scholarly journals A Unified Sustainable Manufacturing Capability Model for Representing Industrial Robot Systems in Cloud Manufacturing

2015 ◽  
pp. 388-395
Author(s):  
Xingxing Wu ◽  
Xuemei Jiang ◽  
Wenjun Xu ◽  
Qingsong Ai ◽  
Quan Liu
Keyword(s):  
Industrial Robot ◽  
Sustainable Manufacturing ◽  
Cloud Manufacturing ◽  
Manufacturing Capability ◽  
Robot Systems

Dynamic Manufacturing Capability Assessment of Industrial Robots Based on Feedback Information in Cloud Manufacturing

2017 ◽  
Author(s):  
Zeyu Zhang ◽  
Wenjun Xu ◽  
Quan Liu ◽  
Zude Zhou ◽  
Duc Truong Pham
Keyword(s):  
Manufacturing Industry ◽  
Dynamic Assessment ◽  
Cloud Manufacturing ◽  
Industrial Robots ◽  
Assessment Model ◽  
Advanced Technology ◽  
Distribution Model ◽  
Information Feedback ◽  
Optimal Solutions ◽  
Manufacturing Capability

With the development of information and computer network technology, cloud manufacturing has been developing rapidly, industrial robots (IRs) as a vital symbol and an advanced technology of manufacturing industry, in scheduling service, the constantly changing information data will result in the corresponding vary of the manufacturing capability. Under a fixed constraint of some capability service request, this will decrease the number of the optimal solutions and provide the inaccurate service to users. So it is important to make the manufacturing capability stable and obtain more optimal solutions to satisfy the constraint, thus the dynamic assessment of manufacturing capability based on information feedback is investigated in this paper. A set of indicators is established considering the IRs’ manufacturing capability and a new dynamic assessment model is proposed to achieve the actual data and the expected data information feedback, using the “normal distribution” model, which can correct the assessment weight. By the way, a case study is simulated in the MATLAB, which shows the reliability and reasonability of this method in evaluate the manufacturing capability in IR.

Hierarchical Decomposition of a Manufacturing Work Cell to Promote Monitoring, Diagnostics, and Prognostics

2017 ◽  
Author(s):  
Brian A. Weiss ◽  
Guixiu Qiao
Keyword(s):  
Machine Tools ◽  
Health Management ◽  
Control Strategies ◽  
Industrial Robot ◽  
Work Cell ◽  
Critical Elements ◽  
Functional Relationships ◽  
Manufacturing Operations ◽  
Robot Systems ◽  
And Control

Manufacturing work cell operations are typically complex, especially when considering machine tools or industrial robot systems. The execution of these manufacturing operations require the integration of layers of hardware and software. The integration of monitoring, diagnostic, and prognostic technologies (collectively known as prognostics and health management (PHM)) can aid manufacturers in maintaining the performance of machine tools and robot systems by providing intelligence to enhance maintenance and control strategies. PHM can improve asset availability, product quality, and overall productivity. It is unlikely that a manufacturer has the capability to implement PHM in every element of their system. This limitation makes it imperative that the manufacturer understand the complexity of their system. For example, a typical robot systems include a robot, end-effector(s), and any equipment, devices, or sensors required for the robot to perform its task. Each of these elements is bound, both physically and functionally, to one another and thereby holds a measure of influence. This paper focuses on research to decompose a work cell into a hierarchical structure to understand the physical and functional relationships among the system’s critical elements. These relationships will be leveraged to identify areas of risk, which would drive a manufacturer to implement PHM within specific areas.

