Enabling robot agility in manufacturing kitting applications

Kootbally, Zeid; Schlenoff, Craig; Antonishek, Brian; Proctor, Frederick M.; Krämer, Thomas; Harrison, William S.; Downs, Anthony J.; Gupta, Satyandra K.

doi:10.3233/ica-180566

Cited by 17 publications

(11 citation statements)

References 29 publications

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“…These formalisms aimed to structure formal descriptions of related products and information. Zeid Kootbally et al proposed an ontology-based approach for formalizing manufacturing kitting applications [7]. The ontology can improve the flexibility of the manufacturing configurations using robots.…”

Section: Formalisms For Supporting Tool-chain Developmentmentioning

confidence: 99%

A domain-specific modeling approach supporting tool-chain development with Bayesian network models

Wang

Tao

et al. 2020

ICA

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Constructing and evaluating a comprehensive tool-chain with commercial off-the-shelf and proprietary tools for the deployment of model-based systems engineering (MBSE) is a challenging and complex task. Specifically, the lack of early assessment during tool-chain development has led to increased research and development costs when unexpected features are developed or poor decisions are made. In this paper, a domain-specific modeling (DSM) approach is proposed to support decision-makings during tool-chain design and to facilitate quantitative assessment of tool-chain features at early-phases. Using this approach, different views of tool-chains are first formalized under a DSM framework. Then the DSM models are transformed to Bayesian network models for supporting the quantitative assessment of related tools in order to analyze the whole tool-chains' features. In the case study, the approach is verified by comparing two MBSE tool-chains for an auto-braking system design. The results indicate that the DSM approach enhances the understanding of tool-chain concepts, promotes the efficiency of MBSE tool-chain development, and verifies the tool-chain in early development phases using a quantitative approach.

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Section: Formalisms For Supporting Tool-chain Developmentmentioning

confidence: 99%

A domain-specific modeling approach supporting tool-chain development with Bayesian network models

Wang

Tao

et al. 2020

ICA

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“…The development and the improvement of the technologies used for the design of collaborative robots, together with the reduction of the investment required for their installation, have led to an interesting spread of these systems [11,12]. Recent research has shown how a proper programming of a cobot can be crucial to guarantee a successful use of such a device [13]; other important aspects are related to the used visual system and to the effectiveness of the grasp action [14,15].…”

Section: Literature Analysismentioning

confidence: 99%

Modelling time efficiency of cobot-supported kit preparation

Fager

Calzavara

Sgarbossa

2019

Int J Adv Manuf Technol

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Kittingmeaning to supply assembly with components in presorted kitsis widely seen as beneficial for assembly quality and efficiency when there is a multitude of component variants. However, the process by which kits are preparedthe kit preparation is labour-intensive, and kit errors are problematic at assembly processes. The use of robotics to support kit preparation has received some attention by researchers, but literature is lacking with respect to how collaborative robotscobotscan support kit preparation activities. The purpose of this paper is to identify the potential of a cobot to support time-efficient batch preparation of kits. To address the purpose, the paper presents a mathematical model for estimation of the cycle time associated with cobotsupported kit preparation. The model is applied in a numerical example with experimental data from laboratory experiments, and cobot-supported kit preparation is compared with manual kit preparation. The findings suggest that cobot-supported kit preparation is beneficial with diverse kits and smaller components quantities per SKU (Stock Keeping Unit) and provides less variability of the outcome, when compared to manual kit preparation. The paper reveals several insights about cobotsupported kit preparation that can be valuable for both academics and practitioners. The model developed can be used by practitioners to assess the potential of cobots to support kit-batch preparation in association with assembly, spare parts, repair and maintenance, or business to business industry.

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“…Work supporting CORA and CRCL has taken place in the Agility Performance of Robotics System (APRS) laboratory at the National Institute of Standards and Technology (NIST) [2]. The lab contains two industrial robots, a Fanuc LR-Mate 200iD and a Motoman SIA20F.…”

Section: System Architecturementioning

confidence: 99%

“…We have focused on how to represent the knowledge needed to achieve robot agility, the system architecture and component integration, planning, sensing and control, and how to measure the agility performance of robotic systems [2]. In support of this work, we have relied on simulation as a tool for the development of robotics systems to find ways to make better-informed decisions.…”

Section: Introductionmentioning

confidence: 99%

Virtual Experimental Investigation for Industrial Robotics in Gazebo Environment

Aksu

Michaloski

Proctor

2018

Volume 2: Advanced Manufacturing

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Measuring the agility performance of the industrial robots as they are performing in unstructured and dynamic environments is a thought-provoking research topic. This paper investigates the development of industrial robotic simulation algorithms for the effective application of robots in those changing environments. The distributed framework for this investigation is the Robot Operating System (ROS) which is extensively used in robotic applications. ROS-Industrial (ROS I), which extends the capabilities of ROS to manufacturing, allows us to interoperate between industrial robots, sensors, communication buses and other kinds of automation tools. Gazebo is used as the open-source 3D simulator to design a virtual industrial robotic system, which is a prevailing tool as a node in the ROS environment. An effort is underway to replicate the in-house experimental robotic kitting lab with a graphical physics simulation that can be shared worldwide. This graphical physics simulation is not tied to a specific robotic control system. An experimental approach will be presented detailing the issues related to a physics based simulation of kitting with multiple collaborative robots, multiple tools, parts, tool changers, safety system, and sensors. In this realm, the ability for the simulation environment to encompass the current system as well as additional more complex sensors and actuators will be discussed. To make this simulation environment more realistic, Gaussian noise will be introduced to the data generated by virtual sensors. We expect that this experimental approach will be a seamless way for users to verify and validate their control systems even if they do not have a physical robot at their facilities.

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Enabling robot agility in manufacturing kitting applications

Cited by 17 publications

References 29 publications

A domain-specific modeling approach supporting tool-chain development with Bayesian network models

A domain-specific modeling approach supporting tool-chain development with Bayesian network models

Modelling time efficiency of cobot-supported kit preparation

Virtual Experimental Investigation for Industrial Robotics in Gazebo Environment

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