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.     

The use of reliability‐oriented field feedback information for product design improvement: a case study

In the innovative industry, four major trends are found to influence product quality and reliability: the increase in product complexity, the strong pressure on time to market, the increasing global economy, and the decreasing tolerance for quality problems. Thus, it becomes more difficult to anticipate all potential failures during the product development process. In this context, an efficient field feedback process should be in place to react to the unanticipated deviations in product performance. Based on a case study made in an innovative company, this paper shows that the problem is not so much in the information collection as in the inherent quality of the information and in the manner the information is processed. Therefore, a new method, presented in this paper, was developed to classify and prioritize field data and to upgrade it into information that can be used for design improvement according to the dominant classes of failures using the four‐phase roller coaster model. Although this newly generated information is richer than raw field data it is not yet detailed enough to allow direct design optimization. Therefore, a second upgrading stage, based on design of experiments, was developed. It uses a method that combines physics‐of‐failure (bottom‐up) and field information (top‐down). As traditional DoE mainly deals with largely time‐independent quality data obtained during the manufacturing process the approach had to be modified to deal with time‐dependent reliability data. Case study results show that it is a promising approach for characterizing and resolving failure mechanisms also in innovative companies. Copyright © 2008 John Wiley & Sons, Ltd.     

Improving the Quality of Information Flows in the Backend of a Product Development Process: a Case Study

Considerable research has gone into designing effective product development processes. This, coupled with the increasing need for products that are able to deliver reliable, complex functionality with a high degree of innovation, presents a major challenge to modern day industries in the business of developing products. In order to incorporate relevant field experience in the design and manufacturing of new products, increasingly detailed information needs to be retrieved from the market in a very short amount of time. In one particular consumer electronics industry, business process models describing the information flow in the backend of the product development process indicated massive data loss and also serious data quality degradation. This paper attempts to show how such losses can be mitigated and also proposes a business model that can adequately capture information of a higher quality and in a more structured manner. The end result will be a product development process that provides better feedback on current product performance and is more responsive to future market needs. Copyright © 2005 John Wiley & Sons, Ltd.     

Total System Reliability: Integrated Model for Growth and Test Termination

Reliability demonstration testing is not the most efficient method of assuring product reliability prior to shipment. It is costly, time consuming and has inherent technical and social limitations. The dilemma facing the reliability and quality engineer is whether to continue demonstration testing and risk shipping a product late or ship the product and risk warranty and field service returns. Either option can cause the company to lose significant market share and profit. This paper sets out to solve this dilemma by meeting both the time to market constraints and the product reliability goals. The weaknesses of existing reliability demonstration techniques are explored and a comprehensive methodology is introduced involving controlled development processes, stress testing, root cause determination and process change feedback mechanisms. All prototype products are manufactured on the final volume process line resulting in the early identification and correction of process‐related problems. Testing commences on the first available prototypes with system stress/robust testing being employed to stimulate failures, determine their root cause and correct them. Reliability growth modelling assesses the ongoing improvements occurring in reliability during the development cycle, while a statistical stopping rule is used to determine the optimal product release time without risking product warranty. The approach is applicable to systems incorporating both hardware and software elements. The methodology has been validated on three development projects of telecommunication systems comprising hardware and software. In addition to enhancing team behaviour and performance, the development times have been reduced by 14% and the ramp‐up time to full worldwide product shipments has been reduced by 50%. Copyright © 2005 John Wiley & Sons, Ltd.     

Quality of Information Flow in the Backend of a Product Development Process: a Case Study

The increasing need for products that are able to reliably deliver complex functionality with a high degree of innovation presents a major challenge to the modern day product creation processes. In order to be able to use information on the field behaviour of previous products in the design of new products, increasingly detailed information needs to be retrieved from the market in an increasingly shorter time. The purpose of this study is to analyse, in a typical case in the consumer electronics industry, whether the underlying business process is able to generate this information with adequate quality sufficiently quickly. Information models of the company's service centre and call centre were developed using the concepts of maturity index on reliability. The results showed that the structure of the information handling process resulted in a massive data loss (up to 60% of the data gathered by the service centres) and also in serious data quality degradation. Would this information have not been lost, it could have been used by development teams for preventive and corrective actions. Copyright © 2004 John Wiley & Sons, Ltd.     

Designing reliability information flows

It is well-known [Reliab. Eng. Syst. Saf. 75 (2002) 295] that in modern development processes it is essential to have an information flow structure that facilitates fast feedback from product users (customers) to departments at the front end, in particular development and production. As information is only relevant if it is used when taking decisions, this paper presents a guideline for building field feedback information flows that facilitate the decision taking during the product creation and realisation process. The guideline takes into consideration that the type of decisions depends on the span-of-control, therefore following Parsons [Structure and Process in Modern Societies (1990)] the span-of-control is subdivided into the following three levels: strategic, tactic, and executive. The guideline is illustrated with a case in which it is used for analysing the quality of existing field feedback flows.     

