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The purpose of the paper is to develop a conceptual framework that integrates the technology and commercial issues early at the design stage to minimize warranty costs in the most effective and efficient manner and also to develop a model for optimization of warranty with specific focus on reliability and warranty policies.

The critical issues in warranty are addressed which affect the warranty cost. An optimization model to achieve multiple goals like minimization of the warranty cost and improving the reliability of the product is developed using genetic algorithm as a solution methodology. The model is illustrated with a real case of automobile engine.

The results of the optimization show improvement in mean time between failures (MTBF) which results due to improvement in the product reliability and also the targeted warranty cost is achieved.

The model developed needs to be further extended with inclusion of additional decision variable such as support level offered and more objectives such as attractiveness of the warranty from the customer's view point and spares cost to the customer.

The paper provides the help to the designers at the design stage to take the decisions related to warranty in deciding the warranty parameters.

The purpose of this paper is to propose a warranty-based bilateral automated multi-issue negotiation approach.

A methodology for bilateral automated negotiation process is developed considering the targets such as warranty attractiveness, warranty cost, mean time between failures, spare parts cost to the end user over the useful life of the life. The negotiation methodology is explained using different cases of negotiation. The optimization for each negotiation step is carried out using genetic algorithm with elitism strategy.

The result after optimization indicates that the desired target values are achieved and manufacturer obtained desired profit margin.

Application of automated negotiation model is illustrated using a real life case of an automobile engine manufacturer. The proposed approach helps the manufacturer of any product to develop a methodology for carrying out the negotiation process. The approach also results into taking warranty-related decisions at the design stage.

This paper contributes in proposing a generalized methodology for warranty-based negotiation in which the negotiation is carried out between the manufacturer and the customer.

The purpose of this paper is to develop an attractiveness index-based warranty cost model considering decision variables as design alternatives, warranty duration and support level.

A warranty optimization approach is illustrated using a real life example of an automobile engine with Mean Time Between Failures and Warranty Attractiveness Index as constraints.

It will help to improve the customer satisfaction by giving a more attractive warranty compared to that being offered by the competitors.

Approaches that consider the effect of decision variables on attractiveness of a warranty policy in a quantitative manner have received relatively less attention. The paper attempts to capture the attractiveness of warranty from the manufacturer as well as customer point of view.

The proposed approach will help manufacturers to take appropriate decisions related to warranty parameters and component selection at the design stage.

The purpose of this paper is to identify and quantify the key components of the overall cost of software development when warranty coverage is given by a developer. Also, the authors have studied the impact of imperfect debugging on the optimal release time, warranty policy and development cost which signifies that it is important for the developers to control the parameters that cause a sharp increase in cost.

An optimization problem is formulated to minimize software development cost by considering imperfect fault removal process, faults generation at a constant rate and an environmental factor to differentiate the operational phase from the testing phase. Another optimization problem under perfect debugging conditions, i.e. without error generation is constructed for comparison. These optimization models are solved in MATLAB, and their solutions provide insights to the degree of impact of imperfect debugging on the optimal policies with respect to software release time and warranty time.

A real-life fault data set of Radar System is used to study the impact of various cost factors via sensitivity analysis on release and warranty policy. If firms tend to provide warranty for a longer period of time, then they may have to bear losses due to increased debugging cost with more number of failures occurring during the warrantied time but if the warranty is not provided for sufficient time it may not act as sufficient hedge during field failures.

Every firm is fighting to remain in the competition and expand market share by offering the latest technology-based products, using innovative marketing strategies. Warranty is one such strategic tool to promote the product among masses and develop a sense of quality in the user’s mind. In this paper, the failures encountered during development and after software release are considered to model the failure process.

The study aims to design the limited number of random working cycle as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability during the warranty period. By extending the proposed warranty to the consumer's post-warranty maintenance model, besides the authors investigate two kinds of random maintenance policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating depreciation expense depending on working time, the cost rate is constructed for each random maintenance policy and some special cases are provided by discussing parameters in cost rates. Finally, sensitivities on both the proposed warranty and random maintenance policies are analyzed in numerical experiments.

