Warranty Claims Research Articles

Tanggung Jawab Showroom Atas Perbaikan Kendaraan Bermotor Bergaransi Perspektif Wahbah Zuhaili: Studi Kasus Kp. Pajak Pulo Jantan Kecamatan N.A IX -X Kabupaten Labuhanbatu Utara

Kp. Pajak Pulo Jantan or Pajak Pulo Village, District N.A IX -X North Labuhanbatu Regency there are cases where motor vehicle SHOWROOMs do not want to claim a damaged engine warranty from their customers even though in the previous sale and purchase agreement it has been agreed. The purpose of this study is to determine the completion of business actors' responsibility for repairing motor vehicles with a warranty perspective from Wahbah Zuhaili's perspective. How is the agreement for guaranteed motor vehicle repairs at the Kp. Pajak Pulo Jantan or District NA. Xi-X North Labuhanbatu. The research method used in this study is an qualitative method to make it easier to get data and also easier to analyze the problems in this study. The results showed that the warranty claim itself according to Wahbah Az-Zuhaili must be carried out because there has been an element of tadlis in the sale and purchase of the motorcycle unit. Not only that, the obligation to carry out this warranty claim is as evidence of fulfillment of the disgrace on an item. Then the obligation order of business actors is also in line with the Consumer Protection Law so that business actors can be prosecuted for committing unlawful acts.

Spare parts provisioning strategy of warranty repair demands for capital-intensive products

The inventory cost of stocking spare parts is a nonnegligible expenditure of providing after-sales service for the manufacturers making capital-intensive products, such as electric vehicles. Especially, for warranty repair service, it is important to manage the spare stock appropriately to satisfy the warranty claims of customers as well as reduce the associated inventory costs. In this paper, we investigate the spare parts inventory issue related to a critical component for under-warranty units of a product. In particular, under the free-replacement warranty policy, failed component will be replaced by a new one by consuming the spare stock. According to the field claim data, we find that the general trend of warranty claims is nonstationary, which will be affected by the product sales and under-warranty failures. Thus, we first propose a model to forecast the time-varying warranty repair demand by explicitly considering the randomness from two major sources, that is, product sales and under-warranty failures. Under the assumptions of Poisson sales process and exponential failure distribution, the closed-form expressions of mean and variance of cumulative warranty repair demand over time are obtained. Because the number of warranty claims in each period is a one-time data, the associated distribution information is unavailable. Then, based on the properties of the demand statistics, we derived a worst-case upper bound for the associated inventory cost and formulate a three-phase finite-horizon spare parts inventory model, which can be used to appropriately address the time-varying warranty claims. Finally, numerical experiments are conducted to investigate the key parameters affecting the optimal decisions where a case study based on real data is presented.

Review on the Implementation of the Consumer Act of the Philippines: Insights to Its Plausible Future

As a developing Southeast Asian nation, the Philippines have experienced economic growth, leading to challenges in ensuring consumer protection. This study reviewed the level of implementation of Consumer Act of the Philippines (Act) and explored insights to its plausible future. This used both quantitative and qualitative components. This was conducted in Capiz. For the survey, respondents comprised of consumers buying in Roxas City supermarkets and grocery stores selling basic commodities. For Focus Group Discussion (FGD), business owner representative, Department of Trade and Industry implementers, and consumer organization members participated. For the challenges encountered in Act’s implementation, respondents believed that the law protects their rights, but they lacked awareness of how to enforce it with perceived weaknesses on Act’s effectiveness in enforcing penalties. For the level of implementation, respondents believed that the Act effectively ensured the quality and safety of consumer products in the market, reduced deceptive, unfair, and conscionable sales acts or practices, provided efficient resolution for valid warranty claims, protected against misleading or deceptive packaging techniques, holds businesses accountable for product and service imperfection, prevents misleading advertisements and fraudulent sales promotion practices, regulates service and repair enterprises, and ensures effective consumer complaints handling. Consumers perceived that Act's provision on penalties was inadequate, ineffective in addressing broader issues, inadequately implements provision on warranties, labeling, and fair packaging, no provision on claims for damages, with gaps in addressing issues on sales promotion, service, and consumer complaints handling. Participants highlighted the need to promote consumer education, clearer guidelines on acceptable sales practices, and areas for improvement in online marketplaces, consumer awareness, and enhanced enforcement capabilities. Overall, strengthened consumer advocacy, enforcement training, and education, provision of harsher penalties, collaboration with other stakeholders, enhanced screening measures on online shopping platforms, and streamlined online dispute resolutions.

