Optimal oppor tunistic maintenance model of multi-unit systems

An opportunistic maintenance model is presented for a continuously deteriorating series system with economical de-pendence. The system consists of two kinds of units, which are respectively subjected to the deterioration failure described by Gamma process and the random failure described by Poisson process. A two-level opportunistic policy defined by three decision parameters is proposed to coordinate the different maintenance actions and minimize the long-run maintenance cost rate of the system. A computable expression of the average cost rate is established by using the renewal property of the stochastic process of the maintained system state. The optimal values of three deci- sion parameters are derived by an iteration approach based on the characteristic of Gamma process. The behavior of the proposed policy is illustrated through a numerical experiment. Comparative study with the widely used corrective maintenance policy demonstrates the advantage of the proposed opportunistic maintenance method in significantly reducing the maintenance cost. Simultane- ously, the applicable area of this opportunistic model is discussed by the sensitivity analysis of the set-up cost and random failure rate.     

OPTIMAL MAINTENANCE AND REPLACEMENT OF EXTRACTION MACHINERY

This paper considers a problem of optimal preventive maintenance and replacement schedule of equipment devoted to extracting resources from known deposits. Typical examples are oil drills, mine shovels, etc. At most one replacement of the existing machinery by a new one is allowed. The problem is formulated as an optimal control problem subject to the state constraint that the remaining deposit at any given time is nonnegative. We show that the optimal preventive maintenance, production rates, and the replacement and salvage times of the existing machinery and the new one, if required, can be obtained by solving sequentially a series of free-end-point optimal control problems. Moreover, an algorithm based on this result is developed and used to solve two illustrative examples.     

Collaborative optimization of maintenance and spare ordering of continuously degrading systems

A collaborative optimization model for maintenance and spare ordering of a single-unit degrading system is proposed in this paper based on the continuous detection. A gamma distribution is used to model the material degradation. The degrading decrement after the imperfect maintenance action is assumed as a random variable normal distribution. This model aims to obtain the optimal maintenance policy and spare ordering point with the expected cost rate within system lifecycle as the optimization objective. The rationality and feasibility of the model are proved through a numerical example.     

Inspection interval optimization for aircraft composite structures with dent and delamination damage

The optimization of inspection intervals for composite structures has been proposed,but only one damage type,dent damage,has been addressed so far.The present study focuses on the two main damage types of dent and delamination,and a model for optimizing the inspection interval of composite structures is proposed to minimize the total maintenance cost on the premise that the probability of structure failure will not exceed the acceptable level.In order to analyze the damage characteristics and the residual strength of the composite structure,the frequency,energy,size,and depth of the damage are studied,and the situation of missing detection during the inspection is considered.The structural residual strength and total maintenance cost are quantified corresponding to different inspection intervals.The proposed optimization method relieves the constraints in previous simulation methods,and is more consistent with the actual situation.Finally,the outer wing of aircraft is taken as an example,and with the historical cases and experimental data,the optimization method is verified.The optimal inspection interval is shorter than the actually implemented inspection interval,and the corresponding maintenance cost is reduced by 23.3%.The result shows the feasibility and effectiveness of the proposed optimization method.     

Optimization in Data Cube System Design

The design of an OLAP system for supporting real-time queries is one of the major research issues．One approach is to use data cubes，which are pre-computed multidimensional views of data in the data warehouse．An initial set of data cubes can be derived．from which the answer to each frequently asked query can be retrieved directly．However，there are two practical problems concerning the design of a cube based system：1)the maintenance cost of the data cubes，and 2)the query cost to answer a selected set of frequently asked queries．Maintaining a data cube requires disk storage and CPU computation，So the maintenance cost is related to the total size of the data cubes materialized，and thus keeping all data cubes is impractical．The total size of cubes may be reduced by merging some cubes．However，the resulting larger cubes will increase the query cost of answering some queries．If the bounds on maintenance cost and query cost are strict．some of the queries need to be sacrificed．An optimization problem in data cube system design has been defined．With a maintenance-cost bound and a query-cost bound given by the user，it is necessary to opti-mize the initial set of data cubes such that the system can answer a maximum number of queries and satisfy the bounds．This is an NP-complete problem．Approximate algorithms Greedy Removing(GR)and 2-Greedy Merging with Multiple paths(2GGM)are proposed．Experiments have been done on a census database and the results show that our approach in both effbctive and efficient.     

Flocking of multi-robot systems with connectivity maintenance on directed graphs

Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields （APF） which could guarantee the connectivity maintenance, col ision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved, and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that al robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.     

