Yihai He

A fuzzy TOPSIS and Rough Set based approach for mechanism analysis of product infant failure

Root causes identification of product infant failure is nowadays one of the critical topics in product quality improvements. This paper puts forward a novel technical approach for mechanism analysis of product infant failure based on domain mapping in Axiomatic Design and the quality and reliability data from product lifecycle in the form of relational tree. The proposed method could intelligently decompose the early fault symptoms into root causes of critical functional parameters in function domain, design parameters in physical domain and process parameters in process domain successively. More specifically, both qualitative and quantitative attributes of quality and reliability types are considered for solving the root causes weight computation problem of product infant failure, this approach emphasizes the integrated application of artificial intelligence techniques of Rough Set and fuzzy TOPSIS to compute the weight of root causes. In order to enumerate the latent root causes of product infant failure, connotation of product infant failure based on the product reliability evolution model in the life cycle and data integration model of quality and reliability in production based on the extended QR chain are presented firstly. Then, a decomposition method for relational tree of product infant failure is studied based on domains of functional, physical and process in Axiomatic Design. The failure relation weight computation of root causes (nodes of relational tree) is considered as multi-criteria decision making problem (MCDM) by integrated application of Rough Set and fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), which the Rough Set is used to mining the quality data and fuzzy TOPSIS is adopted to model the computation process of failure relation weight. Finally, the validity of the proposed method is verified by a case study of analyzing a car infant failure about body noise vibration harshness complaint, and the result proves that the proposed approach is conducive to improve the intelligent level of root causes identification for complex product infant failure.

Technical decomposition approach of critical to quality characteristics for Product Design for Six Sigma

Product Design for Six Sigma (DFSS) approach is a structural and disciplined methodology driven by critical to quality characteristics (CTQs). How to identify and decompose the CTQs is the kernel part in the DFSS process. Traditional method only depends on the quality function deployment (QFD) matrix to flow down CTQs roughly. The paper puts forward a novel technical approach for CTQs decomposition from customer requirements into critical technical parameters based on the relational tree. Specifically, this approach emphasizes the systematic process and quantitative computation on quality relation weight. In order to specify the object of product DFSS, the connotation and evolution model of CTQs are created first. Then along the product development process, a decomposition measure for relational tree of CTQs is studied based on the functional and physical trees in Axiomatic Design (AD). And the quality relation weight computation of its nodes by means of Rough Set and fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is explored. Finally, an application on a car body noise vibration harshness (NVH) improvement, as an example, is given, and the decomposition process of NVH related with the functional and physical trees as well as its node weights computation algorithm are expounded in detail. Copyright

A technical framework of the taguchi system design method based on axiomatic design and TRIZ

70–80% of product quality is determined in the concept design process, concept design stage has become the “bottleneck” of the lifecycle quality control. Taguchi method is an effective design quality control approach, its focuses are on the parameter and tolerance design, and there is short of technique solution for system design. In this paper, based on the design axiom of Axiomatic Design (AD) and solution to contradictions in Theory of Inventive Problem Solving (TRIZ), a technical framework of Taguchi system design is put forward. The framework is a component of an evaluation method of product scheme based on AD and a solution flow of latent design contradictions based on TRIZ, and thus it can identify and solve the latent coupling defects laid in design scheme. Finally, a typical mechanical product design example is provided to validate the effectiveness and correctness of this technical framework.

Reliability-oriented quality control approach for production process based on RQR chain

Reliability assurance is a series of activities that ensure that the product reliability requirements be realised in a product life cycle. However, as reliability assurance activities are usually only implemented in design and usage, the integration of reliability assurance with quality control in production has not attracted the attention it deserved, thereby hindering production performance improvement to satisfy increasingly stringent customer requirements. To this end, this paper proposes a reliability-oriented quality control framework to integrate quality control and reliability assurance in production according to the principles of total quality management (TQM). Firstly, from the integrated quality and reliability assurance perspective, the RQR chain is proposed to represent the bidirectional relationships among the three basic management objects in a production process, namely, manufacturing system reliability (R), manufacturing process quality (Q), and the produced product reliability (R). Secondly, a reliability-oriented quality control framework for the production process based on the RQR chain is presented to provide the control clue for a manufacturing enterprise. Thirdly, the validity of the proposed approach is verified in a vehicle engine manufacturing enterprise of China. The proposed RQR chain as a decision-support model for TQM is eventually proven effective in promoting the integration of quality control and reliability assurance in production.

Reliability Modeling and Optimization Strategy for Manufacturing System Based on RQR Chain

Accurate and dynamic reliability modeling for the running manufacturing system is the prerequisite to implement preventive maintenance. However, existing studies could not output the reliability value in real time because their abandonment of the quality inspection data originated in the operation process of manufacturing system. Therefore, this paper presents an approach to model the manufacturing system reliability dynamically based on their operation data of process quality and output data of product reliability. Firstly, on the basis of importance explanation of the quality variations in manufacturing process as the linkage for the manufacturing system reliability and product inherent reliability, the RQR chain which could represent the relationships between them is put forward, and the product qualified probability is proposed to quantify the impacts of quality variation in manufacturing process on the reliability of manufacturing system further. Secondly, the impact of qualified probability on the product inherent reliability is expounded, and the modeling approach of manufacturing system reliability based on the qualified probability is presented. Thirdly, the preventive maintenance optimization strategy for manufacturing system driven by the loss of manufacturing quality variation is proposed. Finally, the validity of the proposed approach is verified by the reliability analysis and optimization example of engine cover manufacturing system.

Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis

Predictive maintenance (PdM) is an effective means to eliminate potential failures, ensure stable equipment operation and improve the mission reliability of manufacturing systems and the quality of products, which is the premise of intelligent manufacturing. Therefore, an integrated PdM strategy considering product quality level and mission reliability state is proposed regarding the intelligent manufacturing philosophy of ‘prediction and manufacturing’. First, the key process variables are identified and integrated into the evaluation of the equipment degradation state. Second, the quality deviation index is defined to describe the quality of the product quantitatively according to the co-effect of manufacturing system component reliability and product quality in the quality–reliability chain. Third, to achieve changeable production task demands, mission reliability is defined to characterise the equipment production states comprehensively. The optimal integrated PdM strategy, which combines quality control and mission reliability analysis, is obtained by minimising the total cost. Finally, a case study on decision-making with the integrated PdM strategy for a cylinder head manufacturing system is presented to validate the effectiveness of the proposed method. The final results shows that proposed method achieves approximately 26.02 and 20.54% cost improvement over periodic preventive maintenance and conventional condition-based maintenance respectively.

Modelling infant failure rate of electromechanical products with multilayered quality variations from manufacturing process

The optimisation of product infant failure rate is the most important and difficult task for continuous improvement in manufacturing; how to model the infant failure rate promptly and accurately of the complex electromechanical product in manufacturing is always a dilemma for manufacturers. Traditional methods of reliability analysis for the produced product usually rely on limited test data or field failures, the valuable information of quality variations from the manufacturing process has not been fully utilised. In this paper, a multilayered model structured by ‘part-level, component-level, system-level’ is presented to model the reliability in the form of infant failure rate by quantifying holistic quality variations from manufacturing process for electromechanical products. The mechanism through which the multilayered quality variations affect the infant failure rate is modelled analytically with a positive correlation structure. Furthermore, an integrated failure rate index is derived to model the reliability of electromechanical product in manufacturing by synthetically incorporating overall quality variations with Weibull distribution. A case study on a control board suffering from infant failures in batch production is performed. Results show that the proposed approach could be effective in assessing the infant failure rate and in diagnosing the effectiveness of quality control in manufacturing.

Product Reliability Oriented Design Scheme of Control Chart Based on the Convergent CEV for Censored Characteristics

Since the censored characteristics are unmonitored effectively in the manufacturing process, the produced product tends to have an unexpected high infant failure rate. Thus, this paper analyzes the associated relationship between product reliability and censored quality characteristics in manufacturing process firstly, and the dynamic and universal control demands for censored characteristics are presented. In view that traditional CEV-based control charts are usually confined to some specific types when dealing with censored characteristics, which greatly restrict the wide application of censored control charts in the high-quality manufacturing process, the convergent CEV technique based on the principle of asymptotic reduction is proposed to be better applied in the analysis of censored characteristics. And novel design procedures and simple but practical performance indicator in the form of the most dangerous alarm distance for censored characteristics of Weibull distribution are put forward. Finally, the validity of the proposed method is verified by a case study of monitoring a censored characteristic relative to lifetime of some aeronautical bearings, and the result proves that the sensitivity of the proposed control chart increased 79.96% compared to traditional CEV chart and is proved to be applicable to monitoring mixed censored characteristics affecting product reliability in manufacturing process.

A New Statistical High‐Quality Process Monitoring Method: The Counted Number Between Omega‐Event Control Charts

Control chart techniques for high-quality process have attracted great attention in modern precision manufacturing. Traditional control charts are no longer applicable because of high false alarm rate. To solve this problem, in this article a new statistical process monitoring method, the counted number between omega-event statistical process control charts, abbreviated as CBΩ charts, is proposed. The phrase omega event denotes that one observation falls into some certain interval and the CBΩ chart is to monitor the number of consecutive parts between successive r omega events. On the basis of CBΩ charts, a dual-CBΩ monitoring scheme is developed. This scheme sets up two CBΩ charts with symmetrical omega events, (μu2009+u2009ςσ,u2009+u2009∞) and (−u2009∞,u2009μu2009−u2009ςσ), respectively. The performance of CBΩ charts and dual-CBΩ monitoring is investigated. Dual-CBΩ monitoring has shown its capability in detecting both mean and variance shift and convenience in implementation compared with other traditional charts. Dual-CBΩ monitoring can reduce false alarm rate greatly without introducing an unacceptable loss of sensitivity in detecting out-of-control signals in high-quality process control. Copyright

Reliability modeling of manufacturing systems based on the task network evolved by key quality characteristics

With the increasing requirements of product reliability and complexity of manufacturing system, the limitation of traditional reliability analysis of manufacturing systems neither considered product quality, nor the weight of key stations. Therefore, aiming at improving the product reliability, a reliability modeling of manufacturing systems based on the task network evolved by key quality characteristics is presented. Firstly, to identify the key task nodes of manufacturing system, the relationship between manufacturing system and product reliability was established in view of axiomatic design (AD), and the task network model evolved by product key quality characteristics was proposed based on axiomatic design theory successively. Then the reliability analysis model of manufacturing systems was put forward based on the capacity and failure rate of the key task nodes. Finally, a reliability analysis case of a piston ring machining system is given to verify the availability of the model.