Proactive product warranty service planning and control: unravelling the boons of customer-generated content and multi-frequency analyses

Proactive warranty service problems planning and control serve a crucial role in service continuity and sustainability. In this regard, for the majority of manufacturers, predicting warranty claims for complicated goods is a reliability problem. The prediction of warranty claims is a complex task that also inherently possesses ambiguity, uncertainty, and volatility due to various factors. This study tries to overcome these challenges by providing a unique hybrid forecasting technique and experimenting with the use of social media data to improve the accuracy of warranty claims forecasts. We have established a collaborative partnership with a provider of automobile product services to curate a comprehensive dataset comprising two distinct types of data: (1) internal operational data and (2) social media data sourced from Twitter and Facebook. The proposed algorithm exhibits a high level of proficiency in predicting warranty claims and demonstrates robustness in effectively handling various forms of time series data that display multifarious statistical characteristics. Empirical Wavelet Transform (EWT), Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and a Bayesian optimisation algorithm for optimising the shaped Deep LSTM-CNN hyperparameters make up the proposed approach. It is shown that using EWT to provide multi-frequency analysis, LSTM-CNN combination to capture both short- and long-term memory of the data, and the utilisation of social media data significantly improve the efficacy of out-of-sample predictions and counteract the impact of the “warranty data maturation” phenomenon. The suggested algorithm exhibits a decrease in Root Mean Square Error (RMSE) ranging from 29.13% to 90.64% compared to other advanced benchmark models.

Electro Care Hub: Revolutionizing Warranty Services and Electronic Commerce

The Electro Care Hub is essentially a comprehensive system made to make using electronics easier and more enjoyable. It functions as a central hub that comprehends and anticipates the needs of its consumers by utilizing sophisticated algorithms and machine learning skills. The Electro Care Hub provides customized services to match your needs, whether you're a corporation looking for effective electronics management solutions or a tech enthusiast looking for the newest devices. The Electro Care Hub serves as a reliable resource for individual customers, helping them navigate the complicated world of electronics sales. It provides tailored recommendations, making sure that every purchase reflects the user's needs and preferences, by examining browsing history, product ratings, and user preferences. The package of products and services offered by the Electro Care Hub, which are designed to simplify electronics management operations, can also be very beneficial to businesses. Businesses are empowered by the Electro Care Hub to lower expenses, eliminate downtime, and improve customer satisfaction by centralizing electronic maintenance procedures. Customers are frequently overloaded with options, and companies find it difficult to handle warranty claims and upkeep. However, the introduction of the Electro Care Hub is expected to change this environment. Keyword: HTML, CSS, JavaScript, Jsp Servelets.

Non-renewable warranty cost analysis for dependent series configuration with distinct warranty periods

A warranty product often has an interval structure, resulting in different warranty periods for each component due to their distinct degradation paths. From the manufacturer’s perspective, it is reasonable to establish appropriate warranty periods for each part to achieve cost savings. This paper introduces a dependent series configuration consisting of a main component and an auxiliary component. The failure of the main component leads to system failure, while the failure of the auxiliary component only causes a random damage to the main component. These two components follow different Wiener degradation paths, and then their first passage times (FPTs) follow disparate inverse Gaussian distributions. Assuming a pre-deterministic warranty period, W, for the main component, and ηW,0<η<1, for the auxiliary component, the warranty period can be divided into two stages: [0,ηW] and [ηW,W]. In this context, the paper proposes warranty claim policies for replacement, objective-oriented imperfect repair (OOIR), and refund. The corresponding warranty costs sustained by manufacturer and consumer within these two stages are considered. Finally, a numerical example is presented to illustrate the warranty costs sustained by manufacturer and consumer under different scenarios, as well as the total warranty costs.