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.     

Field-Failure and Warranty Prediction Based on Auxiliary Use-Rate Information

Assessment of risk due to product failure is important both for purposes of finance (e.g., warranty costs) and safety (e.g., potential loss of human life). In many applications a prediction of the number of future failures is an important input to such an assessment.

Usually the field-data response used to make predictions of future failures is the number of weeks (or another unit of real time) in service. Use-rate information usually is not available (automobile warranty data are an exception, where both weeks in service and number of miles driven are available for units returned for warranty repair). With new technology, however, sensors and smart chips are being installed in many modern products ranging from computers and printers to automobiles and aircraft engines. Thus the coming generations of field data for many products will provide information on how the product was used and the environment in which it was used. This article was motivated by the need to predict warranty returns for a product with multiple failure modes. For this product, cycles-to-failure/use-rate information was available for those units that were connected to the network. We show how to use a cycles-to-failure model to compute predictions and prediction intervals for the number of warranty returns. We also present prediction methods for units not connected to the network. To provide insight into the reasons that use-rate models provide better predictions, we also present a comparison of asymptotic variances comparing the cycles-to-failure and time-to-failure models. This article has supplementary material online.     

Product Component Genealogy Modeling and Field‐failure Prediction

Many industrial products consist of multiple components that are necessary for system operation. There is an abundance of literature on modeling the lifetime of such components through competing risks models. During the life‐cycle of a product, it is common for there to be incremental design changes to improve reliability, to reduce costs, or due to changes in availability of certain part numbers. These changes can affect product reliability but are often ignored in system lifetime modeling. By incorporating this information about changes in part numbers over time (information that is readily available in most production databases), better accuracy can be achieved in predicting time to failure, thus yielding more accurate field‐failure predictions. This paper presents methods for estimating parameters and predictions for this generational model and a comparison with existing methods through the use of simulation. Our results indicate that the generational model has important practical advantages and outperforms the existing methods in predicting field failures. Copyright © 2016 John Wiley & Sons, Ltd.     

Managing product reliability in business processes ‘under pressure’

Product reliability is often seen as a product attribute. Models with different degree of sophistication analyze and predict the reliability of a product as a function of the internal structure (such as components and their relation). The practical relevance of these models, in relation with the (business) processes in which the related products are actually used, is not often addressed. Different types of reliability issues, however, can be relevant for products in different industrial contexts. This paper will present a classification model to describe different business processes, based on the degree of product innovation. It will also propose a taxonomy that can be used to classify different types of reliability problems. As this paper will demonstrate, only certain combinations of reliability problems are relevant for certain business processes. It will also show that, given certain technology trends, some combinations will become more relevant in the future. The final part of this paper will demonstrate that especially for these combinations many of the existing reliability analysis and prediction methods can be considered inadequate.     

产品设计过程中的可靠性增长研究

针对产品设计过程中的可靠性增长问题,提出把整个产品系统分为大样本子系统和小样本子系统,对于不同的子系统采用不同的可靠性增长方案和可靠性增长数学分析模型,充分挖掘所有的直接或问接数据信息,并利用到产品设计过程;建立产品的可靠性增长分析数据库系统,保存产品在设计过程中的数据,辅助同类产品设计．     

基于B/S模式的弹药失效诊断评估系统研究

为了提高通用弹药产品可靠性评估的效率,实现产品失效及可靠性的系统化辅助分析评估,对通用弹药产品的失效过程进行研究,总结出产品的一般失效分析过程、失效诊断方法及弹药失效分析数据字典.在辅助分析系统中,提供了失效分析、可靠性评估、FMECA等模块.应用Java、JSP等语言,在B/S模式下进行设计开发,实现了对产品失效的过程分析及产品可靠性评估.优化可靠性统计分析的数学模型,改进评估参量算法,使评估工作效率提高30%以上,参数精度达到小数点后8位.     

Soft reliability: an interdisciplinary approach with a user–system focus

A recent trend in technological innovation is towards the development of increasingly multifunctional and complex products to be used within rich socio‐cultural contexts such as the high‐end office, the digital home, and professional or personal healthcare. One important consequence of the development of strongly innovative products is a growing market uncertainty regarding ‘if’, ‘how’, and ‘when’ users can and will adopt such products. Often, it is not even clear to what extent these products are understood and interacted with in the intended manner. The mentioned problems have already become an evident concern in the field, where there is a significant rise in the numbers of seemingly sound products being complained about, signaling a lack of soft reliability. In this paper, we position soft reliability as a growing and critical industrial problem, whose solution requires new academic expertise from various disciplines. We illustrate potential root causes for soft reliability problems, such as discrepancy between the perceptions of users and designers. We discuss the necessary approach to effectively capture subjective feedback data from actual users, e.g. when they contact call centers. Furthermore, we present a novel observation and analysis approach that enables insight into actual product usage, and outline opportunities for combining such objective data with the subjective feedback provided by users. Copyright © 2008 John Wiley & Sons, Ltd.     

