Jiaming Cui

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.

Big data oriented root cause identification approach based on Axiomatic domain mapping and weighted association rule mining for product infant failure

Abstract Product infant failure formation mechanism is a maze that remains unclear to most manufacturers. Root cause analysis is an important and challenging task in exploring this mechanism in the era of quality and big data. Therefore, a novel big data oriented root cause identification approach based on weighted association rule mining (WARM) is proposed in this paper. First, the mechanism is expounded based on big data in the product lifecycle, and the requirements of root cause identification are determined simultaneously. Second, in view of domain mapping theory in Axiomatic design, the associated tree is proposed to provide a framework for the root cause search and identification. Then, the big data of root causes is defined based on the proposed associated tree. Third, a root cause mining technique using the WARM is presented, and the weight computation approach for the node on the associated tree based on the weight confidence is provided. Finally, the validity of the proposed method is verified by a case study on mining root causes for severe infant failure of an automatic washing machine. The final result shows that the proposed approach is conducive to heuristically identify the root causes of the complicated product infant failure from the big data of product lifecycle.

Health prognosis approach for manufacturing systems based on quality state task network

Previous studies on health prognosis are exceedingly dependence on the failure data and sensor data of a single component of manufacturing systems, and the holistic health prognosis techniques applicable to whole manufacturing systems still remain a challenge due to its increasingly physical and functional complexity. Therefore, a generalized health prognosis method is presented based on the deep fusion of quality-oriented big data of operational process of manufacturing systems. First, the generalized connotation of manufacturing system health is explained from the aspects of the physical composition and functional characteristics of manufacturing systems, and the quality state task network is proposed to organize quality-oriented big operational data, which improve the state transparency of the manufacturing system and lay the foundation of holistic health prognosis. Second, key characterization parameters in quality state task network are defined. Specifically, the performance state is analyzed based on multistate characteristics by considering the effects of stochastic degradation processes; the product quality state is quantified by using a process model that is established based on monitoring and inspection data; and the task execution state is quantitatively described by analyzing the evolution of task demand among machines. Third, an integrated model is built by integrating the three above-mentioned states as two key indicators, namely, qualified degree and mission reliability, for the comprehensive prognosis of the health of manufacturing systems. Finally, the effectiveness of the proposed approach is verified with a case study on the health prognosis of a cylinder head manufacturing system.

Mission reliability modeling for multi-station manufacturing system based on Quality State Task Network

Multi-state-oriented mission reliability modeling is the premise of intelligent scheduling and predictive maintenance for the multi-station manufacturing system. Previous studies on reliability modeling for manufacturing system could only provide a static reliability model based on the basic reliability of the components of manufacturing systems, which cannot support reliability-oriented production scheduling and preventive maintenance effectively. To resolve this dilemma, a multi-state-oriented mission reliability modeling for multi-station manufacturing system is proposed. First, the mapping relationship between the produced product reliability and mission reliability of the manufacturing system is proposed as the basis for modeling, and the connotation of mission reliability is elaborated by analyzing the polymorphisms of the multi-station manufacturing system. Second, a graphical representation to improve the state transparency named as Quality State Task Network is proposed based on production data by integrating the variability of task-demands propagation as well as the multi-state in material quality and machine performance. Third, the mission reliability modeling method based on the Quality State Task Network is proposed. Finally, a case study of cylinder-head manufacturing system has been applied to validate the proposed model.

Risk-based quality accident ranking approach using failure mechanism and Axiomatic domain mapping

Manufacturers face numerous product quality accidents and thus require an effective and general approach to rank the occurred quality accidents. Therefore, a universal risk-based quality accident ranking method emphasising the importance of the accident formation mechanism is proposed in this paper to rank, analyse, and prevent occurred quality accidents comprehensively. First, the risk formation mechanism of quality accident is proposed emphatically using two typical failure mechanisms and Axiomatic domain mapping, and the structure of big quality accident data is presented on the basis of big product lifecycle data in order to provide data support for the subsequent risk analysis. Second, the accident failure cost, probability, and detectivity are adopted as the critical risk factors, which are computed using the failure cost model, extended fault tree and Axiomatic relevance tree respectively. Third, a modified risk importance index considering the relative weight of risk factors is presented to measure and rank the risk priority of quality accidents. Finally, a case study on a computer control panel accident risk analysis is conducted to verify the effectiveness of the proposed approach. Results show that the proposed method can objectively reflect the accident risk degree and provide necessary reference for accident risk mitigation.

