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Recently, there has been growing interest in composition of cloud manufacturing resources (CMRs). Composition of CMRs is a feasible innovation to fulfill the user request while single cloud manufacturing resource cannot satisfy the functionality required by the user. In this paper, we propose a new case-based approach for the composition of CMRs. The basic idea of the present approach is to provide a computational framework for the composition of CMRs by imitating the common design method of reviewing past designs to obtain solution concepts for a new composite cloud manufacturing resource (CCMR). A notion of virtual cloud manufacturing resource generators (VCMRGs) is introduced to conceptualize and represent underlying CCMRs contained in existing CCMRs. VCMRGs are derived from previous CCMRs and serve as new conceptual building blocks for the composition of CMRs. Feasible composite CMRs are generated by combining VCMRGs using some adaptation rules. The reuse of prior CCMRs is accomplished via VCMRGs within the framework of case-based reasoning. We demonstrate that the proposed approach yields lower execution time for fulfilling user request and shows good scalability.

A multicriteria decision-making model was proposed in order to acquire the optimum one among different product design schemes. VIKOR method was introduced to compute the ranking value of each scheme. A multiobjective optimization model for criteria weight was established. In this model, projection pursuit method was employed to identify a criteria weight set which could keep classification information of original schemes to the greatest extent, while PROMETHEE II was adopted to keep sorting information. Dominance based multiobjective simulated annealing algorithm (D-MOSA) was introduced to solve the optimization model. Finally, an example was taken to demonstrate the feasibility and efficiency of this model.

The disassembly line is the best choice for automated disassembly of disposal products. Therefore, disassembly line should be designed and balanced so that it can work as efficiently as possible. In this paper, a mathematical model for the multi-objective disassembly line balancing problem is formalized firstly. Then, a novel multi-objective ant colony optimization (MOACO) algorithm is proposed for solving this multi-objective optimization problem. Taking into account the problem constraints, a solution construction mechanism based on the method of tasks assignment is utilized in the algorithm. Additionally, niche technology is used to embed in the updating operation to search the Pareto optimal solutions. Moreover, in order to find the Pareto optimal set, the MOACO algorithm uses the concept of Pareto dominance to dynamically filter the obtained non-dominated solution set. To validate the performance of algorithm, the proposed algorithm is measured over published results obtained from single-objective optimization approaches and compared with multi-objective ACO algorithm based on uniform design. The experimental results show that the proposed MOACO is well suited to multi-objective optimization in disassembly line balancing. [ABSTRACT FROM AUTHOR]

In this paper, a new method is developed for tool path planning on triangular mesh surfaces with consideration of the scallop height restriction and the path smoothness. This method first maps the triangular mesh surface into a unit disk region by using a harmonic map algorithm, and then the shortest boundary path graph (SBPG) is constructed on the unit disk region to describe the shortest geodesic distance from each mesh vertex to the surface boundary. The tool path is then obtained by inversely mapping the contours of SBPG from the harmonic mapped region to the physical space of mesh surface. During this process, a subdivision method is used to boost the computing efficiency and a smoothing treatment is conducted on the SBPG to improve the path smoothness. The tool path planning is performed starting from the surface boundary in an iteration process. Taking the level difference of SBPG contours as the initial path interval and being supplemented by a correction process, the maximal step distance between any two paths, which meets the requirement of scallop height restriction, can be determined efficiently. Typical simulation cases and experiments are carried out to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Copyright of Modern Food Science & Technology is the property of Editorial Office of Modern Food Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Authors that the author would like to thank for their assistance in reviewing the articles published in this journal are mentioned including Gerald Aase, Babak Abbasi and Reza Abdi.

In order to rectify the problems that the component reliability model exhibits deviation, and the evaluation result is low due to the overlook of failure propagation in traditional reliability evaluation of machine center components, a new reliability evaluation method based on cascading failure analysis and the failure influenced degree assessment is proposed. A direct graph model of cascading failure among components is established according to cascading failure mechanism analysis and graph theory. The failure influenced degrees of the system components are assessed by the adjacency matrix and its transposition, combined with the Pagerank algorithm. Based on the comprehensive failure probability function and total probability formula, the inherent failure probability function is determined to realize the reliability evaluation of the system components. Finally, the method is applied to a machine center, it shows the following: 1) The reliability evaluation values of the proposed method are at least 2.5% higher than those of the traditional method; 2) The difference between the comprehensive and inherent reliability of the system component presents a positive correlation with the failure influenced degree of the system component, which provides a theoretical basis for reliability allocation of machine center system. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhejiang University: Science A is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)