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In the automotive industry, some vehicles, failed vehicles, cannot be produced according to the planned schedule due to some reasons such as material shortage, paint failure, etc. These vehicles are pulled out of the sequence, potentially resulting in an increased work overload. On the other hand, the reinsertion of failed vehicles is executed dynamically as suitable positions occur. In case such positions do not occur enough, either the vehicles waiting for reinsertion accumulate or reinsertions are made to worse positions by sacrificing production efficiency. This study proposes a bi-objective two-stage stochastic program and formulation improvements for a mixed-model sequencing problem with stochastic product failures and integrated reinsertion process. Moreover, an evolutionary optimisation algorithm, a two-stage local search algorithm, and a hybrid approach are developed. Numerical experiments over a case study show that while the hybrid algorithm better explores the Pareto front representation, the local search algorithm provides more reliable solutions regarding work overload objective. Finally, the results of the dynamic reinsertion simulations show that we can decrease the work overload by 20% while significantly decreasing the waiting time of the failed vehicles by considering vehicle failures and integrating the reinsertion process into the mixed-model sequencing problem. [ABSTRACT FROM AUTHOR]

Subaqueous mass transport deposits (MTDs) attributed to the Mw 6.1 1935 CE Témiscaming earthquake were mapped at 17 sub-bottom acoustic profile survey areas on 11 lakes near Témiscaming, Quebec. Distributed over about 1270 km2, MTDs are the product of shallow failures, up to several metres thick, that occurred along planar surfaces and involved primarily lacustrine sediments. Core samples of unfailed deposits indicate that the failure planes occurred within soft sediments at the top of a glaciolacustrine unit or at the base of overlying lacustrine deposits. Radioisotope dating of sediment samples from six coring sites on Tee and Kipawa lakes confirm that the MTDs are the product of failures triggered by the 1935 CE earthquake. To assess the application of such a mapping study to a paleoseismic investigation, the minimum magnitude of an earthquake that can generate an MTD distribution of 1270 km2 was extrapolated from a published empirical plot. The resulting magnitude of Mw/Ms 5.7–5.8 is less than the instrumental Mw 6.1 magnitude and deemed a reasonable estimation of minimum earthquake magnitude. The distribution of MTDs triggered by the 1935 CE earthquake forms the only such signature within the Témiscaming study area since roughly 8 ka cal B.P. The lack of an analogous, older signature(s) is consistent with the absence of equivalent shaking to the 1935 CE earthquake over this period, but the actual timespan may be shorter and begin when gyttja deposits on slopes became thick enough to be prone to failure from such an event. [ABSTRACT FROM AUTHOR]

This study investigates the design of additive manufacturing for controlled crack propagation using process parameters and lattice structures. We examine two lattice types—octet-truss (OT) and diamond (DM)—fabricated via powder bed fusion with Ti-6Al-4V. Lattice structures are designed with varying densities (10%, 30%, and 50%) and process using two different laser energies. Using additive-manufactured specimens, Charpy impact tests are conducted to evaluate the fracture behavior and impact energy levels of the specimens. Results show that the type of the lattice structures, the density of the lattice structures, and laser energy significantly influence crack propagation patterns and impact energy. OT exhibits straighter crack paths, while DM demonstrates more random fracture patterns. Higher-density lattices and increased laser energy generally improve the impact energy. DM consistently outperformed OT in the impact energy for angle specimens, while OT showed superior performance in stair specimens. Finally, a case study demonstrates the potential for combining OT and DM structures to guide crack propagation along predetermined paths, offering a novel approach to protect critical components during product failure. [ABSTRACT FROM AUTHOR]

Polyolefins have a multitude of uses across packaging, automotive and construction sectors. Their resistance to degradation during reprocessing enables recyclability, but variability in recycled polymer feedstocks renders it difficult to assure their manufacturing suitability. The lack of quality control methods has disabled circular economy pathways; product failure is costly, wasteful and time-intensive. Using rheology-simulated and extrusion-based recycling experiments, we explore the degradation pathways of high-density polyethylene (HDPE). Chain scission dominates during the initial degradation of HDPE, and increasing exposure to O2 shifts the dominant mechanism to long-chain branching. Importantly, extending this method to post-consumer recyclate (PCR), the results show potential as a methodology to assess recyclate quality to enable a circular plastics economy. In this study, we establish the validity of this rheology simulation to define a characteristic degradation parameter, relating it to the structural evolution under different environments defined for virgin HDPE and post-consumer recyclate (PCR). Polyolefins are used across packaging, automotive and construction but variability in recycled polymer feedstocks renders it difficult to assure a consistent manufacturing quality. Here, the authors use rheology-simulated and extrusion-based recycling experiments to explore the degradation pathways of high-density polyethylene and present a rheology-based method to assess the quality of the recycled material. [ABSTRACT FROM AUTHOR]