Risk-oriented assembly quality analysing approach considering product reliability degradation

Assembly process is a critical stage in the formation of product quality and reliability, but related consideration of the produced product reliability and accident risk has not attracted deserved attention in the most assembly quality analysis frameworks. To this end, this paper enhances risk analysis in assembly process quality control, which is advocated by ISO 9001:2015, and presents a risk-oriented assembly quality analysis approach considering the effects of assembly variations on the produced product reliability degradation and accident risk. First, a conceptual QRR chain is presented to illustrate the relationship among assembly process quality (Q), product reliability (R), and failure accident risk (R). Second, a risk-oriented and bidirectional framework for the analysis of assembly process quality is established based on the presented QRR chain aiming to quantitatively identify the risk sources in the assembly process and reduce the risk of failure accidents. Third, an assembly process quality risk model with key function reliability as its core is presented to establish the quantitative relationship between assembly variation and product failure accident risk. Finally, the presented approach is verified through a case study of an assembling quality risk analysing for acid-resistant grinder.

Product assembling quality risk analysis approach based on RQR chain

The assembling process is the final production step, its quality is the decisive factor of the reliability of the finished product. Along with the release of ISO 9001: 2015, the risk of thinking is firstly cited, and the risk oriented quality analysis should be extended to the assembling process. Therefore, in order to improve the reliability of the final product, the risk thinking is needed to be introduced into the management and analysis of the assembling quality. Therefore, based on the proposed RQR chain, a reliability oriented quality risk analysis method is presented for the product assembling process. Firstly, the RQR assembling chain is introduced in this paper, and its three basic management objects of system reliability (R), assembling process quality (Q) and product reliability (R) are expounded. Secondly, based on the co-effect in the RQR chain, a quality framework of risk control is put forward. Thirdly, the impact of noncritical quality characteristic variations on key quality characteristics (KQC) is analyzed, and then the decline degree of the assembling product reliability caused by the KQCs variation is quantified. Then, according to the impact of the proportion, the risk factor K is determined, and then the quantitative relationship between assembling variation and product quality accident risk is established. Finally, a quality risk analysis case of a lifting equipment assembling process is given to verify the availability of the approach.

Quality variation control oriented product infant failure risk mitigation strategy based on risk chain

Infant failure seriously affects customer satisfaction, which is mainly determined by quality variations in manufacturing process, and it is the most critical part of product quality risk. However, most of manufacturers subject to lack of targeted quality variation controlling for infant failure risk, which causes neglecting of preventing and mitigating infant failure risk. Therefore, in this paper, first, an infant failure risk chain is put forward to clarify the formation mechanism from process variation to infant failure. And second, based on forward analysis of the chain, infant failure risk is quantitatively modeled. Third, according to the analysis results, the key process variations are identified by backward analysis of the chain. And variation controlling costs and infant failure losses costs are comprehensively considered to optimize process variation controlling. Finally, a case study of a level control system is introduced to verify the applicability of the proposed method. The final result shows that the proposed method has a good performance in infant failure risk mitigation.

A cascading failure analyzing approach based on the axiomatic functional and physical domain mapping for complex product

Cascading failures (CFs) in a complex product are the failures of interconnected functions in which the crash of a function can trigger the failure of successive functions. They can affect product function failure probability seriously, and their root causes analysis is a very complicated and challenging task. Therefore, it is significant to develop an applicable analyzing method considering the effects of CFs for complex product failures. In this paper, the domain mapping theory in Axiomatic design is adopted to modeling the effect of cascading failure for the first time, and the latent failure occurrence possibility is computed by the aid of the design matrix. Firstly, the mechanism of cascading failure is expounded, its complexity and analyzing demands are identified. Secondly, the domain mapping theory in Axiomatic design is applied to model the propagation process of cascading failure. Thirdly, the complicated effect of cascading failure is modeled by the design matrix quantitatively, and the occurrence possibility of cascading failure is computed by design matrix. Finally, the proposed method is illustrated through detailed analysis of a wireless temperature measure device component of a complex product.