The Ten-Year Guarantee of the Contractor and the Engineer on Ensuring the Durability of the Building in the System of Applying the Saudi Building Code: A Comparative Study

This study aims to clarify the personal civil liability of the contractor and engineer for the damage and demolition in buildings and facilities and the defects that may appear during the warranty period. The general rules in civil liability were not sufficient in construction and building. During a warrant on the building, the negative result may appear as complete or partial demolition or defects that threaten its safety and durability. This changes the purpose for which it was established, whether in the national economy or compromising public security and public tranquillity. This also varies from a threat to individuals and their money. This pushed the legislators, including the Saudi regulator, to decide on a set of exceptional guarantees characterized by strictness consistent with the tragedies resulting from the collapse of buildings in whole or in part, from multiple aspects and effects. The most important of these guarantees is the decimal responsibility or the decimal guarantee that the Saudi regulator has imposed in Article (8) of the Saudi Building Code application system and clarified by Article (29) of the Executive Regulations for the Saudi Building Code Application System. We have adopted in the research: the descriptive, analytical, and comparative approach of the relevant texts in the system of application of the Saudi building code on which the study is focused, which is the case of the responsibility of the contractor and the engineer, for any demolition or defect in the construction after the issuance of the occupancy certificate, compared to some Arab legislation, which is the Egyptian Jordanian and Bahraini. This study discusses the nature of the decimal guarantee and its duration. Then, we focus on the provisions of the decimal guarantee. The study recommended that the Saudi regulator stipulates the warranty claim against the contractor and engineer. The lawsuit occurs after three years have passed since the demolition occurred or the defect was discovered, contrary to what was mentioned in the Saudi Civil Transactions System, which requires ten years to pass, because the ten-year liability is a private liability. The solidarity between the contractor and the engineer should not be limited to joint liability but should extend to include solidarity in the guarantee. &#x0D; &#x0D; Received: 16 December 2023 / Accepted: 19 February 2024 / Published: 5 March 2024

Modernizing Notice of Breach Rules to Preserve Contract Remedies

Recently, the legal community has scrutinized the capacity of mandatory arbitration rules to deter or foreclose claims for breach of contract. But little attention has been paid to express and constructive notice of breach rules that are just as effective at foreclosing contractual remedies. While four-year statutes of limitations are typically viewed as the default cutoff time for breach of contract claims, contracting parties, particularly buyers of goods, must act much sooner to preserve their legal remedies. It is now common practice for sellers to require notice of breach within days or weeks of their performance as an express condition precedent to buyers’ right to a remedy. Even in the absence of express notice rules, state laws require that buyers provide notice to sellers within a reasonable timeframe when they discover, or should have discovered, the breach. Failure to provide proper notice bars all buyers’ remedies. In effect, failure to satisfy the technical requirement of notice routinely produces forfeiture of contract remedies for the buyer. Such a forfeiture is contrary to the foundational doctrinal promise of adequate remedies for breach, anti-forfeiture rules, and the substantial performance rule for constructive conditions. Judges adjudicating notice defenses rely on an antiquated legal framework, crafted more than a century ago in a vastly different commercial environment. When the notice requirement was codified in 1906, it impacted merchant buyers who contracted directly with sellers for specific goods. Caselaw shows that sellers raised a notice defense when they sued buyers for the contract price, and that buyers sought an offset to damages by arguing that sellers provided defective goods. In the early twentieth century, courts routinely granted the damages offset for breach of promise, even when notice was untimely. Now, notice issues often arise in adhesive transactions in which buyers contract with downstream sellers of mass-produced goods such as vehicles, food products, dietary supplements, drugs, and medical devices. Sellers are usually aware of the breach or face no repercussions from buyers’ failure to provide notice. Product testing, customer complaints, post-sale audits, lawsuits, regulatory policing, and warranty software or warranty claims often give sellers actual notice of their defective performances. Yet judges continue to insist on individualized and particularized notice from each buyer. Judges theorize that sellers will be robbed of their legal rights to cure or settle claims, prepare defenses, or know their terminal point of liability, even though sellers’ curative or defensive interests are unimpaired. This judicial insistence on notice in the current commercial environment ignores how sellers and buyers respond to breach events. It also incentivizes sellers to fabricate and market defective products because only a small percentage of buyers will complain, and even fewer will satisfy the notice rule. This Article proposes that judges adjudicate notice defenses within the broader framework of the parties’ agreement, contract doctrine, and new commercial realities. Specifically, it proposes that judges require sellers to prove material harm when they seek to forfeit buyers’ substantive remedies on technical notice-failure grounds. This new standard would provide uniformity in the law and replace the ad hoc exceptions judges have used to avoid the harsh effects of pre-suit notice. A notice-prejudice requirement would also encourage sellers to create better products and honor the warranties they provide when marketing their goods.