The working cycle of products can be monitored by advanced sensors and measuring technologies. By monitoring the working cycle, manufacturers can design warranty policies to ensure product reliability performance and consumers can model the post-warranty maintenance to sustain the post-warranty reliability. In this article, the authors design a limited number of random working cycles as a warranty term and propose two types of warranties, which can help manufacturers to ensure the product reliability performance during the warranty period. By extending a proposed warranty to the consumer's post-warranty maintenance model, the authors investigate two kinds of random replacement policies to sustain the post-warranty reliability, i.e. random replacement first and random replacement last. By integrating a depreciation expense depending on working time, the cost rate is constructed for each random replacement and some special cases are provided by discussing parameters in the cost rate. Finally, sensitivities to both the proposed warranties and random replacements are analyzed in numerical experiments.

It is shown that the manufacturer can control the warranty cost by limiting number of random working cycle. For the consumer, when the number of random working cycle is designed as a greater warranty limit, the cost rate can be reduced while the post-warranty period can't be lengthened.

The contribution of this article can be highlighted in two key aspects: (1) the authors investigate early warranties to ensure reliability performance of the product which executes successively projects at random working cycles; (2) by integrating random working cycles into the post-warranty period, the authors is the first to investigate random maintenance policy to sustain the post-warranty reliability from the consumer's perspective, which seldom appears in the existing literature.

The purpose of this paper is threefold: first, to analyse the existing work of warranty risk management (WaRM); second, to develop a generic WaRM framework; and third, to design a generic taxonomy for warranty hazards from a warranty chain perspective.

To understand the top warranty hazards, the authors designed a questionnaire, received 40 responses from the warranty decision makers (WDM) in the automotive industry in the UK and then analysed the responses.

The assembly process capability at suppliers is the top contributor to warranty incidents from the suppliers’ and original equipment manufacturers’ (OEMs’) viewpoints. The human error at different stages of the product lifecycle contributes to the occurrence of warranty incidents. The collaboration among parties, particularly, the accessibility to warranty-related data between parties (i.e. suppliers, OEM and dealers), is limited. Customers’ fraud contributes more to warranty costs than warranty services providers’ fraud. The top contributors to customer dissatisfaction relating to warranty are the warranty service time and service quality.

The questionnaires were used to collect data in the UK, which implies the research outcomes of this paper may only reflect the UK area.

The WaRM framework and taxonomy proposed in this paper provide WDM with a holistic view to identifying the top contributors to warranty incidents. With them, the decision makers will be able to allocate the required fund and efforts more effectively.

This paper contributes to the literature by providing the first work of systematically analysing the top contributors to warranty incidents and costs and by providing a WaRM framework.

The purpose of this paper is to design an optimal reliability acceptance sampling plan (RASP) using the Type-I generalized hybrid censoring scheme (GHCS) for non-repairable products sold under the general rebate warranty. A cost function approach is proposed for products having Weibull distributed lifetimes incorporating relevant costs.

For Weibull distributed product lifetimes, acceptance criterion introduced by Lieberman and Resnikoff (1955) is derived for Type-I GHCS. A cost function is formulated using expected warranty cost and other relevant cost components incorporating the acceptance criterion. The cost function is optimized following a constrained optimization approach to arrive at the optimum RASP. The constraint ensures that the producer's and the consumer's risks are maintained at agreed-upon levels.

Optimal solution using the above approach is obtained for Type-I GHCS. As a special case of Type-I GHCS, the proposed approach is also used to arrive at the optimal design for Type-I hybrid censoring scheme as shown in Chakrabarty et al. (2019). Observations regarding the change in optimal design and computational times between the two censoring schemes are noted. An extensive simulation study is performed to validate the model for finite sample sizes and the results obtained are found to be in strong agreement. In order to analyze the sensitivity of the optimal solution due to misspecification of parameter values and cost components, a well-designed sensitivity analysis is carried out using a real-life failure data set from Lawless (2003). Interesting observations are made regarding the change in optimal cost due to change in parameter values, the impact of warranty cost in optimal design and change in optimal design due to change in lot sizes.

The research presents an approach for designing optimal RASPs using Type-I generalized hybrid censoring. The study formulates optimum life test sampling plans by minimizing the average aggregate costs involved, which makes it valuable in dealing with real-life problems pertaining to product quality management.

Warranty service plays a critical role in sustainability and service continuity and influences customer satisfaction. Considering the role of social networks in customer feedback channels, one of the essential sources to examine the reflection of a product/service is social media mining. This paper aims to identify the frequent product failures through social network mining. Focusing on social media data as a comprehensive and online source to detect warranty issues reveals opportunities for improvement, such as user problems and necessities. This model will detect the causes of defects and prioritize improving components in a product-service system based on FMEA results.