Enhancing product development through a dynamic information interchange approach

In today's increasingly competitive environment, firms are experiencing growing pressure to reduce the product development lead time to meet market expectations. In this paper, a Responsive Product Development System (RPDS), which is used to model the product development process and the components of the process with object technology, introduces a dynamic product information schema characterized by its ability to provide design practitioners with a product data exchange standard, thus transforming data to information and then knowledge. To validate the feasibility of the proposed schema, a case study has been conducted in a plastic product factory based on the suggested approach. Following feedback from these companies, a further review of the design of the proposed system has been conducted to ensure efficient information flow across the heterogeneous computing environment. A measure of loss to society associated with RPDS in product development time is also included as a system evaluation.     

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.     

Field Reliability Prediction in Consumer Electronics Using Warranty Data

In innovative fast product development processes, such as consumer electronics, it is necessary to check as quickly as possible, using field data, whether the product reliability is at the right level. In consumer electronics, some major companies use the Warranty Call Rate (WCR) for this purpose. This paper discusses extensively the theoretical and practical drawbacks of the WCR. Subsequently, it is demonstrated, using a Weibull failure distribution, that only a few months after product launch, say three months, the warranty data offer the opportunity to estimate the parameters of the failure distribution. Of course, this requires that the warranty data are available in the quality department. Unfortunately, for some companies the field feedback information process from the repair centres to the quality department causes a delay of several months. These companies have to speed up their field feedback information process before they can fully take advantage of the proposed estimation procedure. Copyright © 2006 John Wiley & Sons, Ltd.     

Reliability and economic analysis and improvement of complex mechanical products based on DEA: An empirical case study of hydraulic products

Complex mechanical products involve many specialized fields such as machinery, electronics, hydraulics, and computers, so their initial cost is usually higher. In addition, regular and irregular maintenance are also needed to extend their service life, so that the cost of the product in its life cycle will be increased. Therefore, for the manufacturing enterprises of complex mechanical products, it is very important to achieve the best matching between reliability and economy. In order to survive in the fierce market competition, it is necessary to compare with other similar products in the market, so as to clearly understand the level of their products, find out the gap, and improve it. However, the existing product reliability assessment methods based on probability and statistics theory cannot provide such help for them to solve this problem. Therefore, this paper puts forward a method to evaluate and improve complex mechanical products by using a data envelopment analysis (DEA) model considering the reliability and economy of product comprehensively. Through the relative effectiveness of DEA, the same type of products on the market can be compared, providing specific method for enterprises to evaluate and improve their own product level to achieve the best matching of economy and reliability. This paper introduces the principle and steps of this method and takes the hydraulic component manufacturing enterprise as an example to carry out practical research, which verifies the feasibility and effectiveness of this method.     

A Bayes approach to reliability prediction utilizing data from accelerated life tests and field failure observations

A Bayes approach is proposed to improve product reliability prediction by integrating failure information from both the field performance data and the accelerated life testing data. It is found that a product's field failure characteristic may not be directly extrapolated from the accelerated life testing results because of the variation of field use condition that cannot be replicated in the lab‐test environment. A calibration factor is introduced to model the effect of uncertainty of field stress on product lifetime. It is useful when the field performance of a new product needs to be inferred from its accelerated life test results and this product will be used in the same environment where the field failure data of older products are available. The proposed Bayes approach provides a proper mechanism of fusing information from various sources. The statistical inference procedure is carried out through the Markov chain Monte Carlo method. An example of an electronic device is provided to illustrate the use of the proposed method. Copyright © 2008 John Wiley & Sons, Ltd.     

Effect of Field Stress Variance on Test to Field Correlation in Accelerated Reliability Demonstration Testing

This paper discusses the effect of field stress variance on the value of demonstrated reliability. In many cases, the acceleration factor for a reliability demonstration test is calculated based on a high percentile field stress level, typically corresponding to severe user or environmental conditions. In those cases, the actual field reliability for the population will be higher than that demonstrated by the test. This paper presents a mathematical approach to estimating ‘true’ field reliability based on the acceleration model and stress variable distribution over the product field population. This method is illustrated by an example of automotive electronics reliability demonstration testing and has a wide range of practical applications. Copyright © 2014 John Wiley & Sons, Ltd.