Mission reliability evaluation based on operational quality data for multistate manufacturing systems

Modern and intelligent manufacturing systems have a prominent multistate feature. However, previous studies of reliability analysis of multistate manufacturing systems mostly focused on the basic reliability of manufacturing systems but disregarded their operating characteristics, which has hindered the development of Prognostics and Health Management technique for intelligent manufacturing systems. Therefore, an evaluation approach of mission reliability for multistate manufacturing systems based on operational quality data is proposed in this paper. First, from the systematic viewpoint of the composition and operational principle of the manufacturing system, the relationship among production task execution state, production equipment degradation state, and produced product quality state is expounded, and the connotation of the mission reliability of multistate manufacturing systems is defined. Second, an extended state task network (ESTN) is presented to organise operational quality data by considering the quality state of work in process (WIP). Third, a fusion model of operational quality data for manufacturing systems is established with the aid of the ESTN, and an operational quality data-oriented evaluation method of mission reliability is been put forward. Finally, a case study of a manufacturing system for a cylinder head is conducted to verify the proposed approach.     

Impact of quality variations on product reliability

The reliability of manufactured products can differ from the desired design reliability due to variations in manufacturing quality. Failure data from field provide useful information to assess if the changes in product reliability variations are significant or not and to identify the cause for the variation. In order to devise statistical methods to detect this, one needs to model the effect of quality variations in manufacturing on product reliability. This paper looks at this issue and examines the Weibull case in detail.     

Integration of dimensional quality and locator reliability in design and evaluation of multi-station body-in-white assembly processes

Research efforts have been made to develop a Quality and Reliability chain (QR chain) model to integrate manufacturing system component reliability and product quality in multi-station manufacturing processes. Based on a previously developed state space model, which captures the variation propagation throughout all stations, a general QR chain model is developed for Body-In-White (BIW) assembly processes. The effectiveness of the QR chain modeling strategy is demonstrated by thoroughly studying the relationship between locator performance and product quality in assembly processes. Based on the analytical result of system reliability obtained from the QR chain model, optimal locator wear rate assignment is further investigated. A case study is conducted to demonstrate the effectiveness and potential usage of the QR chain model for the BIW assembly system design evaluation and optimization.     

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.     

The challenge of quantitative reliability

After examining the need of the equipment/system user to receive, collect, analyse and supply quantitative reliability information, this paper discusses the methods, existing and potential, of satisfying this need. It does so against the background of the now widely acknowledged inaccuracy of traditional methods of reliability prediction, the recognition that the conventional failure-rate bathtub curve is an oversimplification and the difficulty of gathering adequate test and field failure data on increasingly high-reliability product in an age of fast technology evolution and short new product lead-time markets. There are three important tasks for the equipment user: (a) establishment of an efficient system of failure data collection and analysis; (b) utilization of these data in all business and organizational activities; (c) participation in the creation of an accurate method of reliability prediction by providing feedback of field reliability data to product manufacturers. © 1998 John Wiley & Sons, Ltd.     

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.     

Empirical relationships between some manufacturing practices and performance

Intense global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing manufacturers to adopt manufacturing practices and competitive priorities that enable them to deliver high quality products in a short period of time. Identifying manufacturers’ competitive priorities and effective manufacturing practices has long been considered one of the key elements in manufacturing strategy research. This paper presents the results of a study conducted to identify some of the effective manufacturing practices that have a significant influence on manufacturing performance. This study also identifies the main competitive objectives of manufacturing industries that participated in the study. The results reported in this paper are based on data collected from a survey using a standard questionnaire administered to 1000 manufacturers in Australia. Evidence indicates that product quality and reliability are the main competitive factors for manufacturers and price has become surprisingly a relatively less important factor. Results show that simultaneous pursuit of advanced quality practices can neutralize the potential negative impacts of manufacturing difficulties and significantly improve product quality and manufacturing performance. Failure mode and effect analysis (FMEA) is shown to be an important tool for improving product quality and on time delivery performance. FMEA practice driven by the intention to improve customer satisfaction is more effective than that practised to fulfil customer requirements. Effective supplier relationships are shown to contribute positively to the manufacturing performance. The results also suggest that maintaining a supplier rating system and product data management and regularly updating them with field failure and warranty data are important manufacturing practices.     

Tolerance‐based reliability and optimization design of switched‐mode power supply

Due to its high efficiency and low power consumption, switched‐mode power supply (SMPS) represents the development trend of the stabilized voltage power supply. However, tolerance has become one of the key factors in the design of SMPS because of the process fluctuation of electronic components, unstable input parameters of the circuit system, influence of working conditions and environment, and the effect of aging. In order to improve the reliability of SMPS and reduce the manufacturing cost, this paper proposes a reliability analysis and optimization design method based on the tolerance and sensitivity analysis. Finally, this method is applied to the tolerance design for the positive switching power supply of the SMPS circuits, and the optimal tolerance design scheme is obtained. Furthermore, the reliability and probability density curves are evaluated.     

Optimal reliability, warranty and price for new products

The success of a new product depends on both engineering decisions (product reliability) and marketing decisions (price, warranty). A higher reliability results in a higher manufacturing cost and higher sale price. Consumers are willing to pay a higher price only if they can be assured about product reliability. Product warranty is one such tool to signal reliability with a longer warranty period indicating better reliability. Better warranty terms result in increased sales and also higher expected warranty servicing costs. Warranty costs are reduced by improvements in product reliability. Learning effects result in the unit manufacturing cost decreasing with total sales volume and this in turn impacts on the sale price. As such, reliability, price and warranty decisions need to be considered jointly. The paper develops a model to determine the optimal product reliability, price and warranty strategy that achieve the biggest total integrated profit for a general repairable product sold under a free replacement-repair warranty strategy in a market and looks at two scenarios for the pricing and warranty of the product. The model assumes that the sale rate increases as the warranty period increases and decreases as the price increases. The maximum principle method is used to obtain optimal solutions for dynamic price and warranty situations. Finally, numerical examples are given to illustrate the proposed model.