浅谈国有企业矿山物质管理信息系统的建立

介绍了基于供应链管理的现代物流信息系统的基本特点 ;结合国有矿山企业当前的物资管理工作实际 ,提出了建立面向供应链的企业物资管理信息系统的基本思路和在建立过程中需要关注和解决的几个重要问题     

农村配电网自动化系统建设模式的研究及应用

阐述了农村配电自动化系统的建设模式、系统配置、主站方案选择与通讯,探讨了系统在配电可靠性、无功优化等方面的应用情况,并提出了利用该系统防止窃电的新技术。     

线路故障与供电可靠性措施探讨

针对西藏中部电网供电可靠性的突出问题，从电力系统内部出发，分析各种故障特性和电气参数的变化，探讨解决问题的途径和方法。     

Decentralised production-distribution planning system using collaborative agents in supply chain network

With the fast development of information technology and the global market, collaboration between different functional units in a supply chain becomes one of the most critical factors for global companies to respond to rapid changes in customer needs and increase the efficiency of the whole supply chain. This supply chain environment requires a production-distribution planning system to enable the collaboration between production and distribution units more quickly and orderly. Generally, collaboration in a supply chain needs to resolve conflicts between two decentralised functional units, because each unit tries to locally minimise its own costs, not the overall supply chain costs. Also, there exists incomplete information sharing according to the information privacy of each functional unit. This paper proposes a decentralised production-distribution planning system using collaborative agents that can efficiently mediate the planning gaps between two decentralised planning functions: production and distribution. The validity of collaborative-agent model has been shown using some lemmas and numerical examples.     

爆炸性气体环境用电气设备的供电电源

本文介绍了防爆电气设备防爆的基本原理和采用的防爆措施。论述了各种形式的防爆电气设备对供电电源的要求,本质安全型防爆电气设备对供电电源的特殊要求,以及本质安全型电气设备的各种供电方式和供电电源的防爆设计。     

Hybrid approach to distribution planning reflecting a stochastic supply chain

Today’s business environment is experiencing as a period of expansion and the globalization. Therefore, a distribution plan with low cost and high customer satisfaction in supply chain management (SCM) has been widely investigated. The purpose of this study is to establish optimal distribution planning in the supply chain. In this paper, a hybrid approach involving a genetic algorithm (GA) and simulation is presented to solve this problem. The GA is employed in order to quickly generate feasible distribution sequences. Considering uncertain factors such as queuing, breakdowns and repairing time in the supply chain, the simulation is used to minimize completion time for the distribution plan. The computational results for an example of a simple supply chain are given and discussed to validate the proposed approach. We obtained a more realistic distribution plan with optimal completion time by performing the iterative hybrid GA simulation procedure which reflects the stochastic nature of supply chains.     

Bi-objective optimization of three echelon supply chain involving truck selection and loading using NSGA-II with heuristics algorithm

This paper models a three echelon supply chain distribution problem considering multiple time periods, multi-products and uncertain demands. To take the problem closer to reality we consider multiple truck types and focus on the truck selection and loading sub-problem. Truck selection is important because the quantity of goods to be transported varies regularly and also because different trucks have different hiring cost, mileage and speed. Truck loading is important when considering the optimal loading pattern of products having different shapes and sizes on trucks, which themselves have distinct loading capacities. The two objectives considered here are the cost and responsiveness of the supply chain. The distribution problem is solved using the non-dominated sorting genetic algorithm (NSGA-II). However, the genetic algorithms compromise the optimality of the sub-problems while optimizing the entire system. But the optimality of truck selection and loading sub-problem is non-compromisable in nature. Hence a heuristic algorithm is used innovatively along with the NSGA-II to produce much better solutions. To make our model more realistic, the distribution chain is modelled as a push–pull based supply chain having multiple time periods and using demand aggregation over time. Using a separate algorithm also gives the advantage of utilizing the difference in nature of the push and pull part of the supply chain by giving every individual truck different objectives. Real life like data is generated and the optimality gap between the heuristic and non-heuristic approach is calculated. A clear improvement in objectives can be seen while using the heuristic approach.     

Frontier-based performance analysis models for supply chain management: State of the art and research directions

Effective supply chain management relies on information integration and implementation of best practice techniques across the chain. Supply chains are examples of complex multi-stage systems with temporal and causal interrelations, operating multi-input and multi-output production and services under utilization of fixed and variable resources. Acknowledging the lack of system’s view, the need to identify system-wide and individual effects as well as incorporating a coherent set of performance metrics, the recent literature reports on an increasing, but yet limited, number of applications of frontier analysis models (e.g. DEA) for the performance assessment of supply chains or networks. The relevant models in this respect are multi-stage models with various assumptions on the intermediate outputs and inputs, enabling the derivation of metrics for technical and cost efficiencies for the system as well as the autonomous links. This paper reviews the state of the art in network DEA modeling, in particular two-stage models, along with a critical review of the advanced applications that are reported in terms of the consistency of the underlying assumptions and the results derived. Consolidating current work in this range using the unified notations and comparison of the properties of the presented models, the paper is closed with recommendations for future research in terms of both theory and application.     

Semiconductor supply planning by considering transit options to take advantage of pre-productions and order cancellations

One of the objectives of supply planning is to find when and how many productions have to be started to minimize total cost. We aim to find the optimum. Base data like the length of transit time are important parameters to plan for the optimum start of production. In this research, we considered two kinds of transit options: normal transit and emergency transit, and we distinguished between planned and executed transit. The decision regarding which transit option to choose for the execution is trivial because emergency is only used when it is needed since normal transit is more cost efficient. However, for planning purpose, it is more difficult to decide which transit option should be used since the uncertainty in demand and supply between plan and execution can allow to plan an emergency transit but to execute the delivery with normal transit, which is a huge benefit in the competitive capital intensive semiconductor industry. If we planned an emergency, we can save inventory and production cost as we can delay the start of production. In contrast, we need pay additional transit cost in case that emergency transit is actually executed. Many characteristics of the semiconductor industry, which might be the front runner for many other industries, are considered in this model such as demand uncertainty, supply uncertainty and economic volatility. In our numerical experiments, we could gain the optimum, depending on each economic situation. Furthermore, we conducted sensitivity analysis of the effect of demand and supply uncertainties on total cost.     

Disruptions management of a supply chain under strategic subsidy policy for the demand-stimulating inventory

This paper introduces a game model of one manufacturer and one retailer with the demand depending on the amount of inventory displayed on the retailer’s shelf. We study coordination mechanisms of the supply chain with the two kinds of disruptions. To coordinate the channel as well as make a profit, the manufacturer needs to augment the wholesale price lever by another, i.e., an inventory-holding cost subsidy to the retailer. We show that the inventory-subsidy contract for disruption(s) situation has its rationality and limitation: from the perspective of feasibility analysis, we find that when the disrupted amount of inventory-holding cost is larger than a certain threshold value, both players can achieve win–win by using inventory-subsidy contract. Otherwise, it may be ineffective. For two-factor disruptions, there are some mutual restraints between the disrupted inventory-holding cost and the disrupted demand when the coordination mechanism is used. We also find that both disruption situations have their own robust scales, in which the manufacturer should not change the original production plan but at the expense of providing a more attractive subsidy scheme to the retailer. Interestingly, some counter-intuitive managerial insights can be observed in robust scales. For example, the market demand increases with the displayed inventory level in the setting of the demand-stimulating inventory. However, the higher the demand, the less displayed inventory level will be in the robust scale.