Part Supply Method for Mixed-Model Assembly Lines with Decentralized Supermarkets

In-house part supply affects the efficiency of mixed-model assembly lines considerably. Hence, we propose a reliable Just-In-Time part supply strategy with the use of decentralized supermarkets. For a given production sequence and line layout, the proposed strategy schedules tow train routing and delivery problems jointly to minimize the number of employed town trains and the traveling time, while ensuring that stations never run out of parts. To solve this problem, a mathematical formulation is proposed for each sub-problem aiming at minimizing supply cost. Then, a dynamic programming algorithm for routing and a greedy algorithm for delivery are developed, both of which are of polynomial runtime. Finally, a computational study is implemented to validate the effectiveness of the strategy, and to investigate the effects of the delivery capacity of tow trains and storage capacity of stations on supply cost.

Real-Time Control for CPS of Digital Airplane Assembly with Robust H-Infinity Theory

This study introduces a real-time controller design method under the effects of network time delay and external disturbance. The study first introduces the digital, virtual, intelligent trend of airplane assembly and reveals the status and problems of digital airplane assembly studies. The Cyber-Physical System （CPS） structure is then proposed for digital airplane assembly, and the real-time control issues are discussed. Then, the question of real- time control undertaken by a parallel robot is simplified to a control question with bounded time delay and complex interference, and a mathematical description is presented. Next, a robust Hoo controller with a disturbance degree of decay 7 is designed according to the mathematical description. Finally, a simulation is conducted. All of the experiment results show the feasibility of the above proposed methods.

A parallel matching algorithm based on order relation for HLA data distribution management

In distribution simulation based on High-level architecture(HLA),data distribution management(DDM)is one of HLA services for the purpose of filtering the unnecessary data transferring over the network.DDM admits the sending federates and the receiving federates to express their interest using update regions and subscription regions in a multidimensional routing space.There are several matching algorithms to obtain overlap information between the update regions and subscription regions.When the number of regions increase sharply,the matching process is time consuming.However,the existing algorithms is hard to be parallelized to take advantage of the computing capabilities of multi-core processors.To reduce the computational overhead of region matching,we propose a parallel algorithm based on order relation to accelerate the matching process.The new matching algorithm adopts divide-and-conquer approach to divide the regions into multiple region bound sublists,each of which comprises parts of region bounds.To calculate the intersection inside and amongst the region bound sublists,two matching rules are presented.This approach has good performance since it performs region matching on the sublists parallel and does not require unnecessary comparisons within regions in different sublists.Theoretical analysis has been carried out for the proposed algorithm and experimental result shows that the proposed algorithm has better performance than major existing DDM matching algorithms.

Unsupervised Dynamic Fuzzy Cognitive Map

Fuzzy Cognitive Map （FCM） is an inference network, which uses cyclic digraphs for knowledge representation and reasoning. Along with the extensive applications of FCMs, there are some limitations that emerge due to the deficiencies associated with FCM itself. In order to eliminate these deficiencies, we propose an unsupervised dynamic fuzzy cognitive map using behaviors and nonlinear relationships. In this model, we introduce dynamic weights and trend-effects to make the model more reasonable. Data credibility is also considered while establishing a machine learning model. Subsequently, we develop an optimized Estimation of Distribution Algorithm （EDA） for weight learning. Experimental results show the practicability of the dynamic FCM model. In comparison to the other existing algorithms, the proposed algorithm has better performance in terms of convergence and stability.

Synergic Motion Trajectory Planning for Airplane Docking Based on6PURU Parallel Mechanism

Motion planning issues encountered in assembling airplanes by employing the 6PURU parallel mechanism are analyzed in this paper. A sine curve of the change rate of acceleration, which is called as jerk in the following text, is proposed for uniaxial flexible acceleration and deceleration planning based on the optimal time and velocity and acceleration constraints. Compared with other curves, the proposed curve can realize a continuous n-order derivative and the smooth change of the speed and acceleration. The method is computational^y simple and suitable for programming. In addition, a multiaxial coordinated movement scheme is proposed. The motion trajectory is no longer simply split into many single-direction trajectories nor are all single-direction planning trajectories combined directly. The multiaxial coordinated movement scheme aims to achieve synergic movement in multiple directions to ensure smoothness of the movement in the event of a kinematic error when maintaining a stable value. If the movement fails to achieve this goal, driving force mutations will deteriorate the effect of synergic movement. A physical model of the parallel mechanism is developed in simMechanics, and a holistic system model is completed in SIMULINK. The feasibility of the new planning algorithm is simulated and tested, and then, the multiaxial synergic movement planning method is proposed and verified.

Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane

This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”to achieve high level intelligent assembly.Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling,respectively.The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation,and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration,it can also directly link to data,and the error is smaller.This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control.A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness.At the same time,an outer collaborative trajectory planning is also designed.All the experiment results show the feasibility of above proposed methods.

A dynamic delivery strategy for material handling in mixed-model assembly lines using decentralized supermarkets

Material handling has become one of the major challenges in modern production management.Consequently,this paper intends to investigate the part delivery of mixedmodel assembly lines with decentralized supermarkets and tow trains.Besides,uncertain exception disturbances,including tow train failures and adjustments of the production sequence,are also considered.To solve this problem,a heuristic-based dynamic delivery strategy is proposed,which dynamically schedules the route,departure time,quantities and types of loaded parts for each tour.To evaluate the performance of this strategy,it is used to solve an instance in comparison with the periodic delivery strategy,experimental results are reported and their performances are compared under different metrics.Moreover,a multi-scenario analysis is employed to determinate the long-term decisions,including the number of tow trains and the route layout.Finally,the critical storage is suggested to be set for each station to avoid part starvation resulting from disturbances,and its effect on the delivery performance is investigated.