942 research outputs found

    A Multi-Objective Optimization Approach for Multi-Head Beam-Type Placement Machines

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    This paper addresses a highly challenging scheduling problem in the field of printed circuit board (PCB) assembly systems using Surface Mounting Devices (SMD). After describing some challenging optimization sub-problems relating to the heads of multi-head surface mounting placement machines, we formulate an integrated multi-objective mathematical model considering of two main sub-problems simultaneously. The proposed model is a mixed integer nonlinear programming one which is very complex to be solved optimally. Therefore, it is first converted into a linearized model and then solved using an efficient multi-objective approach, i.e., the augmented epsilon constraint method. An illustrative example is also provided to show the usefulness and applicability of the proposed model and solution method.PCB assembly. Multi-head beam-type placement machine. Multi-objective mathematical programming. Augmented epsilon-constraint method

    Comparison of a bat and genetic algorithm generated sequence against lead through programming when assembling a PCB using a 6 axis robot with multiple motions and speeds

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    An optimal component feeder arrangement and robotic placement sequence are both important for improving assembly efficiency. Both problems are combinatorial in nature and known to be NP-hard. This paper presents a novel discrete hybrid bat-inspired algorithm for solving the feeder slot assignment and placement sequence problem encountered when planning robotic assembly of electronic components. In our method, we use the concepts of swap operators and swap sequence to redefine position, and velocity operators from the basic bat algorithm. Furthermore, we propose an improved local search method based on genetic operators of crossover and mutation enhanced by the 2-opt search procedure. The algorithm is formulated with the objective of minimizing the total traveling distance of the pick and place device. Through numerical experiments, using a real PCB assembly scenario, we demonstrate the considerable effectiveness of the proposed discrete Bat Algorithm (BA) to improve selection of feeder arrangement and placement sequence in PCB assembly operations and achieve high throughput production. The results also highlighted that the even though the algorithms out performed traditional lead through programming techniques, the programmer must consider the influence of different robot motions

    Setup Optimization in High-Mix Surface Mount PCB Assembly

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    Siirretty Doriast

    A Multi-Objective Optimization Approach for Multi-Head Beam-Type Placement Machines

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    An MILP model and a hybrid evolutionary algorithm for integrated operation optimisation of multi-head surface mounting machines in PCB assembly

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    This paper focuses on an operation optimisation problem for a class of multi-head surface mounting machines in printed circuit board assembly lines. The problem involves five interrelated sub-problems: assigning nozzle types as well as components to heads, assigning feeders to slots and determining component pickup and placement sequences. According to the depth of making decisions, the sub-problems are first classified into two layers. Based on the classification, a two-stage mixed-integer linear programming (MILP) is developed to describe it and a two-stage problem-solving frame with a hybrid evolutionary algorithm (HEA) is proposed. In the first stage, a constructive heuristic is developed to determine the set of nozzle types assigned to each head and the total number of assembly cycles; in the second stage, constructive heuristics, an evolutionary algorithm with two evolutionary operators and a tabu search (TS) with multiple neighbourhoods are combined to solve all the sub-problems simultaneously, where the results obtained in the first stage are taken as constraints. Computational experiments show that the HEA can obtain good near-optimal solutions for small size instances when compared with an optimal solver, Cplex, and can provide better results when compared with a TS and an EA for actual instances

    Optimization of product assignment to assembly lines

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    Dissertação de mestrado em Industrial engineering and ManagementThe work presented in this dissertation was developed in an industrial context integrated in the production control and management department of the Bosch Car Multimedia Portugal S.A – Braga automatic insertion. The problem addressed in this dissertation was finding the best distribution of product families to assign in different lines according to the physical and technical constraints of the assembly lines. In the approach of the problem, it was used tools and techniques of the Operational Research discipline through mathematical modeling, in order to analyze complex situation and obtain more efficient solutions to help in the decision-making process. Based on production data, production needs forecasts and assembly line physical availability, models with different sets of constraints and objective functions were created to present solutions that best fit the question and the specific problem of the present production context. Through specific software that suited the problem, the previously created models were solved, and the solutions were analyzed and evaluated to suit the company’s current needs and for possible and feasible implementation of the solutions.O trabalho apresentado nesta dissertação foi desenvolvido em contexto industrial integrado no departamento de planeamento e controlo de produção da área de inserção automática da Bosch Car Multimédia Portugal S.A - Braga. O problema abordado nesta dissertação foi encontrar a melhor distribuição de famílias de produtos a alocar nas diferentes linhas de produção de acordo com as suas restrições físicas e técnicas. Na abordagem do problema recorreu-se a técnicas de Investigação Operacional através de modelação matemática, para analisar situações complexas e obter soluções mais eficientes. Tendo como base dados da produção, previsões de necessidades e disponibilidade física da produção, foram criados modelos com diferentes conjuntos de restrições e funções objetivo por forma a apresentar soluções que melhor se adequassem à pergunta e ao problema específico do contexto produtivo presente. Através da utilização de software, foram resolvidos os modelos criados anteriormente, sendo que as soluções foram analisadas e avaliadas para a adequação às necessidades atuais da empresa e para a sua possível e viável implementação