Design and pricing of maintenance service contract based on Nash non-cooperative game approach

Nowadays manufacturers are facing fierce challenge.Apart from the products, providing customers with multiple maintenance options in the service contract becomes more popular, since it can help to improve customer satisfaction, and ultimately promote sales and maximize profit for the manufacturer.By considering the combinations of corrective maintenance and preventive maintenance, totally three types of maintenance service contracts are designed. Moreover, attractive incentive and penalty mechan...     

Optimal maintenance decisions for gamma deteriorating systems

An optimal replacement model for gamma deteriorating systems is studied.This methodology uses a gamma distribution to model the material degradation,and the impact of imperfect maintenance actions on the system reliability is investigated.The state of a degrading system immediately after the imperfect maintenance action is assumed as a random variable and the maintenance time follows a geometric process.A maintenance policy(N) is applied by which the system will be repaired whenever it experiences Nth preventive maintenance(PM),and an optimal policy(N) could be determined numerically or analytically for minimizing the long-run average cost per unit time.Finally,a numerical example is presented to demonstrate the use of this policy.     

Research of intelligence data mining based on commanding decision-making

In order to rapidly and effectively meet the informative demand from commanding decision-making, it is important to build, maintain and mine the intelligence database. The type, structure and maintenance of military intelligence database are discussed. On this condition, a new data-mining arithmetic based on relation intelligence database is presented according to the preference information and the requirement of time limit given by the commander. Furthermore, a simple calculative example is presented to prove the arithmetic with better maneuverability. Lastly, the problem of how to process the intelligence data mined from the intelligence database is discussed.     

HOW ARE PRODUCT-SERVICE COMBINED OFFERS PROVIDED IN GERMANY AND ITALY？ ANALYSIS WITH COMPANY SIZES AND COUNTRIES

A new business concept that offers products and services in a different way of traditional product-sales businesses is getting more attention especially in manufacturing industries. This paper investigates how this new business by means of integration of products and services is achieved in Germany and Italy. In addition, it analyzes the differences according to the company sizes. The results include that this type of business is in many cases motivated by their focus on customers and often consists of physical products and their maintenance. The Italian companies, as opposed to the German ones, often design their physical products specifically for this type of offers. From the analysis based on the size difference, small companies are found to achieve specific design for this type of offers while owning physical products. There do not seem to be any established methods or tools developed to support the development of such offers and within such methods/tools there would be room for more adaptation in form of physical product design.     

装甲装备月份维修计划优化制订方法研究

分析装甲装备月份维修计划的制订目前存在的问题,通过研究任务与装甲装备月份维修计划之间的相关关系,提出了根据任务的强度确定维修时机为优化目标的维修计划优化模型,统筹考虑维修资源、规章制度等因素。经LINGO软件仿真验证,结果显示该模型能够极大化装备的使用效益,实现科学化、精确化的送修,以及对装备的集约化管理。

Abstract：

The problems were analyzed that lay in the formulation of the armored equipment month maintenance plan. Based on researches about the relationship between the mission and the month maintenance plan, a maintenance plan optimization formulation model was brought forward. The model took factors such as maintenance resources, rules and regulations into overall consideration, and selected maintenance opportunity based on the strength of the mission as optimization goal. The model was validated by LINGO simulation. The result shows that the model can not only maximize the use efficiency, but also realize the scientific and precise delivery and the intensive management of the equipment which needs preventive maintenance.     

Condition-Based Spare Ordering Model for a Two-Stage Degrading System

Proper supply of spares is critical to guarantee safe operation,improve service quality and reduce maintenance costs.This paper proposes a condition-based spare ordering model for a two-stage degrading system,which consists of inflection point transfer process and two-stage degradation process with continuous degradation process and random external shocks.External shocks itself does not directly lead to system failure,but it will speed up the degradation process.In turn,degradation can also make the system more vulnerable to shocks.In general,the degradation rate at the defective stage is greater than that at the normal stage.The proposed model depends on system degradation process and spare lead-time.In order to achieve accurate maintenance and deal with emergency maintenance caused by system rapid degradation after inflection point transfer time,the model considers both the regular lead-time and expedited lead-time.Before inflection point transfer time,regular spare ordering policy is performed.After inflection point transfer time,expedited spare ordering policy is implemented.The decision variable of the model is the ordering time.The objective of this study is to determine the optimal ordering time such that the expected cost rate is minimized.Finally,a numerical example is presented to illustrate the proposed model and sensitivity analysis on critical parameters is carried out.     

Re-engineering transformer maintenance processes to improve customized service delivery

The outage of a transformer in a power generation system will generally result in a shutdown of the entire system.Consequentially,large amounts of revenue are lost to the plant owner with a substantial negative impact on the civil community and industrial customers.This paper analyzes the current maintenance practices(i.e.,an as-is process model) of a transformer manufacturing company,which provides maintenance services to power generation plants and reports the major weaknesses in current business pract...     