TWO-DIMENSIONAL MODELING OF CAR RELIABILITY DURING WARRANTY PERIOD

The paper focuses on presenting the concept of two-dimensional modeling of passenger car reliability during the warranty period. The main objective of this paper is to detect the regularity in the intensity of the number of first failure reports during the warranty period. The two-dimensional distribution of the time and mileage of failure-free exploitation is estimated. The period from the date of purchase to the first warranty repair is analysed. The concept presented incorporates the existing state of knowledge on two-dimensional warranties, expanding it through the use of a nonparametric approach and probability smoothing with the use of P-splines. The estimation involved censored data, i.e., data on vehicles that were not submitted for warranty repair within the warranty limits of time and mileage. The originality of this paper entails the combination of a nonparametric approach with probability smoothing. The statistical analyses presented in the paper were carried out on a population of 1005 vehicles of two car brands sold and serviced in 2011-2021 at the Authorized Service Station (Dealership). There were sales, repair, and warranty claim databases.

A finite mixture model for multiple dependent competing risks with applications of automotive warranty claims data

A finite mixture model for multiple dependent competing risks with applications of automotive warranty claims data

Phase-type distributions for product return data with two-layer censoring

Abstract Product return data, such as warranty claims, are usually subject to two layers of right censoring. The first layer, called warranty censoring, applies to the product lifetime due to a fixed warranty limit. The second layer, called end-of-study censoring, applies to the sum of the sales lag and the lifetime due to the end-of-study date for the data collection. The two-layer censoring in the product return data renders traditional nonparametric methods for right-censored data inapplicable. This study develops a generic method for the two-layer censored data using acyclic phase-type distributions (APHDs) in the canonical form. The APHD estimators can be regarded as nonparametric sieve estimators since the family of APHDs is dense in the field of all positive-valued distributions. Based on the property that the class of APHDs is closed under convolution, a dedicated expectation-maximisation algorithm is proposed to compute the maximum likelihood estimators. Comprehensive simulations are conducted to evaluate the performance of the proposed method and compare it with the inverse probability of censoring weighted approach, which is applicable in the absence of warranty censoring. Two real examples from production-delivery supply chains are analysed by the proposed method to provide guidance on warranty reserve management for the manufacturers.

Data‐driven framework for warranty claims forecasting with an application for automotive components

AbstractAutomakers spend billions of dollars annually towards warranty costs, and warranty reduction is typically high on their priorities. An accurate understanding of warranty performance plays a critical role in controlling and steering the business, and it is of crucial importance to fully understand the actual situation as well as be able to predict future performance, for example, to set up adequate financial reserves or to prioritize improvement actions based on expected forthcoming claims. Data maturation, a major nuisance causing changes in performance metrics with observation time, is one of the factors complicating warranty data analysis and typically leads to over‐optimistic conclusions. In this paper, we propose a sequence of steps, decomposing and addressing the main reasons causing data maturation. We first compensate for reporting delay effects using a Cox regression model. For the compensation of heterogeneous build quality, sales delay, and warranty expiration rushes, a constrained quadratic optimization approach is presented, and finally, a sales pattern forecast is provided to properly weigh adjusted individual warranty key performance indicators. The results are shown to dramatically improve prior modeling approaches.

Dynamic monitoring of polynomial profiles with attribute responses and between-profile correlation

Profile monitoring is a popular statistical process control problem in recent years. In many applications, quality characteristics of interest are attribute data due to the inherent feature of processes or limitation of data collection costs. The correlation among data is becoming more significant, since data collection intervals are becoming shorter in the big data era. However, research on monitoring profiles with attribute responses in the presence of Between-Profile Correlation (BPC) has received relatively scant attention. Motivated by a real example of automobile warranty claims, this article aims to monitor polynomial profiles with attribute responses and BPC. The generalized polynomial model and the learning curve model are adopted to characterize the profile relationship and the correlation between profiles, respectively. Then, an EWMA chart with dynamic control limits (dEWMA) is developed. Simulation studies show that ignoring the BPC does not affect the in-control performance of the chart with dynamic control limits, but does have devastating effects on the out-of-control performance. The proposed dEWMA chart can address the impact of correlation and provide superior monitoring performance compared with some competitors. Finally, a real example of warranty claims data is presented to illustrate the implementation of the proposed chart.