Customer perception is an important consideration factor in evaluating the quality of human-computer interaction services. Sustainable user experiences and marketing strategies can be created by analyzing customer perception. By understanding consumer satisfaction with product services in the customer perception area, appropriate product service failure prevention strategies can be formulated. A service failure evaluation model is proposed in this study, which considers the customer tolerance area to accurately evaluate consumers' behavioral experiences from purchasing to using products. The concept of tolerance area is introduced, and a combination of the fuzzy Failure Mode and Effect Analysis (FMEA) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is used to construct a human-computer interaction service failure evaluation model. Potential service failure factors of smart speakers are accurately evaluated by this model, and these service failure factors are ranked within the tolerance area. The research identifies voice misinterpretation and signal connectivity issues as the primary risk factors impacting the quality of human-computer interaction for smart speakers. The application of this method not only enhances the evaluation of smart speaker human-computer interaction services quality but also aids in the precise identification and prioritization of critical failure modes. The proposed service failure prevention strategies can reduce consumer dissatisfaction and provide innovative references for smart product design and marketing. The findings bolster empirical evidence for service failure prevention strategies in smart products and pave the way for novel perspectives on enhancing the quality of human-computer interaction services. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Many industries are plagued by economic losses and product failures caused by counterfeit goods. Therefore, advanced anti‐counterfeiting techniques are continuously needed. In this study, we constructed a series of acid‐base sensitive cyclic chalcone dyes A—F by modifying different electron‐donating groups. Differences in acid sensitivity of different structures are well rationalised by NMR and theoretical calculations. Aniline is difficult to protonate than fatty amines, so there is a difference in fluorescence. Hiding and anti‐counterfeiting of information is achieved by this phenomenon. Powder X and Y are the anti‐counterfeit fluorescent powder containing montmorillonite and cyclic chalcone, which have orange fluorescence and the very similar appearance. However, under the influence of acid the Powder X containing triphenylamine modified cyclic chalcone shows red shifted fluorescence and Powder Y containing morpholino and diethylamino groups modified cyclic chalcone shows blue shifted fluorescence. Therefore, the anti‐counterfeiting strategy based on cyclic chalcone is not only limited to UV‐irradiated fluorescence development, but also has more colorization and pattern variations with the aid of acid developer. Data encryption and decryption of numbers, English alphabets and Chinese characters have been realized using A—F, which have great potential for practical applications. [ABSTRACT FROM AUTHOR]

The hybrid method, known as Incremental Sheet Hydro Forming (ISHF), is a combination of the techniques of Incremental Sheet Forming and Sheet Hydro-Forming. The primary concern identified in the incremental sheet forming formation strategy relates to the potential failure of the product due to the thinning of the sheet and subsequent springback. In response to the issue of sheet failure resulting from thinning, a revised iteration of the integrated sheet hydroforming (ISHF) method was proposed. The revised version of the ISHF process has demonstrated notable improvements in the malleability of the material. The ISHF technique entails the movement of a single ball tool along one side of the sheet's surface, while hydraulic support is applied on the opposite side through the use of pressurized hydraulic fluid. The present study sought to investigate the impact of hydraulic support on metal formability and thickness distribution. In addition, a modified variant was also considered. The experimental results are in close agreement with the predictions made by the analytical models. The strain distribution throughout the length of deformation for the sheet has been calculated. The surface quality of the products was found to be satisfactory and a preliminary simulation has been performed. This study examines the influence of process factors, specifically spindle speed (1000/1500/2000 RPM), feed rate (400/600/800 mm/min), tool diameter (8/10/12 mm), and step-down (0.2/0.4/0.6 mm), on the cone-shaped feature at the specimen of aluminum alloy A 5010. The results demonstrated that, through analysis of variance, the most influential factor in the distribution of thickness was speed. Regarding formability, the rate of change was found to be the highest at 50%. [ABSTRACT FROM AUTHOR]

This research explores consumer reactions following green product failures, identifying a novel benefit for companies selling environmentally friendly products. Across an empirical field analysis and eight controlled experiments, the authors show that consumers react less negatively to the failure of green products than conventional ones, which is referred to as the greenguard effect. The findings suggest that by not reacting negatively to green product failures, consumers believe they are being more prosocial, as their negative reaction may harm the success of a product that otherwise benefits the environment and society. This research contributes to the literature on green products by highlighting a novel benefit of green product attributes and demonstrating how prosocial motives influence consumer reactions to green product failures, and offers valuable insights for marketers on green product marketing. [ABSTRACT FROM AUTHOR]

Understanding how organizations respond to failure is important to management research, yet prior studies have offered contrasting findings for whether, in a multiunit hierarchical organization, a corporate office improves business unit search following product failure. To better understand how a corporate office affects business unit search, we focus on the role of corporate proximity (hierarchical, geographic, and cognitive) between the corporate office and constituent units. We argue that corporate proximity improves a business unit's local search process through two mechanisms—vertical linkages and corporate attention—that positively condition the likelihood of persisting; that is, reentering a product market after having experienced a prior product failure in that market. We find support for our theory using data on reentry in the U.S. medical device industry following exit from the market due to product failure. We also explore how age of the product market and characteristics of the failure—cause and severity—further moderate corporate proximity's role in business unit reentry. Overall, our study offers a better understanding of how complex organizations respond to failure, thereby contributing to literatures on search, corporate headquarters, and product entry. [ABSTRACT FROM AUTHOR]

Major hysteresis loops of the F/NM/F/AF structure are classified according to the magnetization process, with the assumption of coherent rotation for each F component and antiferromagnetic coupling between the two F layers. Magnetic stable states of the system as well as specific reversal modes of magnetization during each stage of the major hysteresis cycle are studied in detail based on energetics analysis, in the whole range of exchange bias field and interlayer antiferromagnetic coupling strength. The analysis shows 12 different types of major hysteresis loops for this system and is confirmed by simulation. Strategies to determine key material parameters for the F/NM/F/AF structure from major hysteresis loops are proposed and illustrated by numerical simulation. The research shows a subtle tuning of the magnetization process in the F/NM/F/AF structure, collectively by exchange biasing and interlayer antiferromagnetic coupling. Practically, this serves as a theoretical grounding for the identification of root causes of failure in the product analysis of GMR (giant magnetoresistance) sensors. [ABSTRACT FROM AUTHOR]

More companies are engaging with consumers in real-time on digital platforms, which may lead to accidental or unintentional sharing of messages. Accordingly, how to manage online brand crises has become an increasingly important issue for marketing managers. The present research explores how online brand blunders influence consumers' trust and liking toward the blunderer brand, and the role of brand commitment in this relationship. Three studies show that consumers evaluate online brand blunders differently than they do product performance problems. Specifically, upon receiving negative brand blunder information, high (vs. low)-commitment consumers' brand trust and brand liking decrease to a higher extent due to finding the blunder less humorous and more offensive. On the contrary, upon receiving negative product performance information, low (vs. high)-commitment consumers' brand trust and brand liking decrease to a higher extent, which supports previous literature. Our findings suggest that managers should prioritize high and low-commitment consumers differently and tailor blunder communication in handling online brand crises. [ABSTRACT FROM AUTHOR]