Research on knowledge acquisition method about the IF/THEN rules based on rough set theory

The basic principles of IF/THEN rules in rough set theory are analyzed first, and then the automatic process of knowledge acquisition is given. The numerical data is qualitatively processed by the classification of membership functions and membership degrees to get the normative decision table. The regular method of relations and the reduction algorithm of attributes are studied. The reduced relations are presented by the multi-representvalue method and its algorithm is offered. The whole knowledge acquisition process has high degree of automation and the extracted knowledge is true and reliable.     

A NEW CHARACTERIZATION OF NBU CLASS OF LIFE DISTRIBUTIONS WITH APPLICATION

Assume an unreliable workstation performing jobs with a random service time, namely, it occasionally breaks down because of unexpected interruptions. As an interruption really occurs, the station is instantaneously repaired and the uncompleted job is restarted again from the beginning till a job is completed without being interrupted. The total service time is shown to be NBU if and only if the total time it takes to finish each job with interruptions is stochastically larger than that without them, irrespective of when and how the breakdowns occur. As an application, a nonparametric procedure is developed to test for the strict NBU property of the service time. Finally, some numerical simulations are presented as well.     

The conditional diagnosability of shuffle-cubes

<正> In the application of multiple-processor systems some processors or links in a system maynot function properly,thus the fault diagnosis is one of the most important issues in the analysisand maintenance of those systems.For the practical fault diagnosis systems,the probability that allneighboring processors of a processor are faulty simultaneously is very small.Thus,the conditionaldiagnosability,which is a new metric for evaluating such systems,assumes that every fault set doesnot contain all neighbors of any processor in the system.In this paper,the authors show that then-dimensional shuffle-cube has the conditional diagnosability of 4n-15 for n = 2 (mod 4) and n ≥ 10.     

SYNTHESIZED EXPECTED BAYESIAN METHOD OF PARAMETRIC ESTIMATE

This paper develops a new method of parametric estimate, which is named as "synthesized expected Bayesian method". When samples of products are tested and no failure events occur, the definition of expected Bayesian estimate is introduced and the estimates of failure probability and failure rate are provided. After some failure information is introduced by making an extra-test, a synthesized expected Bayesian method is defined and used to estimate failure probability, failure rate and some other parameters in exponential distribution and Weibull distribution of populations. Finally, calculations are performed according to practical problems, which show that the synthesized expected Bayesian method is feasible and easy to operate.     

Rough function model and rough membership function

Two pairs of approximation operators, which are the scale lower and upper approximations as well as the real line lower and upper approximations, are defined. Their properties and antithesis characteristics are analyzed. The rough function model is generalized based on rough set theory, and the scheme of rough function theory is made more distinct and complete. Therefore, the transformation of the real function analysis from real line to scale is achieved. A series of basic concepts in rough function model including rough numbers, rough intervals, and rough membership functions are defined in the new scheme of the rough function model. Operating properties of rough intervals similar to rough sets are obtained. The relationship of rough inclusion and rough equality of rough intervals is defined by two kinds of tools, known as the lower （upper） approximation operator in real numbers domain and rough membership functions. Their relative properties are analyzed and proved strictly, which provides necessary theoretical foundation and technical support for the further discussion of properties and practical application of the rough function model.     

Data driven modeling for power transformer lifespan evaluation

Large sized power transformers are important parts of the power supply chain. These very critical networks of engineering assets are an essential base of a nation＇s energy resource infrastructure. This research identifies the key factors influencing transformer normal operating conditions and predicts the asset management lifespan. Engineering asset research has developed few lifespan forecasting methods combining real-time monitoring solutions for transformer maintenance and replacement. Utilizing the rich data source from a remote terminal unit （RTU） system for sensor-data driven analysis, this research develops an innovative real-time lifespan forecasting approach applying logistic regression based on the Weibull distribution. The methodology and the implementation prototype are verified using a data series from 161 kV transformers to evaluate the efficiency and accuracy for energy sector applications. The asset stakeholders and suppliers significantly benefit from the real-time power transformer lifespan evaluation for maintenance and replacement decision support.     

An Analysis of Suburban Agricultural Land Allocation System and Sustainable Development Strategy──Taking Kaifeng Suburban as an example

\\burban agricu1tural land use is an open regional natural--human system, whichconsists of cropland, forest1and, garden plot, grassland, water body etc. It has a closeexchange of matter and energy with the external environment, and is dominated by humanactivities and limited by natural resources situation. The maintenance of system depends, on both the natural import of sunlight, air, heat, rainfall, creatures, and the humaneinput of agricultural productive resources including labor force, capi…