Research Trends and Outlooks in Assembly Line Balancing Problems

This paper presents the findings from the survey of articles published on the assembly line balancing problems (ALBPs) during 2014-2018. Before proceeding a comprehensive literature review, the ineffectiveness of the previous ALBP classification structures is discussed and a new classification scheme based on the layout configurations of assembly lines is subsequently proposed. The research trend in each layout of assembly lines is highlighted through the graphical presentations. The challenges in the ALBPs are also pinpointed as a technical guideline for future research works

A geometrical model for managing surface productivity of U-Shaped assembly lines

U-Shaped Assembly Lines (U-SALs) are cellular manufacturing systems that, among other things, provide a remarkable feature for industrial cost efficiency: their effectiveness in space utilization. While the challenge of machine placement for labour productivity optimization is widely studied in the literature, surface productivity optimization has been scarcely explored. This paper proposes an industry-validated geometrical model for optimizing U-SAL surface productivity. The model links the drivers for market, product and process with the geometrical design. Managers and lean practitioners can use this approach to make decisions for layout design. The model is particularly useful in cases where the cost of floor space is substantially high.Peer ReviewedPostprint (author's final draft

Multi-objective particle swarm optimization for the structural design of concentric tube continuum robots for medical applications

Concentric tube robots belong to the class of continuum robotic systems whose morphology is described by continuous tangent curvature vectors. They are composed of multiple, interacting tubes nested inside one another and are characterized by their inherent flexibility. Concentric tube continuum robots equipped with tools at their distal end have high potential in minimally invasive surgery. Their morphology enables them to reach sites within the body that are inaccessible with commercial tools or that require large incisions. Further, they can be deployed through a tight lumen or follow a nonlinear path. Fundamental research has been the focus during the last years bringing them closer to the operating room. However, there remain challenges that require attention. The structural synthesis of concentric tube continuum robots is one of these challenges, as these types of robots are characterized by their large parameter space. On the one hand, this is advantageous, as they can be deployed in different patients, anatomies, or medical applications. On the other hand, the composition of the tubes and their design is not a straightforward task but one that requires intensive knowledge of anatomy and structural behavior. Prior to the utilization of such robots, the composition of tubes (i.e. the selection of design parameters and application-specific constraints) must be solved to determine a robotic design that is specifically targeted towards an application or patient. Kinematic models that describe the change in morphology and complex motion increase the complexity of this synthesis, as their mathematical description is highly nonlinear. Thus, the state of the art is concerned with the structural design of these types of robots and proposes optimization algorithms to solve for a composition of tubes for a specific patient case or application. However, existing approaches do not consider the overall parameter space, cannot handle the nonlinearity of the model, or multiple objectives that describe most medical applications and tasks. This work aims to solve these fundamental challenges by solving the parameter optimization problem by utilizing a multi-objective optimization algorithm. The main concern of this thesis is the general methodology to solve for patient- and application-specific design of concentric tube continuum robots and presents key parameters, objectives, and constraints. The proposed optimization method is based on evolutionary concepts that can handle multiple objectives, where the set of parameters is represented by a decision vector that can be of variable dimension in multidimensional space. Global optimization algorithms specifically target the constrained search space of concentric tube continuum robots and nonlinear optimization enables to handle the highly nonlinear elasticity modeling. The proposed methodology is then evaluated based on three examples that include cooperative task deployment of two robotic arms, structural stiffness optimization under the consideration of workspace constraints and external forces, and laser-induced thermal therapy in the brain using a concentric tube continuum robot. In summary, the main contributions are 1) the development of an optimization methodology that describes the key parameters, objectives, and constraints of the parameter optimization problem of concentric tube continuum robots, 2) the selection of an appropriate optimization algorithm that can handle the multidimensional search space and diversity of the optimization problem with multiple objectives, and 3) the evaluation of the proposed optimization methodology and structural synthesis based on three real applications