Although much research has examined chatbot interactivity as one of the most human-like qualities, replicating a conversation norm in human-to-human dialogue, far less has examined the "native state" of two-way communication between humans and chatbots. This study fills the gap by substantiating a synchronous two-way conversation between users and chatbots and testing how chatbot interactivity shapes the users' perceived empathy. Guided by the computers-are-social-actors (CASA) paradigm, like skilled customer service representatives interacting with customers during product failures, this study designs a between-subject experiment (N = 300) to embody the warm and competent types of human conversation and suggests two versions of chatbot interactivities: social interactivity (high/low) and message interactivity (high/low). We further investigate whether a chatbot's warm or competent persona manifested in its interaction with consumers elicits empathic responses from consumers, such as calming down their anger in line with social response theory. As a result, both social and message interactivity in chatbots effectively elicit users' perception of empathy, alleviating customer anger and reducing adverse word-of-mouth (WOM) intentions. The findings provide empirical evidence that supports the explanatory framework of social response theory. This research demonstrates how technological features, particularly interactivity, contribute to creating experiential value for customers. Specifically, it elucidates how customers perceive empathy displayed by chatbots, which subsequently influences their level of anger and inclination to engage in negative word-of-mouth communication. Notably, these results offer novel insights into the roles of chatbot interactivity and empathy as psychological mechanisms that enable consumers to express their dissatisfaction by interacting with chatbot service agents, particularly in situations involving product failures. The implications of this study extend to the practical realm, providing valuable guidance on the design and implementation of empathetic chatbots in frontline consumer service contexts. [ABSTRACT FROM AUTHOR]

We investigate the role of financial analysts in product quality failures. Relying on information about product recalls, we first show that analyst coverage on average reduces product quality, particularly when managers face greater short-term pressure from institutional investors. However, after identifying a subgroup of analysts who raise questions on product-related issues in earnings conference calls, we find that coverage by these "product analysts" enhances rather than compromises product quality. Firms with greater product analyst coverage are also more likely to retire low-quality products. Additional analysis demonstrates that product analysts help safeguard product quality by further probing into product-related matters and issuing more timely recommendation downgrades after firms announce product deficiencies. [ABSTRACT FROM AUTHOR]

Purpose: The industrial revolution changed the market landscape significantly in all industrial sectors. It has a noteworthy impact on enhancing the quality of goods and services. The quality aspect is of utmost concern and determines the success or failure of any product. Therefore, the presented study analyses the key barriers and solutions of Quality 4.0. Design/methodology/approach: Twenty barriers and fifteen solutions were identified using a literature review and investigated using a hybrid approach. Barrier weights were evaluated with the help of the fuzzy AHP method. Furthermore, the computed weights were used to perform computations in the next step using fuzzy-TOPSIS to prioritize the ranking of identified solutions. Findings: The research results show that "Lack of applying advanced analytics to uncover Quality 4.0 initiatives" and "Lack of integrating data from various sources across the organization" are the topmost barriers. Furthermore, "Implement a leadership development program focused on Quality 4.0" and "Cross-departmental peer learning environment" are the topmost solutions. Practical implications: Managers and industrialists can benefit from Quality 4.0 through improved decision-making, process efficiency, supply chain collaboration, agile quality management, enhanced customer experience and a culture of continuous improvement. This results in better quality, operational effectiveness and a competitive edge. Originality/value: The solutions need to be mapped with barriers to adopting Quality 4.0. Furthermore, the research results involve novelty by prioritizing the solutions to overcome the anticipated barriers. [ABSTRACT FROM AUTHOR]

The manufacturing process is the last opportunity to build an ideal design reliability index into a product. With the advancement of intelligent manufacturing technology, the concept of quality evolves from conformance to fitness for use, which emphasizes that reliability should be built into product with quality control. To effectively implement reliability assurance in the manufacturing process, it is necessary to accurately identify the vital few characteristics that are critical to reliability. Thus, a heuristic key reliability characteristic (KRC) analysis in manufacturing model fusing big quality data is proposed. First, on the basis of the fusion big quality data in manufacturing-by-manufacturing system Reliability-operational process Quality- output product Reliability (RQR) chain, a data driven KRC analysis model is proposed, and a reliability proactive control framework in manufacturing driven by KRC is expounded. Second, considering mass quality and reliability data, an effective KRC identification method based on data mining using multi-objectives genetic algorithm (MOGA) is established. Third, considering manufacturing data and product failure risk, an extended risk priority number (RPN) for KRC ranking is proposed. Finally, an example of an insulating base of subway locomotive is provided to verify the proposed approach. • A novel KRC conceptual model is proposed. • A heuristic KRC identification approach based on MOGA is presented. • A KRC ranking approach based on extended RPN is proposed. • The proposed method is illustrated using an insulating base of subway locomotive example. [ABSTRACT FROM AUTHOR]

Predictors of organic cosmetic product purchase intention have been widely investigated. However, a company-CSR fit triggered from this business area has not been examined in purchase intention. In addition, company-CSR fit-driven positive CSR perception in several business areas such as tourism, banking, and pharmacy has been found to serve a buffer in a service failure. Whether CSR belief derived from a company-CSR fit in the organic cosmetic product business still generates the buffering effect. This study examines the buffering effect of CSR belief driven by the company-CSR fit in the context of service failure on brand attitude and purchase intention for organic cosmetic products. In addition, this study proposes a moderating role of health consciousness that could influence the buffering effect of CSR belief on brand attitude after a service failure. Using data from a sample of 257 respondents on Amazon Mechanical Turk, the study uses SmartPLS 3 to perform the partial least squares structural equation modelling (PLS-SEM). The results indicate that a company-CSR fit driven-CSR belief generates a buffering effect on brand attitude, resulting in the maintenance of purchase intention after a service failure. Results further show that health consciousness moderates this buffering effect on brand attitude. Particularly, consumers with high levels of health consciousness strengthen this buffering effect, while the buffer of CSR belief does not have an effect on consumers with low levels of health consciousness. These findings bring theoretical contributions and practical implications for the organic cosmetic product business. [ABSTRACT FROM AUTHOR]