Supporting Semantic Capture During Kinesthetic Teaching of Collaborative Industrial Robots

2018 ◽  
Vol 12 (01) ◽  
pp. 167-186 ◽  
Author(s):  
Maj Stenmark ◽  
Mathias Haage ◽  
Elin A. Topp ◽  
Jacek Malec
Keyword(s):  
Domain Knowledge ◽  
Semantic Information ◽  
Industrial Robot ◽  
Semantic Context ◽  
Industrial Robots ◽  
Teaching Mode ◽  
Language Support ◽  
Semantic Data ◽  
Robot Systems ◽  
System Knowledge

Industrial robot systems being deployed today do not contain domain knowledge to aid robot operators in setup and operational use. To gather such knowledge in a robotic context requires mechanisms for entering and capturing semantic data. Such mechanisms would allow a system to gradually build a working vocabulary while interacting with the environment and operators, valuable for the bootstrapping system knowledge and ensuring the data collection over time. This paper presents a prototype user interface that assists the kinesthetic teaching mode of a collaborative industrial robot, allowing for the capture of semantic information while working with the robot in day-to-day use. Two modalities, graphical point-and-click and natural language, support capture of semantic context and the building of a working vocabulary of the environment while modifying or creating robot programs. A semantic capture experiment illustrates the approach.

Modeling of Resources Capability for Manufacturing Equipments in Cloud Manufacturing

2012 ◽  
Vol 271-272 ◽  
pp. 447-451 ◽  
Author(s):  
Yuan Yuan Zhao ◽  
Quan Liu ◽  
Wen Jun Xu ◽  
Lu Gao
Keyword(s):  
Web Service ◽  
Cloud Manufacturing ◽  
Enterprise Group ◽  
Functional Capability ◽  
Manufacturing Equipment ◽  
Service Platform ◽  
Production Capability ◽  
Manufacturing Capability ◽  
Proposed Model ◽  
Functional Attribute

Being a kind of actual resources, manufacturing equipment resources (MERs) need to be virtualized and encapsulated into services. Our proposed works mainly focus on manufacturing capability of MERs that is consisted of two aspects: static functional capability and dynamic production capability, and relationship between related concepts so as to model MERs by ontology web language (OWL) that is based on semantic. In this paper, firstly, ontology based methodology within manufacture field is developed according to cloud manufacturing characters. Secondly, manufacturing capability is studied from functional attribute capability and production capability, then, the related concepts classes and relationship are analyzed, with the special properties defined to describe these classes based on semantic. Thirdly, the built in model is described by OWL (ontology web language) using protégé tool and an instance of MER is built based on the proposed model to express its manufacturing capability. Finally, this model is applied to Cloud MERs service platform, which is constructed for a given enterprise group, to provide MERs services. Moreover, Web Service is used in the platform to realize the sharing of the provided services.

scholarly journals Analysis of flexible supported industrial robot on terminal accuracy

2018 ◽  
Vol 15 (4) ◽  
pp. 172988141879302
Author(s):  
Liping Wang ◽  
Lian Chen ◽  
Zhufeng Shao ◽  
Liwen Guan ◽  
Li Du
Keyword(s):  
Vibration Suppression ◽  
Industrial Robot ◽  
Reaction Force ◽  
Industrial Robots ◽  
High Quality ◽  
Flexible Support ◽  
Performance Requirements ◽  
Large Structures ◽  
Robot Systems ◽  
Motion Range

To meet comprehensive performance requirements of large workspace, lightweight, and low energy consumption, and flexible supported industrial robots emerge, which are usually composed of a six-degrees-of-rotational-freedom (6R) industrial robot and a flexible support. Flexible support greatly expands the motion range of the attached industrial robot. Flexible supported industrial robots have been adopted in surface coating of large structures such as aircrafts and rockets. However, the rigid–flexible coupling exists in these robot systems. When the industrial robot moves, the reaction force and torque of the robot disturb the flexible support and introduce vibration, which may result in the deterioration of the system’s terminal accuracy. This study focuses on both the robot body accuracy and system vibration suppression to improve the terminal accuracy of the flexible supported industrial robot. Firstly, based on kinematics analysis, accuracy of the industrial robot is investigated with the local conditioning index. Then, reaction force and torque ellipsoids are proposed with the deduced dynamic model to evaluate disturbances that the industrial robot applies to the flexible support. Considering these two aspects, the high-quality workspace of the flexible supported industrial robot is established. Numerical simulations show that reaction force and torque are effectively limited in the high-quality workspace, which greatly reduce the vibration energy and improve the terminal accuracy of the system.

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