Product Quality Augmentation Through Agile Operation: A Critical perspective on Supply Chain Capabilities on Reducing Operations Cost

This study focuses on the impact of product quality improvement and supply chain capabilities on reducing operational costs through agile operation. It highlights the significance of adopting agile operation principles and practices to enhance product quality, optimize supply chain operations, and achieve cost efficiencies. The study underlines the importance of continuous improvement processes, such as Lean Six Sigma, in identifying and eliminating inefficiencies, defects, and waste to improve product quality and reduce costs associated with rework and warranty claims. Additionally, it emphasizes the role of agile supply chain capabilities in minimizing inventory carrying costs, production disruptions, and transportation expenses through efficient inventory management techniques. The research emphasizes that integrating product quality improvement and agile supply chain capabilities drives down operational costs by streamlining processes, reducing waste, and fostering a culture of continuous improvement. Overall, this study highlights the critical role of product quality improvement and supply chain capabilities in reducing operational costs and achieving operational excellence through agile operation practices.

A Snapshot-Stacked Ensemble and Optimization Approach for Vehicle Breakdown Prediction

Predicting breakdowns is becoming one of the main goals for vehicle manufacturers so as to better allocate resources, and to reduce costs and safety issues. At the core of the utilization of vehicle sensors is the fact that early detection of anomalies facilitates the prediction of potential breakdown issues, which, if otherwise undetected, could lead to breakdowns and warranty claims. However, the making of such predictions is too complex a challenge to solve using simple predictive models. The strength of heuristic optimization techniques in solving np-hard problems, and the recent success of ensemble approaches to various modeling problems, motivated us to investigate a hybrid optimization- and ensemble-based approach to tackle the complex task. In this study, we propose a snapshot-stacked ensemble deep neural network (SSED) approach to predict vehicle claims (in this study, we refer to a claim as being a breakdown or a fault) by considering vehicle operational life records. The approach includes three main modules: Data pre-processing, Dimensionality Reduction, and Ensemble Learning. The first module is developed to run a set of practices to integrate various sources of data, extract hidden information and segment the data into different time windows. In the second module, the most informative measurements to represent vehicle usage are selected through an adapted heuristic optimization approach. Finally, in the last module, the ensemble machine learning approach utilizes the selected measurements to map the vehicle usage to the breakdowns for the prediction. The proposed approach integrates, and uses, the following two sources of data, collected from thousands of heavy-duty trucks: Logged Vehicle Data (LVD) and Warranty Claim Data (WCD). The experimental results confirm the proposed system’s effectiveness in predicting vehicle breakdowns. By adapting the optimization and snapshot-stacked ensemble deep networks, we demonstrate how sensor data, in the form of vehicle usage history, contributes to claim predictions. The experimental evaluation of the system on other application domains also indicated the generality of the proposed approach.

Monitoring aggregate warranty claims with dynamically designed CUSUM and EWMA charts

Statistical monitoring of warranty claims data using dynamic probability control limits has been shown to be effective in early detection of unforeseen reliability problems that emerge at the design and manufacturing phases. As the discrepancy between abnormal patterns and the normal pattern in aggregate warranty claims is usually small (especially at the early stage), we develop two new dynamic monitoring schemes that adopt CUSUM-type and EWMA-type statistics, named DyCUSUM and DyEWMA, respectively, to better address the warranty claims monitoring problem. Three effective algorithms – that is, the Monte Carlo simulation, Markov chain, and near-enumeration algorithms – are proposed to progressively determine control limits for the two schemes. In particular, comparison studies show that the near-enumeration algorithm can attain a higher approximation accuracy with a lower computational burden and is thus recommended. In-depth simulation experiments are then conducted to assess the performance of the schemes. We find that the DyEWMA scheme has superior and robust detection performance in various situations, whereas the DyCUSUM scheme is less effective and could even be ineffective in certain cases, compared with a Shewhart-type counterpart. Some specific suggestions are also provided to facilitate implementation of the proposed monitoring schemes. Improved schemes by combining the moving window approach to mitigate the ‘inertia’ problem is further discussed. Finally, a real case study is presented.