Design Failure Mode and Effects Analysis (DFMEA) is a process to identify and mitigate risks of failure of a product to perform the intended function(s) for the customer. DFMEAs can be performed at all stages of design from product concept to system to component. Several issues with concept level design FMEAs have been identified by Henshall, et al in 2014: large documents, focus on components with poorly defined connections, focus on hardware rather than integrated electro‐mechanical systems. As a result of these challenges, improvements to the system‐level product concept are unlikely. In 2023 Genter and Bauer described a novel approach to eliciting design considerations representing the needs of both the customer and business using System Level Assessment. These design considerations form the basis for a concept level design FMEA. This approach was applied to a design concept for a technology that had not been previously developed. When compared to a concept DFMEA approach as part of Inclusive Customer Driven Conceptual Design defined by Hari and Weiss, the System Level Assessment based approach took 4.5 hours for the Critical System compared to 8 hours per concept for Inclusive Customer Driven Conceptual Design. When compared to a traditional Concept FMEA yielding 67% prevention tasks, the System Level Assessment Concept FMEA yielded 95% prevention tasks. [ABSTRACT FROM AUTHOR]

Purpose: This study examines the effect of stable institutional investors on firms' product quality failures. Furthermore, the authors investigate the channels through which institutional ownership stability enhances product quality management. Design/methodology/approach: This study uses probit, ordered probit and negative binomial regression frameworks to investigate the research questions. In addition, the authors utilize the three-stage least-squares to address the endogeneity issues. Findings: Using a sample of product recall incidents from 2012 to 2021, the authors find that firms with more stable institutional ownership have a lower probability, frequency and severity of recall incidents and adopt a proactive product recall strategy. Institutional investors with significant and persistent holdings improve quality management by reducing overinvestment and the use of option-linked and relative performance executive compensations. Furthermore, the influence of stable institutional owners on product quality failures is more pronounced in firms with low managerial ability and specialist CEOs. Lastly, the empirical evidence demonstrates that stable holdings by active investors have a more substantial impact on reducing product recalls than passive and other stable institutional holdings. Originality/value: This study is the first to examine the impact of institutional ownership stability on firms' product recalls. The authors contribute to the literature on the benefits of stable institutional ownership on firm outcomes and the determinants of product quality failures. [ABSTRACT FROM AUTHOR]

Generally, quality assurance (QA) functions are sized at the direction of management and are rarely sized commensurately with their need. Over the years, influenced strongly by in vogue attitudes and real-world circumstances the size of the QA function has exhibited extremes: ▪ Inordinately large after an embarrassing product failure, or an executive's overreaction (in the distant past, from attending an Edwards Deming seminar), or ▪ Completely eradicated when perceived to be unneeded, or too expensive. This article introduces quality efficiency indicators, which facilitate adequate sizing of the quality assurance function; i.e., sizing QA to the customer's need, or the producer organization's own quality goals. The interpretation and application of the indicators is explained, and a simple example is provided demonstrating the calculation for sizing the QA function. (A basic knowledge of Statistical Process Control, and statistics, specifically Confidence Interval, is helpful to the understanding of this article.) The quality assurance sizing process presented is broadly applicable to various industries and processes. The method presented in this paper assumes there is a semi-smooth flow of performance effort, and the requirement for quality assurance is not sporadic. [ABSTRACT FROM AUTHOR]

Purpose: This study examines handmade clothing consumption as a means of self-expression by exploring the interrelationships between consumers' self-expression, brand love and word of mouth. Design/methodology/approach: Using a descriptive research design, data were collected from 295 respondents in South Africa who posted about fashion on social media and who had bought handmade clothing in the 6 months prior to data collection. Structural equation modelling was used to examine the interrelationships between consumers' self-expression, brand love and word of mouth. Findings: Brand love intervenes between consumers' self-brand connections and word of mouth about handmade clothing. More specifically, brand love strengthens positive word of mouth online and mitigates negative word-of-mouth intentions following a handmade clothing product failure scenario. Research limitations/implications: The study enlightens scholarly understanding of consumers' self-expression motivations for using ready-made handmade clothing that results in brand love and positive word of mouth. Practical implications: Handmade clothing marketers who tap into consumers' self-expression and who can establish brand love among consumers can similarly create beneficial consumer–brand relationships. Originality/value: Consumers often use handmade clothing for the purpose of self-expression, which provides subsequent spin-offs for brands in the form of brand love and positive word of mouth. Objective self-awareness theory provides a parsimonious lens to reveal the important role that brand love plays as a mechanism to explain the linkage of consumers' self-brand connections to word of mouth about handmade clothing. [ABSTRACT FROM AUTHOR]

Product‐harm crises are discrete events in which product failures expose consumers to safety hazards. Firms facing such crises must legally recall their products to protect consumers from further harm. In this study, we examine the effects of product‐harm crises and their recall strategies on CEO turnover. We find that firms are more likely to replace their CEOs after issuing product recalls, especially for recalls that are proactive and that offer extensive corrective actions. We further find that firms with poor performance and with limited financial flexibility are more likely to dismiss their CEOs after product recalls. Our study contributes to the disciplines of accounting, finance, and management by documenting product‐harm crises are a strong predictor of CEO dismissal, that is, incremental to other measures of firm performance for U.S. companies. [ABSTRACT FROM AUTHOR]

This paper focuses on the reliability estimation of Weibull distributions with zero-failure data. Since no product failure occurred in the tests, the conventional maximum likelihood method was not applicable. Recent methods ignore the estimation of location parameter and tend to be conservative. This study developed a new estimation technique to address these problems. A prior model between the life dispersion boundary and shape parameter is constructed by considering the historical failure data of similar high-reliability products. The failure probabilities for all samples were inferred using the E-Bayesian method, after which the reliability was estimated. Afterward, a confidence interval for reliability was obtained based on the bootstrap confidence interval and modified maximum likelihood method. A Monte Carlo simulation study demonstrated that the proposed method is satisfactory in terms of point estimates, confidence intervals, coverage probabilities, and computational efficiency. Finally, a real engineering example is introduced to illustrate the application of this method. [ABSTRACT FROM AUTHOR]

