1,721,316 research outputs found
A proposal of an assembly workstation for car panel fitting aided by an augmented reality device
No full textIn the automotive sector, panel fitting operations represent a delicate phase of the assembly process, during which car bodywork components are manually aligned attempting to comply with spacing tolerances. Digital technologies currently promoted by the Industry 4.0 approach, such as collaborative robots and augmented reality (AR), could assist workers for reducing execution times of this "trial and error"procedure. On the one hand, human-robot collaboration (HRC) can enhance assembly process efficiency, by combining human dexterity and cognitive capabilities with robot repetitiveness and support in heavy load handling; on the other, AR can provide interactive instructions to guide workers during the process. In this regard, the present paper is focused on the development of a novel assembly workstation using HRC and AR to support workers during car panel fitting operations. The system is based on the implementation of an algorithm able to convert the values on panel spacing, which are measured by laser gauge positioned on the collaborative robot, in the instructions for the worker to correctly carry out the panel fitting operation. The paper finally presents the application of the system to a real assembly example
A Multi-Objective Software Tool for Manual Assembly Line Balancing using a Genetic Algorithm
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Drilling carbon fiber reinforced plastics with pre-cooling treatment by cryogenic fluid
No full textThe high technological properties of carbon fiber reinforced plastics (CFRPs) have led to their ever-increasing use in recent decades for industrial applications, especially in the aerospace and automotive sectors, where the demand for lightweight structures is high. The panels of composite, to be assembled with other materials, may require repeated realization of holes, making the final quality of the union highly dependent on the drilling process. However, the heterogeneity of the composite material may lead to several inconveniencies, such as rapid tool wear and hole delamination, as during machining the drill bit encounters fiber and matrix alternatively, which have different properties. These damages could be reduced through cryogenic drilling, as demonstrated in the related literature, mainly because the machining behavior of composite changes at low temperatures. Starting from this evidence, the present paper proposes an experimental study conducted on CFRP panels using a new methodology of cryogenic drilling, based on the pre-cooling of the composite before starting the machining process, in order to create a uniformly refrigerated material. The analysis is aimed at comparing the hole quality obtained under dry and pre-cooled cryogenic conditions in terms of delamination, surface roughness and dimensional accuracy and at evaluating thrust force, tool wear and the influence of feed rate
Job rotation and human–robot collaboration for enhancing ergonomics in assembly lines by a genetic algorithm
No full textCurrently, the largest percentage of the employed workforce in the manufacturing industry is involved in the assembly process, making ergonomics a key factor when dealing with assembly-related problems. During these processes, repetitive tasks and heavy component handling are frequent for workers, who may result overloaded from an energetic point of view, thus affecting several aspects not only relating to the human factor but also to potentially reduced productivity. Different organizational strategies and technological solutions could be adopted to overcome these drawbacks. For these purposes, the present paper proposes a genetic algorithm for solving the typical problem of assembly line balancing, taking into account job rotation and human–robot collaboration for enhancing ergonomics of workers. The objectives of the problem are related to both economic aspects and human factor: (i) the cost for implementing the assembly line is minimized, evaluated on the basis of the number of workers and differentiated by skill levels and on equipment installed on workstations, including collaborative robots, and (ii) the energy load variance among workers is also minimized, so as to smooth their energy expenditure in performing the assigned assembly operations, calculated according to their movements, physiological characteristics, job rotations and degree of collaboration with robots. The paper finally presents and discusses the application of the developed tool to an industrial assembly case
Sensitivity analysis and validation of a genetic approach to enhance ergonomics in assembly lines