Energy Efficient Policies, Scheduling, and Design for Sustainable Manufacturing Systems

Climate mitigation, more stringent regulations, rising energy costs, and sustainable manufacturing are pushing researchers to focus on energy efficiency, energy flexibility, and implementation of renewable energy sources in manufacturing systems. This thesis aims to analyze the main works proposed regarding these hot topics, and to fill the gaps in the literature. First, a detailed literature review is proposed. Works regarding energy efficiency in different manufacturing levels, in the assembly line, energy saving policies, and the implementation of renewable energy sources are analyzed. Then, trying to fill the gaps in the literature, different topics are analyzed more in depth. In the single machine context, a mathematical model aiming to align the manufacturing power required to a renewable energy supply in order to obtain the maximum profit is developed. The model is applied to a single work center powered by the electric grid and by a photovoltaic system; afterwards, energy storage is also added to the power system. Analyzing the job shop context, switch off policies implementing workload approach and scheduling considering variable speed of the machines and power constraints are proposed. The direct and indirect workloads of the machines are considered to support the switch on/off decisions. A simulation model is developed to test the proposed policies compared to others presented in the literature. Regarding the job shop scheduling, a fixed and variable power constraints are considered, assuming the minimization of the makespan as the objective function. Studying the factory level, a mathematical model to design a flow line considering the possibility of using switch-off policies is developed. The design model for production lines includes a targeted imbalance among the workstations to allow for defined idle time. Finally, the main findings, results, and the future directions and challenges are presented

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Space-Time Continuous Models of Swarm Robotic Systems: Supporting Global-to-Local Programming

A generic model in as far as possible mathematical closed-form was developed that predicts the behavior of large self-organizing robot groups (robot swarms) based on their control algorithm. In addition, an extensive subsumption of the relatively young and distinctive interdisciplinary research field of swarm robotics is emphasized. The connection to many related fields is highlighted and the concepts and methods borrowed from these fields are described shortly

Mobile Robots

The objective of this book is to cover advances of mobile robotics and related technologies applied for multi robot systems' design and development. Design of control system is a complex issue, requiring the application of information technologies to link the robots into a single network. Human robot interface becomes a demanding task, especially when we try to use sophisticated methods for brain signal processing. Generated electrophysiological signals can be used to command different devices, such as cars, wheelchair or even video games. A number of developments in navigation and path planning, including parallel programming, can be observed. Cooperative path planning, formation control of multi robotic agents, communication and distance measurement between agents are shown. Training of the mobile robot operators is very difficult task also because of several factors related to different task execution. The presented improvement is related to environment model generation based on autonomous mobile robot observations

An Approach Based on Particle Swarm Optimization for Inspection of Spacecraft Hulls by a Swarm of Miniaturized Robots

The remoteness and hazards that are inherent to the operating environments of space infrastructures promote their need for automated robotic inspection. In particular, micrometeoroid and orbital debris impact and structural fatigue are common sources of damage to spacecraft hulls. Vibration sensing has been used to detect structural damage in spacecraft hulls as well as in structural health monitoring practices in industry by deploying static sensors. In this paper, we propose using a swarm of miniaturized vibration-sensing mobile robots realizing a network of mobile sensors. We present a distributed inspection algorithm based on the bio-inspired particle swarm optimization and evolutionary algorithm niching techniques to deliver the task of enumeration and localization of an a priori unknown number of vibration sources on a simplified 2.5D spacecraft surface. Our algorithm is deployed on a swarm of simulated cm-scale wheeled robots. These are guided in their inspection task by sensing vibrations arising from failure points on the surface which are detected by on-board accelerometers. We study three performance metrics: (1) proximity of the localized sources to the ground truth locations, (2) time to localize each source, and (3) time to finish the inspection task given a 75% inspection coverage threshold. We find that our swarm is able to successfully localize the present so