"Planned obsolescence," broadly defined as conduct by manufacturers to shorten product lifespans and spur consumption, is characteristic of the American economy. Such conduct largely manifests in widely accepted competitive strategies that require consumer participation: The periodic release of products or emergence of a trend, for example. In some instances, planned obsolescence conduct reaches beyond the accepted competitive practices, desired by consumers, to conduct that clearly harms consumers with no countervailing rationale. Such practices effectively cease product function prematurely, either through product failure or poor performance and inefficient repair costs. While this conduct largely evades legal capture, it intersects with many existing legal frameworks. Recognizing both the unlikeliness of a statutory proscription and the conduct's position in our market economy, this Comment explains how existing consumer law infrastructure could limit harmful planned obsolescence. Encompassing both antitrust and consumer protection, consumer law advances consumer welfare by promoting the competitive process and ameliorating consumer harm. The Federal Trade Commission, consumer law's dual enforcer, is uniquely situated to protect consumers from planned obsolescence that goes too far. However, greater research and careful application are necessary. [ABSTRACT FROM AUTHOR]

Additive manufacturing (AM), also known as 3D printing (3DP), refers to manufacturing technologies that build up the desired geometries by adding materials layer by layer. Common meltable and fusible materials such as polymers, metals, and ceramics could be used in 3DP processes. During decades of development, products made by 3DP can now achieve stringent industrial standards at comparable costs compared to those traditionally manufactured. Improving 3DP technologies is required to make them more competitive and acceptable than their counterparts. However, achieving this is challenging since the quality of printing products is still heavily dependent on many cost-driven factors. Inadequate quality, impaired functionality, and reduced service life are three main consequences of 3DP's failures. To effectively detect and mitigate defects and failures of 3DP products, machine condition monitoring (MCM) technologies have been used to monitor 3D printing processes. With the help of those dedicated algorithms, it could also prevent failures from occurrence by alerting operators to take appropriate actions accordingly. This study systematically reviews the MCM technologies used in a typical 3DP process—the fused deposition modelling (FDM), identifying their advantages and disadvantages. The mentioned MCM technologies include but are not limited to traditional MCM (sensors only), aided with analytical and artificial intelligence (AI) tools. The MCM techniques focus on the defects of the 3DP process. The detection and identification of those defects are investigated. Furthermore, research trends on developing MCM technologies, including challenges and opportunities, are identified for improving the FDM process. This review highlights the developed methodologies of MCM that are applied to FDM processes to detect and identify abnormalities such as defects and failures. The evaluations of defects are elaborated to deepen the comprehension of the essence of the defects, including their cause, severity, and effect. A detailed deliberation about identifying the critical components for the successful application of 3DP MCM systems was done. Finally, this review indicates the technical barriers that need to be overcome to enhance the performance of monitoring, detection, and prediction by MCM and associated technologies. [ABSTRACT FROM AUTHOR]

The market development trend of foldable AMOLED screen is introduced in the article, and then the core links of the industry chain of foldable mobile phones is drawn off. Furthermore, that improving the bending ability is an urgent problem to be solved in achieving lightweight is proposed. Based on this demand, a specific structural scheme and a complete set of bending ability evaluation methods to achieve lightweight affect are put forward. By combining bending simulation and product failure test, the mechanism is analyzed, and also, the main and secondary factor affecting bending ability are proposed. After that, a standardized improvement system for bending ability, including optimization of membrane quality, structural optimization, and process optimization, is validated and applied. On condition that an average bending radius of 1.5mm for Panel and 1.3mm for MDL are achieved ultimately, that has reached the international leading level. Moreover, based on the stress simulation research, a nonlinear model relationship between the strain of the TLD film layer (SiNx) and the clamp distance, which is a key factor affecting the bending ability and can predict the bending ability, is established. Finally, the future development direction and research direction of improving the bending ability of foldable AMOLED screen are prospected. [ABSTRACT FROM AUTHOR]

In materials engineering applications, lifetime of product is one of the quality characteristics of interest. Lifetimes of products are inspected in life tests upto a predetermined time t0, which may observe early failure of some of the products; incorporation of this fact may not only reduce the cost of inspection, but also provide some more insight into the failure mechanism. In this paper, we consider a two-stage time censoring scheme by dividing test truncation time t0 into two parts t t and observe the number of failures in each interval, considering the remainder items as censored at t0. The trinomial distribution has been used to develop life test acceptance sampling plans for establishing quantile life of items having Weibull lifetimes. The proposed life test sampling plan gives added advantage to producers and extra safeguard to consumers, as compared to the life test sampling plans available in the literature for the Weibull distribution. Tables of plan parameters are constructed through code written in R 4.1.2, and illustrated for some real-life industrial cases. [ABSTRACT FROM AUTHOR]

Product configuration plays a vital role in product customization. Customers require products with reasonable cost and reliability, so manufacturers should exchange between reliability and production cost through product configuration. To investigate this problem, a novel combined FTA-DFMEA method is presented that implements integrated AHPTOPSIS to improve product configuration. In this procedure, customer's needs and market's feedbacks are considered to identify possible product failures, and an integrated AHP-TOPSIS is applied in order to select the most crucial potential failure based on some identified and extracted criteria. Then, minimal paths are obtained through fault tree analysis and an inverse search method is done to identify related functions and defective components. Failure modes and effect analysis is implemented to conclude modes of failure, effects, and causes. Subsequently, a combined AHP-TOPSIS method is utilized for ranking failure modes and selecting the most crucial failure mode. Failure modes are addressed according to their importance and corrective actions are carried out to improve product configuration. Suppliers with various policies, reliability, warranty and purchasing costs are considered. In addition, for the first time all configuration models like series, parallel, and joint series-parallel as well as redundancy allocation are taken into consideration. A minimum improvement index is considered, which is determined by the decision-maker based on risk-averseness. Eventually, a case study of a laptop system is introduced to evaluate the practicality of the developed algorithm. The results indicate that the proposed method creates different efficient alternatives for the decision-maker to enhance reliability, total costs, and product configuration. Also, the proposed framework consisting of the integration of failure analysis and MADM techniques, effectively identifies failure modes and prevents them from occurring. [ABSTRACT FROM AUTHOR]

