives in this study. The membership function defi nition and boundary value determination still remains a key issue when using fuzzy logic to incorporate the preference information of the decision maker.AFRIKAANSE OPSOMMING: Toringstrukture van windturbines is belangrike kostekomponente van `n windkragopwekking stelsel. Deur middel van geï ntegreerde ontwerp en optimalisering kan die lewensikluskoste aansienlik verminder word. In hierdie tesis word horisontale-as windturbinetoringstrukture ondersoek. Deur middel van `n tegniek of hulpmiddel wat kan baat vind by besluitneming situasies, word die lewensiklus-koste van sodanige windturbine ondersteuning torings vanaf voorgebruik-fase tot lewenseinde-fase verminder. Dikwels, tydens die konseptuele ontwerp-fase, speel `n sekere vlak van onsekerheid of verwarring ook `n rol. Die sentrale fokus in hierdie projek is op staal vakwerk tipe torings gelê. `n Vereenvoudigde ontleeding van buisvormige torings is ook benader. Die probleem is van multikriteria aard, waar `n verskeidenheid van kriterie of doelwitte ge denti seer was. Hulle speel `n rol in die moontlike vermindering van die totale lewensiklus-koste van die struktuur. Die studie behels ook die bespreking en afbakening van die faktore en komponente wat die lewensiklus-koste van 'n staal struktuur bepaal. Die besluitnemer het slegs beheer oor sekere van hierdie faktore en komponente, en hierdie word deur middel van `n saamgevoegde doel-funksie gede neer wat dan geminimeer word. Sommige van die doelfunksies kompeteer met mekaar en sommige kompeteer nie met mekaar nie. Die ondersoek het gelei tot die ontwikkeling van `n multikriteria lewensiklus-koste optimalisering met behulp van die λ-formulering (of min-max formulering). Hierdie is `n tegniek wat die kriterie in vorm van `n verteenwoordigende doel-funksie saamvoeg. Daar is vier doelwitte wat geï denti seer was. Die gebruiker de nieer spesiale, lineêre doel-funksies wat van totale aanvaarding tot totale verwerping streek. Dit word deur middel van randwaardes gedoen. Hierdie formulering is nie Pareto gebaseer nie, en die besluitnemer verkry die `best trade-off ' of die beste kompromis oplossing. Die detailleerde bespreking rondom hierdie doelwitte is in die literatuurstudie ingesluit. Die doelwitte wat in die multikriteria studie gebruik word is gewig, koste, omtrek van die snitpro el en strukturêle defleksie. `n Gewig kan aan elke kriterium toegeken word, maar dit word van hierdie studie uitgesluit. `n Genetiese algoritme (GA), geï mplementeer in MATLAB, word as die optimalisering instrument en tegniek gebruik. Die algoritme gebruik `n kwadratiese `straf-funksie' en `n MATLAB Eindige Element Analise (EEA) word gebruik vir die gedragsmodel in die `fi ksheid' evalueringsproses. Die prestasie vir stabiliteit, kapasiteit en algehele verlegging van `n individu in die GA bevolking word daardeur gekwanti seer. `n GA het die voordeel, dat dit met `n hele bevolking van individue werk. Dit is gebaseer op beginsels van genetika en Darwin se beginsels. GAs is baie stabiel en ook e ektiewe globale soek metodes wat van toepassing in verskillende studierigtings is. GAs is al e ektief toegepas in strukturêle optimalisering (veral strukturêle gewig optimalisiering). Die GA in hierdie studie was aangepas en die gedrag en prestasie is bevestig met resultate van akademiese probleme uit die literatuur. Bevredigende prestasie is waargeneem, maar ruimte vir verbetering is ook geï denti seer. `n Gevallestudie oor `n grootskaal model is uitgevoer, en die gebruik van ronde holpro ele en gelykbenige hoekpro ele is uitgevoer. Dit is algemeen gebruikte staalpro ele vir vakwerk tipe torings. Die resultate wat verkry is, is soos verwag. Die strukturêle massa is gebruik as `n maatstaf om die resultate te vergelyk. `n Swaarder struktuur is die resultaat wanneer gelykbenige hoekpro ele gebruik word in vergelyking met die ronde holpro el struktuur. `n Verskil tot 20% in gewig is waargeneem. Die beste kompromis oplossing is haalbaar en naby-optimaal, gegewe die omstandighede van die gelyk geweegde doelfunksies in hierdie studie. Die doel-funksie de nisie, die voorkeur van die besluitnemer en die bepaling van die randwaardes bly steeds `n belangrike kwessie by die gebruik van hierdie benadering

Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems

This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book

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

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