Journal of Quality Engineering and Management

Abstract Determining the Factors Influencing the Prediction of Helicopter Rotor Failures

Purpose: The purpose of this paper is to investigate and identify the variables that influence the occurrence of helicopter accidents caused by different types of rotor failures. These crucial factors include flight conditions, maintenance conditions, and helicopter configuration. With this approach, accidents can be investigated more effectively and flight safety can be significantly improved.

Methodology: By analyzing 135 rotor faults accident from a comprehensive dataset containing 5652 helicopter-related accidents, eight classes of rotor faults were identified. Based on expert surveys and a review of studies in the field of helicopter accidents, nine features were proposed as crucial factors to such accidents. The significance of these factors was assessed using five feature selection methods. The input features included maximum takeoff weight, flight hours since the last inspection, type of last inspection, engine power, flight hours, altitude, wind speed, wind direction, and flight phase. Five well-known feature selection techniques—Correlation Matrix, Extreme Gradient Boosting (XGBoost), Mutual Information, Deep Learning, and Neural Network—were employed to identify the most essential factors.

Findings: "Maximum weight", "helicopter engine power", "flight phase" and "flight hours" were identified as variables with the highest degree of importance in predicting faults class of helicopter rotor, which also have a strong and acceptable justification in flight mechanics.

Originality/Value: The distinction of the present study from similar works lies in the inclusion of a broader range of variables, such as flight conditions and helicopter configuration, in contrast to previous studies that considered only a limited set of variables. By prioritizing these variables, the findings pave the way for proactive measures to prevent rotor faults, aiming to enhance prediction accuracy, reliability, and flight safety.

Abstract Purpose: Reliability is one of the most critical quality characteristics of components, products, and systems. Unlike other attributes, it cannot be directly measured and is usually evaluated only after significant operational time under real conditions. However, waiting for long-term field data may reduce market competitiveness in commercial industries and pose serious safety risks in sensitive systems such as military equipment. Therefore, reliability prediction plays a vital role in key decision-making areas such as product release timing, warranty policies, and maintenance planning. This study aims to present an integrated model based on accelerated degradation testing and accelerated life testing to predict the lifetime of a turbine engine nozzle under operational conditions.
Methodology: Initially, the ADT was designed and conducted to monitor the degradation trend of the nozzle's critical feature at various temperature and time levels. Using the power-law and Arrhenius acceleration models, acceleration parameters and the activation energy were estimated. Subsequently, the ALT was performed under high-stress thermal conditions using the extracted parameters, and the corresponding failure times were recorded. Finally, by integrating the results of both tests and applying statistical methods such as maximum likelihood estimation and degradation path modeling, the system's lifetime distribution was modeled.
Findings: The implementation of the proposed model on a turbine engine nozzle demonstrated its ability to predict lifetime accurately and to reduce testing time and cost significantly.
Originality/Value: This model introduces a novel analytical framework that systematically combines two testing methods (ADT and ALT), with the output of one serving as input to the other. The proposed approach can be generalized and applied to other critical industrial and defense-related products.

Abstract In this paper, a novel multi objective mathematical programing model is developed which focuses on enhancement of quality of design via optimizing the layout of components in multicomponent systems. The objectives include maximization of accessibility to components, optimization of distance between members based on their positive/negative interaction, maximal maintenance space inclusion around components and minimization of total volume of the system. The structure of the variables and constraints of the model is novel and assorts the formulation of the objectives. As a case study, the model is used to optimize the layout of components of a laser range finder. First, the model is converted to a single objective one via the weighting method and by using the eigenvalue approach. Then, the obtained model is solved via Lingo. Results demonstrate that the solution is close to the ideal solution by 82.7%. Moreover, accessibility (the most important objective) and maintenance distance requirement correspond 100% to their ideal value. 

Abstract The use of a Functional Block Diagram is usually one of the most commonly used methods to estimate the reliability of products. This method is not responsive in many missionoriented complex systems. Because at each stage of each mission, different sections and subsystems work and then stop at different times. This is precisely the problem of this research, which is a mission-centered submarine for rescue.  For this purpose, in this paper, a method for calculating the reliability of this submarine, which has four 9-step subsystems, has been designed and presented. At first, the functions of each stage are extracted from the subsystems (electricity, secondary, radio-electronics and navigation) during the meetings with experts, then a Functional Block Diagram is drawn for each step. In the following, the potential failure states for each function are determined in the form of a Failure Mode and Effect Analysis tool. Also, for risk analysis, the severity-probability matrix and the average RPN number have been used and good suggestions for improving the design presented. Further, calculating the failure rate for each step by Kim formula, we calculated the reliability of each stage of each subsystem. Then, the reliability of each subsystem is computed. Finally, in order to calculate the reliability of the entire submarine, first, the reliability of each step is obtained by multiplying the reliability values of each of the four subsystems in each step, eventually multiplied by the successive steps. According to the calculations, the total submarine reliability in the design stage is approximately 0.6, which is considered by the experts to be reasonable. 
       