In this study, we focused on innovative approaches to improve drug administration in oral pathology, especially by transmucosal and transdermal pathways. These improvements refer to the type of microneedles used (proposing needles in the saw), to the use of certain enhancers such as essential oils (which, besides the amplifier action, also have intrinsic actions on oral health), to associations of active substances with synergistic action, as well as the use of copolymeric membranes, cemented directly on the tooth. We also propose a review of the principles of release at the level of the oral mucosa and of the main release systems used in oral pathology. Controlled failure systems applicable in oral pathology include the following: fast dissolving films, mucoadhesive tablets, hydrogels, intraoral mucoadhesive films, composite wafers, and smart drugs. The novelty elements brought by this paper refer to the possibilities of optimizing the localized drug delivery system in osteoarthritis of the temporomandibular joint, neuropathic pain, oral cancer, periodontitis, and pericoronitis, as well as in maintaining oral health. We would like to mention the possibility of incorporating natural products into the controlled failure systems used in oral pathology, paying special attention to essential oils. [ABSTRACT FROM AUTHOR]

The number of failures serves as a critical indicator that dynamically impacts the reliability of self-announcing failure products, making it highly practical to incorporate the failure count into reliability management throughout the entire product life cycle. This paper investigates comprehensive methodologies for effectively managing the reliability of self-announcing failure products throughout both the warranty and post-warranty stages, taking into account factors such as the failure count, mission cycles, and limited time duration. Three renewable warranty strategies are introduced alongside proposed models for post-warranty replacements. By analyzing variables like the failure number, mission cycles, and time constraints, these proposed warranties provide practical frameworks for efficient reliability management during the warranty stage. Additionally, the introduced warranties utilize cost and time metrics to extract valuable insights that inform decision making and enable effective reliability management during the warranty stage. Moreover, this study establishes cost and time metrics for key post-warranty replacements, facilitating the development of individual cost rates and model applications in other post-warranty scenarios. Analyses of the renewable free-repair–replacement warranties demonstrate that establishing an appropriate number of failures as the replacement threshold can effectively reduce warranty-servicing costs and extend the coverage duration. [ABSTRACT FROM AUTHOR]

This study examines how a manufacturer can improve the robustness of an imperfect production system by implementing maintenance activities, which can be measured in terms of system reliability and product failure rate. A two‐dimensional maintenance policy comprising system reliability and the product defect rate is proposed to assess maintenance activity costs. The optimal thresholds of the two dimensions are analyzed to investigate the trade‐off between cost and system quality. A numerical example is provided to verify the proposed model's effectiveness. The results showed that the less stable the system, the greater the total costs incurred; therefore, lower stringent thresholds may be set to prevent frequent maintenance. Moreover, a sensitivity analysis is performed to investigate the essential parameters that significantly affect maintenance decisions. The results showed that the thresholds of the reliability function and defect rate significantly impact total costs. Any inaccurate assessment of system usage could lead to incorrect estimations and a substantial increase in cost. [ABSTRACT FROM AUTHOR]

The failure threshold of a product is not always constant when affected by random shocks. Thus, this paper establishes a reliability model that combines dynamic failure threshold and self-healing characteristics, which are subjected to the competing failure process. Soft failure is caused by degradation exceeding the soft failure threshold, and hard failure occurs because of random shocks. Degradation consists of natural degradation and a degradation increment caused by shocks. The failure thresholds and degradation rate will also be affected by random shocks. Moreover, the self-healing characteristics in the degradation process, together with the degradation increment, will affect the whole degradation process. When the random shock arrives, the soft and hard failure thresholds will change simultaneously. Based on the above factors, the corresponding analytical expressions of reliability models under different shock models are derived. To confirm the effectiveness of the proposed model, an example of micro-engine is used to verify the constructed reliability model. The influences of self-healing and dynamic thresholds in micro-engines on reliability are studied. The effects of self-healing and thresholds on the models are analyzed, which can provide study basis for the maintenance and replacement of product. [ABSTRACT FROM AUTHOR]

People use social media as free channels to share their sentiments and experiences during all stages of consuming a product or service. Likewise, corporations depend on social media as feedback sources that influence the positioning of their products/services in the market. This paper aims to recognise the frequent product flaws and warranty issues through social network mining. We have performed ontology-based methods, text mining, and sentiment analysis using deep learning methods on social media data to investigate product failures, symptoms, and the correlation between warranty programs and customer behaviour. Correspondingly, a multi-sources mining approach has been incorporated into social media mining to cover all the occasions. Furthermore, we promoted a decision support system to learn practically through customer feedback. Finally, to validate the accuracy and reliability of the results, we used the claimed data of the laptop industry to compare our derivatives and machine learning validation metrics to ensure accuracy. [ABSTRACT FROM AUTHOR]

In recent decades, laser additive manufacturing has seen rapid development and has been applied to various fields, including the aerospace, automotive, and biomedical industries. However, the residual stresses that form during the manufacturing process can lead to defects in the printed parts, such as distortion and cracking. Therefore, accurately predicting residual stresses is crucial for preventing part failure and ensuring product quality. This critical review covers the fundamental aspects and formation mechanisms of residual stresses. It also extensively discusses the prediction of residual stresses utilizing experimental, computational, and machine learning methods. Finally, the review addresses the challenges and future directions in predicting residual stresses in laser additive manufacturing. [ABSTRACT FROM AUTHOR]

