scholarly journals Dynamic and unified modelling of sustainable manufacturing capability for industrial robots in cloud manufacturing

2017 ◽  
Vol 93 (5-8) ◽  
pp. 2753-2771 ◽  
Author(s):  
Yuanyuan Zhao ◽  
Quan Liu ◽  
Wenjun Xu ◽  
Xingxing Wu ◽  
Xuemei Jiang ◽  
...  
Author(s):  
Zeyu Zhang ◽  
Wenjun Xu ◽  
Quan Liu ◽  
Zude Zhou ◽  
Duc Truong Pham

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.


2012 ◽  
Vol 271-272 ◽  
pp. 447-451 ◽  
Author(s):  
Yuan Yuan Zhao ◽  
Quan Liu ◽  
Wen Jun Xu ◽  
Lu Gao

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.


2014 ◽  
Vol 624 ◽  
pp. 687-693
Author(s):  
Pei Zhi Liu ◽  
Jun Ji ◽  
Wei Yan Chai ◽  
Xiao Chuan Zhao

To realize sharing and synergy between manufacturing resources and manufacturing capability in cloud manufacturing, the manufacturing service model is divided into function model and non-function model. Elements and description of function model is given, and function model determines manufacturing services’ combination planning. Also the composition of non-function model and each part’s weight is presented, and non-function model is the basis to evaluate the priority of manufacturing services. For the case of resource in cloud manufacturing services, sharing ontology and private ontology are researched. Sharing ontology is common description of the whole manufacturing domain, and private ontology is individual description of a specific manufacturing platform. The transformation between sharing ontology and private ontology provides a way for isomerism resources to invoke each other.


Author(s):  
Z.M. Bi ◽  
Yanfei Liu ◽  
Blane Baumgartner ◽  
Eric Culver ◽  
J.N. Sorokin ◽  
...  

Purpose The purpose of this paper is to illustrate the importance of redesigning, reusing, remanufacturing, recovering, recycling and reducing (6R) to sustainable manufacturing and discuss the general procedure to reconfigure robots. Two critical challenges in adopting industrial robots in small and medium-sized enterprise (SMEs) are flexibility and cost, as the number of tasks of the same type can be limited because of the size of an SME. The challenges can be alleviated by 6R. The 6R processes allow a robot to adopt new tasks, increase its utilization rate and reduce unit costs of products. Design/methodology/approach There is no shortcut to implement sustainable manufacturing. All of the manufacturing resources in a system should be planned optimally to reduce waste and maximize the utilization rates of resources. In this paper, modularization and reconfiguration are emphasized to implement 6R processes in sustainable manufacturing; robots are especially taken into consideration as core functional modules in the system. Modular architecture makes it feasible to integrate robots with low-cost customized modules for various tasks for the high utilization rates. A case study is provided to show the feasibility. Findings Finding the ways to reuse manufacturing resources could bring significant competitiveness to an SME, in the sense that sophisticated machines and tools, such as robots, can be highly utilized even in a manufacturing environment with low or medium product volumes. The concepts of modularization and 6R processes can be synergized to achieve this goal. Research limitations/implications The authors propose the strategy to enhance the utilization rates of core manufacturing resources using modular architecture and 6R practice. The axiomatic design theory can be applied as the theoretical fundamental to guide the 6R processes; however, a universal solution in the implementation is not available. The solutions have to be tailored to specific SMEs, and the solutions should vary with respect to time. Practical implications To operate a sustainable manufacturing system, a continuous design effort is required to reconfigure existing resources and enhance their capabilities to fulfill new tasks in the dynamic environment. Social implications The authors focus on the importance of sustainable manufacturing to modern society, and they achieve this goal by reusing robots as system components in different applications. Originality/value Sustainable manufacturing has attracted a great deal of attention, although the operable guidance for system implementation is scarce. The presented work has thrown some light in this research area. The 6R concept has been introduced in a modular system to maximize the utilizations of critical manufacturing resources. It is particularly advantageous for SMEs to adopt sophisticated robots cost-effectively.


Author(s):  
Jiayi Liu ◽  
Wenjun Xu ◽  
Jiaqiang Zhang ◽  
Zude Zhou ◽  
Duc Truong Pham

Cloud Robotics (CR) is the combination of Cloud Computing and Robotics, which encapsulate resources related with robots as services and is also the robotics’ next stage of development. Under this background, due to the characteristics of convenient access, resource sharing and lower costs, industrial cloud robotics (ICR) is proposed to integrate the industrial robots resources in the worldwide to provide ICR services in worldwide. ICR also plays an important role in improving the productivity of manufacturing. In the manufacturing field, Cloud Manufacturing (CM) and Sustainable Manufacturing (SM) is the developing orientation of future manufacturing industry. The energy consumption optimization of ICR is the crucial issue for manufacturing sustainability. However, currently, ICR systems are not programmed efficiently, which leads to the increase of production costs and pollutant emissions. Thus, it is an actual problem to optimize the energy consumption of ICR. In this paper, in order to achieve the goal of energy consumption optimization in worldwide range, the framework of ICR towards sustainable manufacturing is presented, as well as its enabling methodologies, and it is used to support energy consumption optimization services of ICR in the Cloud environment. This framework can be used to support energy-efficient services related with ICR to realize sustainable manufacturing in the worldwide range.


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