Warranty Data Analysis: A Review

Warranty claims and supplementary data contain useful information about product quality and reliability. Analysing such data can therefore be of benefit to manufacturers in identifying early warnings of abnormalities in their products, providing useful information about failure modes to aid design modification, estimating product reliability for deciding on warranty policy and forecasting future warranty claims needed for preparing fiscal plans. In the last two decades, considerable research has been conducted in warranty data analysis (WDA) from several different perspectives. This article attempts to summarise and review the research and developments in WDA with emphasis on models, methods and applications. It concludes with a brief discussion on current practices and possible future trends in WDA

Improving root cause analysis through the integration of PLM systems with cross supply chain maintenance data

The purpose of this paper is to demonstrate a system architecture for integrating Product Lifecycle Management (PLM) systems with cross supply chain maintenance information to support root-cause analysis. By integrating product-data from PLM systems with warranty claims, vehicle diagnostics and technical publications, engineers were able to improve the root-cause analysis and close the information gaps. Data collection was achieved via in-depth semi-structured interviews and workshops with experts from the automotive sector. Unified Modelling Language (UML) diagrams were used to design the system architecture proposed. A user scenario is also presented to demonstrate the functionality of the system

Warranty return policies for products with unknown claim causes and their optimisation

In practical warranty services management, faults may not always be found in claimed items by warranty service agents, which is the well-known no-fault found phenomenon (for example, caused by a loose connection between parts, or simply human error). This phenomenon can contribute more than 40% of reported service faults in electronic products and it can be due to faults of manufacturers or product users. Little research, however, considers this phenomenon in warranty management since faults are normally assumed to be found in the claimed items. On the basis of different levels of testing, this paper proposes three warranty return policies, which decide whether new items should be sent to warranty claimants or not. It then derives and compares the expected costs of the policies, and obtains the optimal warranty periods under supply chain environments. The paper illustrates the results with artificially generated data

Expert Elicitation for Reliable System Design

This paper reviews the role of expert judgement to support reliability assessments within the systems engineering design process. Generic design processes are described to give the context and a discussion is given about the nature of the reliability assessments required in the different systems engineering phases. It is argued that, as far as meeting reliability requirements is concerned, the whole design process is more akin to a statistical control process than to a straightforward statistical problem of assessing an unknown distribution. This leads to features of the expert judgement problem in the design context which are substantially different from those seen, for example, in risk assessment. In particular, the role of experts in problem structuring and in developing failure mitigation options is much more prominent, and there is a need to take into account the reliability potential for future mitigation measures downstream in the system life cycle. An overview is given of the stakeholders typically involved in large scale systems engineering design projects, and this is used to argue the need for methods that expose potential judgemental biases in order to generate analyses that can be said to provide rational consensus about uncertainties. Finally, a number of key points are developed with the aim of moving toward a framework that provides a holistic method for tracking reliability assessment through the design process.Comment: This paper commented in: [arXiv:0708.0285], [arXiv:0708.0287], [arXiv:0708.0288]. Rejoinder in [arXiv:0708.0293]. Published at http://dx.doi.org/10.1214/088342306000000510 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

WeighstEd

The purpose of this design thesis is to outline and describe the design project; WeighstEd. WeighstEd, is a data collection, storage, and analysis system for food waste to help Santa Clara University’s Sustainability Center reach a quantifiable food waste reduction goal of 10% by 2020 by using data to make informed cafeteria changes. The report will outline the entire engineering design process from ideation to manufacture including analysis techniques and benchmark testing. This report will serve as a written documentation of three mechanical engineers Senior Design Project completed at Santa Clara University. WeighstEd will be implemented at on campus events and in the university cafeteria beginning in the 2019-2020 school year

Warranty prediction during product development: Developing an event generation engine

In 2010, high tech industries including computer makers, peripherals manufacturers, and medical equipment manufacturers spent a total of $8 billion on warranty. Reducing warranty costs improves the manufacturer\u27s profit and helps to reduce the overall cost of the product. An often cited principle is that approximately 80% of the eventual product cost is \u27locked in\u27 during the very early stages of product development, however, traditional methods of warranty analysis are not well suited to predict the warranty costs during these early stages. Thus, product development personnel need better tools to make good predictions about the warranty costs so that they can make better decisions to reduce warranty earlier in product development. In order to address this gap, previous research defined a warranty prediction framework, which at its core was a warranty event generation engine that integrated the disparate data sources available early in the product development process. The objective of this work was to create this event generation model, which would give the probability of occurrence for a warranty event, given the length of time of service for the system. The model developed in this work used different data sources namely, field data, product development data and engineering judgment data from our industrial partner. The datasets were then combined using a two-stage numerical Bayes method to predict the probability of occurrence of an event. Various test cases were created, by using the different datasets as priors and likelihoods. The results were then compared to actual field data set to understand how well the model performed. It was found that the model performed well and was able to produce a bounded solution. The future research agenda is to create a tool for product development professionals that will help them predict warranty costs

Photovoltaic module reliability model based on field degradation studies

Crystalline silicon photovoltaic (PV) modules are often stated as being the most reliable element in PV systems. This presumable high reliability is reflected by their long power warranty periods. In agreement with these long warranty times, PV modules have a very low total number of returns, the exceptions usually being the result of catastrophic failures. Up to now, failures resulting from degradation are not typically taken into consideration because of the difficulties in measuring the power of an individual module in a system. However, lasting recent years PV systems are changing from small isolated systems to large grid-connected power stations. In this new scenario, customers will become more sensitive to power losses and the need for a reliability model based on degradation may become of utmost importance. In this paper, a PV module reliability model based on degradation studies is presented. The main analytical functions of reliability engineering are evaluated using this model and applied to a practical case, based on state-of-the-art parameters of crystalline silicon PV technology. Relevant and defensible power warranties and other reliability data are obtained with this model based on measured degradation rates and time-dependent power variability. In the derivation of the model some assumptions are made about the future behaviour of the products—i.e. linear degradation rates—although the approach can be used for other assumed functional profiles as well. The method documented in this paper explicitly shows manufacturers how to make reasonable and sensible warranty projections

A Conceptual Framework for Definition of the Correlation Between Company Size Categories and the Proliferation of Business Information Systems in Hungary Download article

Based on a conceptual model, this paper aims to explore the background of the decision-making process leading to the introduction of business information systems among enterprises in Hungary. Together with presenting the problems arising in the course of the implementation of such systems, their usage patterns are also investigated. A strong correlation is established between the size of an enterprise, the scope of its business activities and the range of the business information systems it applies

Predicting Cost/Reliability/Maintainability of Advanced General Aviation Avionics Equipment

A methodology is provided for assisting NASA in estimating the cost, reliability, and maintenance (CRM) requirements for general avionics equipment operating in the 1980's. Practical problems of predicting these factors are examined. The usefulness and short comings of different approaches for modeling coast and reliability estimates are discussed together with special problems caused by the lack of historical data on the cost of maintaining general aviation avionics. Suggestions are offered on how NASA might proceed in assessing cost reliability CRM implications in the absence of reliable generalized predictive models