Because defects in software modules (e.g., classes) might lead to product failure and financial loss, software defect prediction enables us to better understand and control software quality. Software development is a dynamic evolutionary process that may result in data distributions (e.g., defect characteristics) varying from version to version. In this case, effective cross‐version defect prediction (CVDP) is not easy to achieve. In this paper, we aim to investigate whether the defect prediction method of the threshold‐based active learning (TAL) can tackle the problem of the different data distribution between successive versions. Our TAL method includes two stages. At the active learning stage, a committee of investigated metrics is constructed to vote on the unlabeled modules of the current version. We pick up the unlabeled module with the median of voting scores to domain experts. The domain experts test and label the selected unlabeled module. Then, we merge the selected labeled module and the remaining modules with pseudo‐labels from the current version into the labeled modules of the prior version to form enhanced training data. Based on the training data, we derive the metric thresholds used for the next iteration. At the defect prediction stage, the iterations stop when a predefined threshold is reached. Finally, we use the cutoff threshold of voting scores, that is, 50%, to predict the defect‐prone of the remaining unlabeled modules. We evaluate the TAL method on 31 versions of 10 projects with three prevalent performance indicators. The results show that TAL outperforms the baseline methods, including three variations methods, two common supervised methods, and the state‐of‐the‐art method Hybrid Active Learning and Kernel PCA (HALKP). The results indicate that TAL can effectively address the different data distribution between successive versions. Furthermore, to keep the cost of extensive testing low in practice, selecting 5% of candidate modules from the current version is sufficient for TAL to achieve a good performance of defect prediction. [ABSTRACT FROM AUTHOR]

Context. The main idea is to take into account the possibility of the influence of hidden defects on the reliability of multi-mode radioelectronic equipment with a variable structure, which do not take into account the known methods for calculating reliability indicators. A quantitative assessment of the parameter of the failure flow of products is proposed, taking into account the impact of the accumulation of hidden defects on its value. Objective. Improvement of the method for assessing the reliability of objects with a variable structure, taking into account the possibility of hidden defects when used for their intended purpose in certain operating modes. Method. The methodology for assessing the values of reliability indicators of complex technical systems is used. The method being developed is the development of an algorithm for assessing the reliability indicators of multi-mode objects in the direction of taking into account the possibility of appearance and accumulation of hidden defects in subsets of elements of the object, which are not used when it operates in separate modes. Results. Functional dependencies of partial and complex indicators of reliability of multi-mode objects on the accumulation of hidden defects, which manifest themselves only during maintenance or change of operating modes, are obtained. The solution is formalized in the form of an algorithm that uses the results of trial operation of products as initial data. Conclusions. The scientific novelty lies in the development of the following innovative solutions: 1) for the first time it is proposed to take into account the presence of hidden defects when assessing the reliability of multi-mode objects with a variable structure; 2) for the first time, functional dependencies of the influence of the presence of hidden defects on the values of partial and complex reliability indicators were obtained and studied. The practical significance of the results lies in the fact that it allows, at the stage of trial operation of radioelectronic equipment with a variable structure, to objectively assess the compliance of calculations with the required values of reliability indicators by taking into account the possibility of hidden defects. [ABSTRACT FROM AUTHOR]

In this paper we present new empirical evidence on the relationship between exporting experience and the duration of exports at the firm-product-destination level. We find that the direct effect of experience on export flow survival is negative. However, when we include interactions between experience and firm export diversification measures, this effect becomes positive. This suggests that more experienced firms launch more risky export flows which increases the probability of failure of any individual product-destination pairing. [ABSTRACT FROM AUTHOR]

The rise of passive investing is shining a new light on the world of Indexing. Indexing is all around us today, whether being discussed by a media outlet showing the movements of the day or a newly launched passive ETF that tracks a recently created index. But there is little research on whether picking one index over another provides value to the investor when the indexes all share very similar index construction methodologies. Is there value in selecting one over the other or should investors choose the one that is the most accessible or cheapest to access? This article aims to fill that gap by conducting a comparative analysis of US Large Cap indexes that are substantially similar in their construction methodologies. As expected, the indexes selected perform very similarly to one another based on the quantitative methods used within the analysis. Other than number of securities, the largest difference among the indexes is their exposure to Mid-Cap stocks. The decision of which index to select is dependent on the application being selected. This article focuses on the four purposes outlined by DiBartolomeo (2019) which are: journalistic, representation of an asset class, a fair benchmark, and basis of passive investment. In most cases, each index is a reasonable substitution for the others. Given that risk and return profiles are similar, factors such as number of securities, licensing costs, and brand value are the most significant to consider. This is especially true when selecting an index as the basis of a passive product, where those factors affect the product cost and capacity that can determine the success or failure of a passive product. [ABSTRACT FROM AUTHOR]

Prior literature has documented that product quality failures have negative impacts on the interest of stakeholders, such as consumers and shareholders. We extend this literature by investigating its potential effects on the interest of employees. Using a novel dataset that tracks the recall incidents of Chinese firms in an industry where product quality is crucial (i.e., the drug industry), our empirical results show that the effects on corporate employment decisions are twofold. On the one hand, we show that firms' employment growth decreases after product recalls. The effect is more pronounced in non-state-owned firms, firms with higher labor costs, firms in regions with weaker labor protection, and during periods when local politicians lack promotion incentives. On the other hand, product recalls mainly induce firms to reduce the employment growth of low-grade employees, consistent with recalling firms relying on high-skilled labor to improve drug quality. Collectively, our study suggests that product quality failures could be a broader issue of corporate social responsibility (CSR) than being documented, and carries implications for policymakers concerning employment as well as product safety. [ABSTRACT FROM AUTHOR]