Ontology-based methods, text mining and sentiment analysis with machine learning methods are performed on social media data to investigate product defects, symptoms and the relationship between warranty plans and customer behaviour. Also, the authors have incorporated multi-source data collection to cover all the possibilities. Then the authors promote a decision support system to help the decision-makers using the FMEA process have a more comprehensive insight through customer feedback. Finally, to validate the accuracy and reliability of the results, the authors used the operational data of a LENOVO laptop from a warranty service centre and classifier performance metrics to compare the authors’ results.

This study confirms the validity of social media data in detecting customer sentiments and discovering the most defective components and failures of the products/services. In other words, the informative threads are derived through a data preparation process and then are based on analyzing the different features of a failure (issues, symptoms, causes, components, solutions). Using social media data helps gain more accurate online information due to the limitation of warranty periods. In other words, using social media data broadens the scope of data gathering and lets in all feedback from different sources to recognize improvement opportunities.

This work contributes a DSS model using multi-channel social media mining through supervised machine learning for warranty-service improvement based on defect-related discovery to unravel the potential aspects of social networks analysis to predict the most vulnerable components of a product and the main causes of failures that lead to the inputs for the FMEA process and then, a cost optimization. The authors have used social media channels like Twitter, Facebook, Reddit, LENOVO Forums, GitHub, Quora and XDA-Developers to gather data about the LENOVO laptop failures as a case study.

The purpose of this paper is to present a decision model for second-hand products to determine the optimal upgrade level, warranty period and preventive maintenance (PM) effort level which maximize the total expected profit generated by the dealer considering any given past age of the product and the effect of the sales volume.

A mathematical model is developed to derive the optimal triplet: upgrade level, warranty period and PM effort level, which maximize the total expected profit generated by the dealer for any second-hand product with a given past age. Numerical experimentations have been conducted to investigate the effectiveness of the proposed model and to explore the interactions among the model variables.

Numerical experimentations including a sensitivity analysis have been conducted on the model key parameters. The obtained results show that performing PM actions during the warranty period helps the dealers to provide extended warranty for older second-hand products without spending a significant effort on upgrade actions and therefore increase the volume of sales. Also, the interaction between the PM level and the profit margin threshold is demonstrated. Finally, the effect of the sales volume function parameters (the price and warranty elasticity parameters) on the optimal solution is characterized.

Given the complexity of the profit function to be maximized involving a considerable number of decision variables with different nature, the authors limited the study to the case where the past age of the second-hand product is known.

The proposed model aims to provide second-hand product dealers with a modeling framework that enables them to have a realistic estimation of the generated profit by integrating the marketing and engineering key parameters of the second-hand product.

Most of the existing literature dealing with the reliability improvement of second-hand products does not take into account the fact that a realistic estimation of the total profit generated by the dealer requires the consideration of the sales volume. The latter is closely related to the marketing parameters characterized by the warranty period length and the second-hand product selling price. The proposed model introduces the effect of the total sales volume on the total expected profit. The authors also introduce the concept of discrete upgrade levels for a better control of the restoration degree. The authors study the impact of warranty and price elasticity parameters on the optimal solution and the resultant interaction with the customer purchase decision and consequently the sales volume.

In order to reduce avoidably lengthy duration required to test highly reliable products under usage stress, accelerated life test sampling plans (ALTSPs) are employed. This paper aims to build a decision model for obtaining optimal sampling plan under accelerated life test setting using Type-I hybrid censoring scheme for products covered under warranty.

The primary decision model proposed in this paper determines ALTSP by minimizing the relevant costs involved. To arrive at the decision model, the Fisher information matrix for Type-I hybrid censoring scheme under accelerated life test setting is derived. The optimal solution is attained by utilizing appropriate techniques following a nonlinear constrained optimization approach. As a special case, ALTSP for Type-I censoring is obtained using the same approach. ALTSP under Type-I hybrid censoring using the variance minimization approach is also derived.

On comparing the optimal results obtained using the above mentioned approaches, it is found that the cost minimization approach does better in reducing the total cost incurred. Results also show that the proposed ALTSP model under cost function setting has considerably lower expected testing time. Interesting findings from the sensitivity analysis conducted using a newly introduced failure dataset pertaining to locomotive controls are highlighted.

The research introduces a model to design optimum ALTSP for Type-I hybrid censoring scheme. The practical viability of the model makes it valuable for real-life situations. The practical application of the proposed model is exemplified using a real-life case.