In order to resolve the modeling method of logistics network, a basic model named NGM is presented. According to some special characteristics of the real logistics network such as growth, preferential attachment, edge-weighted, and clustering, the basic model is improved and optimized. The modeling method of logistics is analyzed and simulated too. The results of the simulation show that the modeling method is more effective than the traditional logistics modeling theories.
The issue of CNC machine tool energy consumption and environmental protection plays an important role on manufacturing technology research since CNC machine tool energy is consumed during motor racing or cutting process. The paper analyzes CNC machine tool energy consumption influence by cutting parameters of cutting speed, feed speed, cutting depth. Based on nonlinear mapping ability of neural network, the model of CNC machine tool energy consumption related to cutting parameters is established by using experimental data, and then the optimal combination of cutting parameters are searched by using global optimization of genetic algorithm, and verified in CNC machine tool cutting experiment. The proposed method provides a good energy control proposal for CNC machine tool roughing process. The experimental results show that the energy consumption is optimal.
Obtaining the fault information online may eliminate many potential fatal accidents, in order to inspect and resolve the online fault diagnosis problem in process industry, an online fault diagnosis model based on IoT(Internet of Things) is proposed in the paper. the model is composed as four layer of user layer, application layer, basic technology layer and resources layer, and it can use the resources effectively such as virtual organizations, entity organization, equipment, network resources and so on, the basic technologies such as Internet of things, multiple information collection, knowledge engineering and application technologies were analyzed in the paper too. Finally, an application system is developed, and it proved the model is validity and correctness.
The cooperator’s optimal selection is a difficulty in manufacturing supply chains, but the complex networks developed rapid recent year provide us a new method. It proposed a probability distribution model for optimal selecting cooperator in supply chains. Analyzed the growth of Manufacturing Supply Chain Network Relationship Graph (MSCNRG) firstly, and put forward a probability distribution function consisted with degrees, relationships and conditions of the vertices; some experiments were carried out to check the model. The results of probability distribution model provide a novel method to analyze the optimal selecting cooperators in supply chains.
A mechanism that the backoff exponent changes dynamically was proposed aiming at the poor performance of backoff algorithm in IEEE 802.15.4 MAC protocol. The algorithm could adjust the initial backoff exponent according to the previous transmission status and the backoff exponent. A Markov chain model for the algorithm was established and the mathematical derivation for the model was carried out. The theoretical analysis and simulation results show that the model increases the channel access probability and system throughput. The optimized algorithm improves the performance of LOWPAN effectively.
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