Analisis Kualitatif pada Komunitas Gamers Surabaya dalam Memutuskan Pembelian Headset Gaming Merek Fantech

In this increasingly modern era, the increasing popularity of electronic esports, commonly known as E-sports, has become a magnet for some people to try playing games. Accessories or additional game equipment, including keyboards, mice, headsets, and mousepads, are often called gaming gear. Fantech is a product developed by a peripheral gaming company from Indonesia founded in 2009 by three brothers. Researchers are interested in examining how a Fantech Gaming Headset Brand Image as a Brand or Gaming Headset Brand. Using qualitative analysis, it was found that product trust, benefits, service, and price are the hallmarks of the Fantech gaming headset product. Risk factors have the lowest average score, which explains that Fantech gaming headset products have a high risk of product damage, which can make high warranty claims.

An Event Based Digital Forensic Scheme for Vehicular Networks

The software in today's cars has become increasingly important in recent years. The development of high-tech driver assistance devices has helped fuel this movement. This tendency is anticipated to accelerate with the advent of completely autonomous vehicles. As more modern vehicles incorporate software and security-based solutions, "Event-Based digital forensics," the analysis of digital evidence of accidents and warranty claims, has become increasingly significant. The objective of this study is to ascertain, in a realistic setting, whether or not digital forensics can be successfully applied to a state-of-the-art automobile. We did this by dissecting the procedure of automotive forensics, which is used on in-car systems to track the mysterious activity by means of digital evidence. We did this by applying established methods of digital forensics to a state-of-the-art car.Our research employs specialized cameras installed in the study areas and a log of system activity that may be utilized as future digital proof to examine the effectiveness of security checkpoints and other similar technologies. The goal is to keep an eye on the vehicles entering the checkpoint, look into them if there is any reason to suspect anything, and then take the appropriate measures. The problem with analyzing this data is that it is becoming increasingly complex and time-consuming as the amount of data that has been collected keeps growing. In this paper, we outline a high-level methodology for automotive forensics to fill in the blanks, and we put it through its paces on a network simulator in a state-of-the-art vehicle to simulate a scenario in which devices are tampered with while the car is in motion. Here, we test how well the strategy functions. Diagnostics over IP (Diagnostics over IP), on-board diagnostics interface, and unified diagnostic services are all used during implementation. To work, our solution requires vehicles to be able to exchange diagnostic information wirelessly.These results show that it is possible to undertake automotive forensic analysis on state-of-the-art vehicles without using intrusion detection systems or event data recorders, and they lead the way towards a more fruitful future for automotive forensics. The results also show that modern autos are amenable to forensic automotive analysis.

Clustered Coefficient Regression Models for Poisson Process with an Application to Seasonal Warranty Claim Data

Motivated by a product warranty claims dataset, we propose clustered coefficient regression models in a nonhomogeneous Poisson process for recurrent event data. The proposed method, referred as CLUPP, can estimate the group structure and parameters simultaneously. In our proposed method, a penalized regression approach is used to identify the group structure. Numerical studies show that the proposed approach can identify the group structure well, and outperforms traditional methods such as hierarchical clustering and K-means. We also establish theoretical properties, which show that the proposed estimators can converge to true parameters in high probability. In the end, we apply our proposed methods to the product warranty claims dataset, which achieve better prediction than the state-of-the-art methods.

Electric Vehicle Lithium-ion Battery Ageing Analysis under Dynamic Condition: A Machine Learning Approach

Currently, the smart cities, smart vehicles, and smart gadgets will improve the way of living standard. Cloud connectivity of IoT sensed devices will capture real-time data in the cloud which helps to improve the system performance and quick response to queries. Electric Vehicle battery health diagnosis plays an important role in the proper functioning of the battery management system, guarantees safety, and warranty claim. Society 5.0 develops with the advancement in the road, infrastructure, better connectivity, transportation, and options available to purchase. Battery health cannot be measured directly. There are internal and external factors that affect battery health such as State of Charge, model parameters, charging/discharging method, temperature, Depth of Discharge, C-rate, battery chemistry, form factor, thermal management, and load change effect. Battery degrades due to both calendar ageing and cyclic ageing. Artificial Intelligence plays a significant role in Battery management system due to the nonlinear behavior of lithium-ion battery. Prediction of battery health accurately and in due time will reduce the risk of recklessness. Timely maintenance will reduce the risk of fatal accidents. This paper presents different batteries analysis under different discharge voltage and capacity conditions. Different machine learning algorithms such as Neural Network, Modified Support Vector Machine (M-SVM) and Linear Regression are used to predict state of health. The proposed M-SVM performs well with less error for all four-battery discharge data.