The thermo-oxidative aging of rubber products is inevitable during their use and leads to product failure and can even endanger safety. Oxygen is an important factor that cannot be ignored during the thermo-oxidative aging process. Thus, the gas barrier property of rubber products is of significant concern. In this work, a strategy of crystallizing rubber in unfilled rubber composites was designed by firstly constructing a dual synergistic mechanism of crosslinking density and crystallization on the oxygen barrier properties. As a crystallizable polymer, trans-butadiene-co-isoprene rubber (TBIR) shows dendritic fibril crystals or spherulites in natural rubber (NR)/TBIR vulcanizates. Meanwhile, the vulcanizates containing TBIR have a higher crosslinking density than NR vulcanizates. These TBIR-rich crystals and high-crosslinking-density structures are distributed in vulcanizates like continuous islands. Contrary to what has been reported in the literature, the decrease in oxygen permeability of NR/TBIR is not only due to the high crosslinking density and free volume of the polymer matrix, but more importantly, the spherulites of TBIR play a role in blocking and prolonging the oxygen diffusion path during the diffusion of oxygen in the polymer composites. We propose that the compatible crystalline polymer can replace the lamellar filler, play the role of the oxygen barrier in rubber composites, reduce the diffusion and dissolution of oxygen, and achieve the effect of improving the thermo-oxidative aging property of the rubber composite. Future research will follow the morphology evolution of TBIR crystals, their crosslinking structure and density, and interactions between TBIR and NR on the oxygen barrier and thermo-oxidative aging property. [ABSTRACT FROM AUTHOR]

In this article, an attribute control chart is proposed when the lifetime of a product follows a Weibull distribution in two-stage sampling, which is based on the number of failures from a truncated life test. The coefficients of the proposed double sampling attribute control chart and the test duration are determined so that the average run length when the process is in control is close to the target value. An overview is reported on how double sampling np control charts work. Tables reporting the out-of-control average run lengths are given for various shift parameters. A case study is given to illustrate the proposed control chart for industrial use. A comparison of two-stage and single-stage sampling of failure of products is discussed. [ABSTRACT FROM AUTHOR]

In the realm of smart manufacturing, predictive maintenance plays a pivotal role in ensuring equipment reliability, minimizing downtime, optimizing costs, and reducing product failure rate by detecting faulty products in the early stage. However, the efficacy of predictive maintenance hinges on the quality of training data employed for predictive modeling. Inadequate data quality can lead to erroneous predictions and, consequently, ineffective maintenance strategies. This research paper introduces a solution that leverages deep learning and data quality management to enhance predictive maintenance in smart manufacturing. Our proposed methodology encompasses two major components such as data quality management and faulty product detection. Data quality management includes data preprocessing, feature reduction, and data balancing, whereas faulty product detection is done using deep learning techniques. By combining these elements, a predictive model capable of accurately forecasting faulty products in early stages to reduce economic losses is developed. The proposed approach effectively addresses data quality issues and is tested on the SECOM dataset which indicates that it surpasses traditional models with an accuracy of 96.4% and perfect recall. Ultimately, this research contributes to the advancement of predictive maintenance and deep learning in the context of smart manufacturing, benefiting both industrial practitioners and researchers alike. [ABSTRACT FROM AUTHOR]

Given that the vast majority of brand extensions fail, it is important to understand how extension failure influences consumer judgments of the parent brand that launched the extension. In the brand extension literature, there is a paucity of research on the role of consumer characteristics in influencing response to such failures. To fill this gap, the present research examines the impact of consumers' implicit theory orientation—their perspective on whether personality traits are malleable versus fixed—on the severity of negative feedback effects following extension failure. Seven studies show that entity theorists, who believe in the fixedness of personality traits, penalize parent brands more than incremental theorists, who endorse trait malleability. This brand penalty effect arises because as compared to incremental theorists, entity theorists are motivated to view brands as a cohesive group and therefore equate extension failure with the diminishment of the overarching parent brand. This effect is more likely when brand cohesiveness is low or ambiguous, but it is less likely when brand cohesiveness is high. Furthermore, while entity theorists are more likely to reduce brand evaluations after extension failure, the two groups do not differ in parent brand evaluations after extension success. [ABSTRACT FROM AUTHOR]

The development of stiffness theory is constrained by its contradiction with engineering experience. Several easily overlooked details of stiffness theory were clarified, and a qualitative evaluation formula for the risk of coal burst was provided. Then a novel structure factor called uneven stiffness coal seam structure (USCS), which consists of high stiffness zone (HSZ), low stiffness zone (LSZ), and contiguous roof and floor, was proposed. Many areas prone to coal bursts, such as thinning zones, bifurcating areas, magmatic intrusion areas, and remnant pillar affected areas of coal seam, are the HSZs of USCSs. Comparative analysis of the uneven stiffness coal seam under different roof conditions and examination of the simplified trisection model of the USCS were conducted. Then 6 groups of 14 simplified 2D models using COMSOL5.2 was constructed based on controlled variable method to simulate different responses of the USCS with varying parameters under same working conditions. The results demonstrate the following: (1) coal bursts occur only when both the failure criterion and the stiffness criterion are simultaneously satisfied, the risk of coal burst (rCB) is the product of the risk of failure (rF) and the risk of instability (rI). (2) The pressure concentration function of USCS facilitates stress concentration from LSZ to HSZ, thus raising the rF in HSZ. The stiffness reduction function of USCS reduces the local mine stiffness (LMS) of the HSZ, allowing the system to meet the stiffness criterion even with a hard roof, thereby raising the rI in HSZ and reconciling the contrast between stiffness theory and engineering experience. Failures within HSZ of the USCS enables the roof strata to release bending deformation energy without roof breakage. (3) The normal stress of HSZ is positively correlates with the value of ERHRKHSL/KLSH; The LMS of the HSZ is positively correlated with the value of ERKL/KHHRSLSH. The USCS boasts significant advantages in integrating and harmonizing various existing theories and explaining multiple specific types of coal bursts. By applying relevant USCS findings, new explanations can be provided for engineering phenomena such as the time-delayed coal bursts, the inefficient pressure relief in ultra thick coal seams, and the "microseism deficiency" observed prior to certain coal bursts. [ABSTRACT FROM AUTHOR]

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