No full textManual assembly processes are largely performed today in the industry to benefit from human features of dexterity and flexibility. For this reason, the human factor should be properly regarded when designing assembly processes and systems, where repetitive and physically demanding operations are frequent. This work aims to present and validate a software tool for solving a bi-objective version of the assembly line balancing problem, in which, besides the efficiency of the process, the optimization of ergonomics is pursued. The software, based on a genetic algorithm, aims to distribute assembly tasks on the line to smooth the energetic workload among the different workers assigned to manual workstations, considering their physical capabilities and limits. To validate the system and assess its robustness, tests for different case studies taken from the industrial reality are presented and discussed, together with a sensitivity analysis conducted on problem parameters. Experimental results show that the developed tool optimizes the two objectives in different scenarios, thus demonstrating its profitable use in the industrial reality for planning manual assembly processes that do not overload workers assigned to the line
Optimizing ergonomics in assembly lines: A multi objective genetic algorithm
No full textErgonomics is an essential aspect to deal with while solving problems related to manual assembly, for the effects it may have on both productivity and human factor related issues. The frequent execution of repetitive movements and the handling of heavy components are among the main factors that characterize the assembly process, potentially resulting in worker's overload. An appropriate distribution of assembly operations and, therefore of relative workloads, on a production line can improve ergonomic aspects, according to the worker's anthropometric and physiological characteristics. In this paper, a multi-objective genetic algorithm for solving the assembly line balancing problem taking into account ergonomics based on energy expenditure is proposed. The novelty of the contribution relies in the assignment of assembly tasks to workstations considering a set of human operators actually available in a company. The assignment of workers is based on their physical capabilities and limits, evaluated according to their anthropometric and physiological characteristics. The objectives of the problem, besides the minimization of the number of workstations, are related to the human factor; in particular, the distribution of assembly tasks to workstations according to worker technical skills and to worker physical capabilities are optimized. A practical case study taken from the industrial reality is finally tested and discussed
Designing assembly lines with humans and collaborative robots: A genetic approach
No full textHuman-robot collaboration represents a significant evolutionary step in manufacturing. A crucial point is to establish a proper task assignment to combine robot productivity with human flexibility. In this regard, this paper proposes a genetic algorithm to approach the Assembly Line Balancing Problem (ALBP) in the case of human-robot collaborative work. The aim is the minimization of: i) the assembly line cost, evaluated according to the number of workers and equipment on the line, including collaborative robots, ii) the number of skilled workers on the line, iii) the energy load variance among workers, based on their energy expenditures and thus on their physical capabilities and on the level of collaboration with robots
Improving ergonomics in mixed-model assembly lines balancing noise exposure and energy expenditure
No full textIn the manufacturing industry, assembly processes involve most of the workforce to deal with the many manual operations. Thus, the design of workplaces must take into account ergonomics to promote workers well-being and safeguard their health and safety, also enhancing productivity. The occupational ergonomic risk not only depends on the physical workload of a task, but also on environmental characteristics of the workplace, including noise, the assessment of which may contribute to prevent workers from possible health issues associated to hearing injuries. In this regard, the present study proposes a software tool based on a genetic algorithm for solving the mixed-model assembly line balancing problem with job rotation and collaborative robots to improve workers’ ergonomics, for the evaluation of which noise exposure is also considered. In particular, the objectives of the problem concern economic aspects, which are taken into account through the optimization of the cost of the line, and ergonomics, which is pursued by reducing and smoothing both workers’ energy expenditure and noise exposure for performing operations on the line. To test the effectiveness of the proposed approach, an industrial case study is finally discussed
An augmented reality approach for supporting panel alignment in car body assembly
No full textOne of the major problems in automotive assembly consists in achieving alignment within the specified tolerances between car panels that make up the exterior bodywork. To reduce errors and time requested to perform the assigned assembly tasks, workers should be guided during these panel fitting operations. Augmented Reality (AR) could be particularly suitable in this regard, as it represents one of the most promising tools to support personnel, with constantly growing applications in production processes. Following this trend, the present work aims to present an AR prototype system for supporting the operator during panel fitting operations of car body assembly, by providing instructions to correct alignment errors in terms of gap and flushness. A real case study concerning the fine alignment of car body panels with respect to the front light projector is also presented
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