Abstract Abstract: In today's competitive world, considering customers' needs and having a proper understanding of them, as the first phase of the conceptual design and development in the life cycle of a system, ensures the success of economic institutions and determines the purpose of the system. In this context, all needs must be considered and correctly interpreted in a continuous interaction with the customer. The correct interpretation of these requirements will result in the creation of two categories of requirements, designated as functional and non-functional requirements. Addressing both of these requirements and their values as well as an eventual assessment of the designs under construction in agreement with these values in the early stages of the life cycle of a system will bring about a reduction in costs and create a customer- oriented system. The purpose of the present study that conducted on a submarine of class H, is to choice the effective conceptual design for design and construction the product using the calculation of the overall measure of effectiveness index and based on the requirements specified in the conceptual design stage. During this research, first, all needs were identified; being interpreted, they were classified into two categories of functional and non-functional requirements. Then, the quantitative values of functional requirements were calculated using experts’ judgments and the quantitative values of nonfunctional requirements were worked out using various methods on the basis of the processes, so, the paired comparison matrix was used to determine the weights of each of the requirements and the effectiveness measure of the proposed designs was determined on the basis of weight and quantitative values of each category of requirements for each the conceptual design. Finally, from the two conceptual designs considered, an effective conceptual design is introduced and introduced to the industry. 

Abstract Abstract: Nowadays, extensive use of computers, networks and the internet in information systems has increased the diversity of information security risks so the management of these risks has been increasingly considered. According to the importance of information security in online research information systems as the main source of future researches, this study applies a hybrid of fuzzy Failure Mode and Effects Analysis (FMEA), analytic hierarchy process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), attempts to optimizely identify, assess and prioritize organization's information security risks. By using fuzzy logic ratings will be more accurate and more transparent, and with the combination of AHP and TOPSIS can measure the weight of the criteria of FMEA and with the calculation closeness coefficient of any risk prioritized each of them. The result to study of application this model in identifying and assessing potential risks of system studied in three main areas: confidentiality, availability and integrity of information, shows risks related to unauthorized access to information and incorrect and lack of integrated information are in the highest priority of the organization's experts.

Abstract The growing need for systems with high availability/reliability has led to numerous studies in recent years on reliability optimization (availability, if the system is repairable). The use of different redundancy policies and adding extra components are generally considered effective ways to increase system availability. When the system is multi-state, due to the computational complexity involved, the methods used to calculate system availability play a crucial role in providing an acceptable solution. This paper aims to minimize costs for multi-state systems under the constraint that system availability must exceed an acceptable threshold. The redundancy allocation problem is modeled as heterogeneous, meaning that components in such a system can differ from one another. Both components and the system can have multiple states. To compute system availability, the Universal Generating Function (UGF) algorithm is employed, and to optimize the system structure, the Genetic Algorithm (GA) is used.

Abstract Reliability is an integral part of the planning, design, and operation of engineering systems, ranging from the smallest and simplest to the largest and most complex. The failure of any system can disrupt the ongoing processes of people and equipment associated with it, which in some cases is considered a serious threat to the community. Therefore, this study first aims to identify all industrial engineering techniques that can be effective in improving reliability and to prioritize these techniques across all phases of the product life cycle using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). Subsequently, using the Interpretive Structural Modeling (ISM), the cause-and-effect relationships among the techniques in each phase are determined, providing a systematic framework to enhance equipment reliability and to understand and develop the relationships between reliability and other industrial engineering techniques.

Abstract One of the common approaches in system reliability optimization is the use of redundant components. It has been proven that the redundant component allocation problem is NP-hard and involves selecting redundant components to optimize system reliability based on pre-defined constraints. In this paper, the maximization of reliability in series-parallel systems is addressed by adding redundant components subject to weight and cost constraints. In the allocation of redundant components, the existence of multiple types for each component is considered, meaning that in addition to determining the number of components, it is also necessary to select the appropriate type from the available options. This problem is modeled as a three-level graph, and an Ant Colony Optimization (ACO) algorithm is employed to solve it. The search capability of the proposed algorithm is enhanced by a local search method in the neighborhood of feasible points, and a dynamic penalty function is used to guide solutions toward feasible regions. The application of this algorithm is demonstrated in optimizing the reliability of a mechanical gearbox system. Numerical results obtained from solving sample problems indicate the considerable efficiency of the proposed algorithm compared to previous approaches, achieving not only the maximization of reliability but also minimizing the required weight and cost.