    Optimization of robotic assembly of printed circuit board by using evolutionary algorithm

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    This research work describes the development and evaluation of a custom application exploring the use of Artificial Immune System algorithms (AIS) to solve a component placement sequencing problem for printed circuit board (PCB) assembly. In the assembly of PCB’s, the component placement process is often the bottleneck and the equipment to complete component placement is often the largest capital investment

    Optimisation process for robotic assembly of electronic components

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    Adoption of robots in the manufacturing environment is a way to improve productivity, and the assembly of electronic components has benefited from the adoption of highly dedicated automation equipment. Traditionally, articulated 6-axis robots have not been used in electronic surface mount assembly. However, the need for more flexible production systems that can be used for low to medium production builds means that these robots can be used due to their high degrees of flexibility, excellent repeatability and increasingly lower investment costs. This research investigated the application of an articulated robot with six degrees of freedom to assemble a multi-component printed circuit board (PCB) for an electronic product. A heuristic methodology using a genetic algorithm was used to plan the optimal sequence and identify the best location of the parts to the assembly positions on the PCB. Using the optimised paths, a condition monitoring method for cycle time evaluation was conducted using a KUKA KR16 assembly cell together with four different robot path motions. The genetic algorithm approach together with different assembly position iterations identified an optimisation method for improved production throughput using a non-traditional but highly flexible assembly method. The application of optimised articulated robots for PCB assembly can bridge the gap between manual assembly and the high-throughput automation equipment

    Mitigating unbalance using distributed network reconfiguration techniques in distributed power generation grids with services for electric vehicles: A review

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    © 2019 Elsevier Ltd With rapid movement to combat climate change by reducing greenhouse gases, there is an increasing trend to use more electric vehicles (EVs) and renewable energy sources (RES). With more EVs integration into electricity grid, this raises many challenges for the distribution service operators (DSOs) to integrate such RES-based, distributed generation (DG) and EV-like distributed loads into distribution grids. Effective management of distribution network imbalance is one of the challenges. The distribution network reconfiguration (DNR) techniques are promising to address the issue of imbalance along with other techniques such as the optimal distributed generation placement and allocation (OPDGA) method. This paper presents a systematic and thorough review of DNR techniques for mitigating unbalance of distribution networks, based on papers published in peer-reviewed journals in the last three decades. It puts more focus on how the DNR techniques have been used to manage network imbalance due to distributed loads and DG units. To the best of our knowledge, this is the first attempt to review the research works in the field using DNR techniques to mitigate unbalanced distribution networks. Therefore, this paper will serve as a prime source of the guidance for mitigating network imbalance using the DNR techniques to the new researchers in this field

    Assembly Line

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    An assembly line is a manufacturing process in which parts are added to a product in a sequential manner using optimally planned logistics to create a finished product in the fastest possible way. It is a flow-oriented production system where the productive units performing the operations, referred to as stations, are aligned in a serial manner. The present edited book is a collection of 12 chapters written by experts and well-known professionals of the field. The volume is organized in three parts according to the last research works in assembly line subject. The first part of the book is devoted to the assembly line balancing problem. It includes chapters dealing with different problems of ALBP. In the second part of the book some optimization problems in assembly line structure are considered. In many situations there are several contradictory goals that have to be satisfied simultaneously. The third part of the book deals with testing problems in assembly line. This section gives an overview on new trends, techniques and methodologies for testing the quality of a product at the end of the assembling line
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