Industrial machine structural components’ optimization and redesign

Tese de doutoramento em Líderes para as Indústrias TecnológicasO corte por laser é um processo altamente flexível com numerosas vantagens sobre tecnologias concorrentes. O crescimento do mercado é revelador do seu potencial, totalizando 4300 milhões de dólares americanos em 2020. O processo é utilizado em muitas indústrias e as tendências atuais passam por melhorias ao nível do tempo de ciclo, qualidade, custos e exatidão. Os materiais compósitos (nomeadamente polímeros reforçados por fibras) apresentam propriedades mecânicas atrativas para várias aplicações, incluindo a que se relaciona com o presente trabalho: componentes de máquinas industriais. A utilização de compósitos resulta tipicamente em máquinas mais eficientes, exatidão dimensional acrescida, melhor qualidade superficial, melhor eficiência energética e menor impacto ambiental. O principal objetivo deste trabalho é aumentar a produtividade de uma máquina de corte laser, através do redesign de um componente crítico (o pórtico), grande influenciador da exatidão da máquina. Pretende-se com isto criar uma metodologia genérica capaz de auxiliar no processo de redesign de componentes industriais. Dado que o problema lida com dois objetivos concorrentes (redução de peso e aumento de rigidez) e com um elevado número de variáveis, a implementação de uma rotina de otimização é um aspeto central. É crucial demonstrar que o processo de otimização proposto resulta em soluções efetivas. Estas foram validadas através de análise de elementos finitos e de validação experimental, com recurso a um protótipo à escala. O algoritmo de otimização usado é uma metaheurística, inspirado no comportamento de grupos de animais. Algoritmos Particle Swarm são sugeridos com sucesso para problemas de otimização semelhantes. A otimização focou-se na espessura de cada laminado, para diferentes orientações. A rotina de otimização resultou na definição de uma solução quase-ótima para os laminados analisados e permitiu a redução do peso da peça em 43% relativamente à solução atual, bem como um aumento de 25% na aceleração máxima permitida, o que se reflete na produtividade da máquina, enquanto a mesma exatidão é garantida. A comparação entre os resultados numéricos e experimentais para os protótipos mostra uma boa concordância, com divergências pontuais, mas que ainda assim resultam na validação do modelo de elementos finitos no qual se baseia a otimização.Laser cutting is a highly flexible process with numerous advantages over competing technologies. These have ensured the growth of its market, totalling 4300 million United States dollars in 2020. Being used in many industries, the current trends are focused on reduced lead time, increased quality standards and competitive costs, while ensuring accuracy. Composite materials (namely fibre reinforced polymers) present attractive mechanical properties that poses them as advantageous for several applications, including the matter of this thesis: industrial machine components. The use of these materials leads to machines with higher efficiency, dimensional accuracy, surface quality, energy efficiency, and environmental impact. The main goal of this work is to increase the productivity of a laser cutting machine through the redesign of a critical component (gantry), also key for the overall machine accuracy. Beyond that, it is intended that this work lays out a methodology capable of assisting in the redesign of other machine critical components. As the problem leads with two opposing objectives (reducing weight and increasing stiffness), and with many variables, the implementation of an optimization routine is a central aspect of the present work. It is of major importance that the proposed optimization method leads to reliable results, demonstrated in this work by a finite element analysis and through experimental validation, by means of a scale prototype. The optimization algorithm selected is a metaheuristic inspired by the behaviour of swarms of animals. Particle swarm algorithms are proven to provide good and fast results in similar optimization problems. The optimization was performed focusing on the thickness of each laminate and on the orientations present in these. The optimization routine resulted in a definition of a near-optimal solution for the laminates analysed and allowed a weight reduction of 43% regarding the current solution, as well as an increase of 25% in the maximum allowed acceleration, which reflects on the productivity of the machine, while ensuring the same accuracy. The comparison between numeric and experimental testing of the prototypes shows a good agreement, with punctual divergences, but that still validates the Finite elements upon which the optimization process is supported.Portuguese Foundation for Science and Technology - SFRH/BD/51106/2010

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available