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The method for aircraft unit fault diagnosis, which is based on the self‐organising feature map (SOM) artificial neural net and expertise, has been presented in this paper. A fault probability of components, of which an aircraft unit is comprised, is generated by the SOM. The qualitative possibilities that the components of a specific unit may cause a failure were estimated by an expert in natural language. It was converted into numeric value by means of Zadeh's fuzzy logic. Both the fault probability and the expertise value of the specific components have been considered in this method based on SOM too. The technical feasibility of this method has been shown by the example. The method is useful when a model based on the First Principles or a causal model of a diagnostic object is not available. It is also applicable to the fault diagnosis of other complicated electromechanical equipments.

The objective of this paper is to develop an expert system according to the features of the fault diagnosis for modern commercial aircraft, which is based on case based reasoning and fuzzy logic. The development strategy of this kind of expert system is illustrated by the development process of an A340 fault diagnostic expert system. The key technology, which is involved in the system, is discussed, such as the construction of case base, the structure of indexes, the algorithm of retrieval and the management of case base.

Maintenance disassembly that involves separating failed components from an assembly or system plays a vital role in line maintenance of civil aircraft, and it is necessary to have an effective and optimal sequence planning in order to reduce time and cost in maintenance. The purpose of the paper is to develop a more effective disassembly sequence planning method for maintenance of large equipment including civil aircraft systems.

The methodology involves the following steps: a component‐fastener graph is built to describe the equipment in terms of classifying components into two categories that are functional components and fasteners; interference matrix is developed to determine the removable component, and a disassembly sequence planning of functional components is proposed based on Dijkstra's algorithm; the disassembly sequence planning including fasteners is presented based on particle swarm optimization.

An application case, which takes the nose landing gear system of a regional jet as a study object, shows that the disassembly sequence planning method proposed in the paper can reduce the calculation complexity greatly, and its effectiveness is greater than that of a genetic algorithm‐based method, in most situations.

The method proposed herein can acquire the optimal maintenance disassembly sequence, which can reduce the cost and time for maintenance of large equipment.

A novel and effective disassembly sequence planning solution for maintenance of large equipment is presented, which can be applied to the line maintenance of civil aircraft.

Direct maintenance costs (DMC) of commercial aircraft make a significant contribution to an aircraft's cost of ownership. The aim of our research is to find out some methods to reduce DMC. The paper first points out that design and fault diagnosis are the key factors to influence DMC, disregarding factors unique to a particular airline. A new concept of R&M design – maintenance free operating period and fault diagnosis expert system are discussed in this paper, in order to reduce DMC.

The purpose of this paper is to analyze parameters that influence direct maintenance cost (DMC) in the civil aircraft operational phase. Reducing direct maintenance cost of civil aircrafts is one of the important ways to improve economy. DMC prediction can provide decision support for the optimization of the design parameters optimization to realize the objection in decreasing the maintenance cost, and it can also improve the aircraft competitiveness.

The paper analyzes some parameters comprehensively, which influence DMC in the civil aircraft’s operational phase. Based on the analysis of the influential parameters and the characteristics of data in the period of civil aircraft’s designing period, the paper presents prediction support method based on fuzzy support vector machine (FSVM) and realizes quantitative forecast of DMC in the aircraft design phase.

The paper presents the process of DMC analysis and model in the aircraft design phase, the DMC prediction model is used in newly developed aircrafts.

The numerical examples using B737NP fleet data in the paper have proved the effectiveness of the proposed method.

The paper establishes the prediction model of civil aircraft DMC based on FSVM. The model can handle fuzzy data and small sample data which contain noise. The results prove that the method can satisfy the demand of the real data in civil aircraft designing.

The purpose of this paper is to provide a new approach involving guidelines and supporting techniques that guarantees all needed space for appropriate product maintenance.

The approach is based on two major areas: field survey to understand how maintainability parameter is applied and converge theory and practice into a systematic space claim method using computer-aided design (CAD) systems to assure proper maintenance procedures at design stages.

Case studies from a truck industry conducted following the proposed approach contrast the savings that can be achieved by using a proper space claim for aftermarket needs against an unsuitable level of participation by maintenance personnel during the design development.

This approach is highly dependent on maintenance experts with suitable skills on CAD systems.

Products developed according to the approach envisaged can result in following aspects: lower repair time, better maintenance procedures on key components, easier preventive maintenance, less need for special tools, more ergonomic design, better communication between design and service engineers, simplicity and less complex training.

Further research on maintainability will provide new information on how to apply this parameter on product development process (PDP), so design teams can better understand and address this relevant issue. The proposed method has been introduced in the PDP of a major multinational automotive company.

A new process is presented, considering the protection of needed spaces for maintenance procedures throughout the PDP, diverging to other studies that only propose analysis addressing maintainability at singular point in time during the product development. In just one case study presented, savings of US$1.3m were achieved by applying this space claim approach.