Model-based Robust Online Fault Detection for Mating Process of Electric Connectors in Robotic Wiring Harness Assembly Systems

Huang, Jian; Di, Pei; Fukuda, Toshio; Matsuno, Takayuki

doi:10.1109/mhs.2007.4420916

Cited by 21 publications

(18 citation statements)

References 8 publications

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“…They share the same working space and time [1], [4] [5]. However, if we take a look at current manufacturing system using robotic manipulators, it is easy to find out that robotic manipulators are widely used in packaging (even in micro-nano scale [6]), electronic assembly [7], [8], mobile vehicle welding, and so on, which are not suitable for human and robot working together. The manufacturing case we considered, also adopted in this study, is the extension from traditional electronic manufacturing, like electronic module assembly and packaging.…”

Section: Introductionmentioning

confidence: 99%

Optimal Subtask Allocation for Human and Robot Collaboration Within Hybrid Assembly System

Chen

Sekiyama

Cannella

et al. 2014

IEEE Trans. Automat. Sci. Eng.

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137

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In human and robot collaborative hybrid assembly cell as we proposed, it is important to develop automatic subtask allocation strategy for human and robot in usage of their advantages. We introduce a folk-joint task model that describes the sequential and parallel features and logic restriction of human and robot collaboration appropriately. To preserve a cost-effectiveness level of task allocation, we develop a logic mathematic method to quantitatively describe this discrete-event system by considering the system tradeoff between the assembly time cost and payment cost. A genetic based revolutionary algorithm is developed for real-time and reliable subtask allocation to meet the required cost-effectiveness. This task allocation strategy is built for a human worker and collaborates with various robot co-workers to meet the small production situation in future. The performance of proposed algorithm is experimentally studied, and the cost-effectiveness is analyzed comparatively on an electronic assembly case.Note to Practitioners-This paper was motivated by the critical demand within the manufacturing industry to meet the High-Mix, Low-Volume requirements for the changing consumer market demands. A fully robotic manufacturing process cannot obtain sufficient flexibility with a highly variable product line. Therefore, it must aim towards a complimentary cost-effectiveness to improve productivity from other ways. By taking advantage of a human's adaptability and flexibility, we can exploit the concept of a hybrid assembly system for medium sized manufacturing processes. Hybrid assembly creates a modern assembly mode where the robot works as co-worker to collaborate with the human and share the same working space and time. Hybrid assembly cell emphasizes two challenging issues to somehow improve the manufacturing productivity: (1) the way of describing and modeling human and robot collaboration and coordination, and (2) the effective task scheduling and allocation strategy for human and robot. This research is focused on the subtask allocation method while considering the features of human and robot collaboration. The original contribution of this work is the design of an offline and online resource constraint project scheduling problem (RCPSP) algorithm for hybrid assembly systems. The resource is not only limited to the recycle resource, but also extend to the features of human and robot, such as human fatigue issues, and robot assembly failure issues. This RCPSP for hybrid assembly is to realize both sequential and parallel task scheduling between human and several robots while minimizing the assembly time and payment Manuscript cost. This algorithm is fast in reaching the semi-optimal solution, therefore it can be used for both offline and online situations. The simulation results demonstrates the effectiveness of this task scheduling algorithms. We believe this study is helpful to improve the productivity for hybrid assembly system. Index Terms-Genetic algorithm, human and robot collaboration, hybrid assembly sys...

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Section: Introductionmentioning

confidence: 99%

Optimal Subtask Allocation for Human and Robot Collaboration Within Hybrid Assembly System

Chen

Sekiyama

Cannella

et al. 2014

IEEE Trans. Automat. Sci. Eng.

Self Cite

137

View full text Add to dashboard Cite

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“…There are many attraction of automation of difficult assembly by robotic manipulator [1] [2] with advantage that employment issue due to adjustment of production can be ignored. Other advantage is that production line can work all night and all day in factory.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear SVM based anomaly detection for manipulator assembly task

Matsuno

Huang

Fukuda

2012

2012 International Symposium on Micro-NanoMechatronics and Human Science (MHS)

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There is much attraction of automation of difficult assembly by robotic manipulator. However, robots in factory should be overseen by human workers in order to check whether task condition is anomaly or not. In order to reduce human cost, anomaly detection for assembly task is important. A task to tighten a screw as one of assembly tasks is focused on. In this paper, we propose a method to generate high confidence area in the map of features based on nonlinear support vector machine with Gaussian kernel. By proposed method, a robot system can reduce occasions to make mistake in recognition of task conditions.

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“…Currently in electronic manufacturing industry, for instance, the connector insertion on circuit board is entirely done by robotic manipulators. Some simplified models for connector insertion are already studied to help robotic manipulators recover from insertion error [1,2]. However, when confronting complicated shapes of connectors or assembly parts, the extension of existed connector insertion algorithms works not so well.…”

Section: Introductionmentioning

confidence: 99%

Assembly strategy modeling and selection for human and robot coordinated cell assembly

Chen¹,

Sekiyama²,

Sasaki³

et al. 2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Manufacturing industry tends to employ more flexible assembly cells for High-Mix, Low-Volume production. We has proposed an innovative human and robot hybrid assembly cell within this purpose to solve the problem of persistent growing cost for human resources and now and again changes in programs and configurations for robots, and to achieve a high manufacturing efficiency. One of the key issues is to find out the optimal way of allocating the assembly subtasks to both human and robot. In this paper, a model for assembly strategy generation and selection for human and robot coordinated (HRC) cell assembly is proposed. A Dual Generalized Stochastic Petri Net (GSPN) model is theoretically researched and then built based on a practical assembly task for human and robot coordination. Based on GSPN, Monte Carlo method is carried out to study the time cost and payment cost for possible strategies, and Multiple-Objective Optimization (MOOP) method related Cost-effectiveness analysis is adopted to select the optimal ones. We demonstrate the effectiveness of this approach by comparing the simulation and experimental results.

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Model-based Robust Online Fault Detection for Mating Process of Electric Connectors in Robotic Wiring Harness Assembly Systems

Cited by 21 publications

References 8 publications

Optimal Subtask Allocation for Human and Robot Collaboration Within Hybrid Assembly System

Optimal Subtask Allocation for Human and Robot Collaboration Within Hybrid Assembly System

Nonlinear SVM based anomaly detection for manipulator assembly task

Assembly strategy modeling and selection for human and robot coordinated cell assembly

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