Product Failure Research Articles

Crack Control in Additive Manufacturing by Leveraging Process Parameters and Lattice Design

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.

Designing branching scenarios to support clinical reasoning in dental education

Branching scenarios are educational tools where dental students can explore their decision making in a clinical environment without risking harm to patients. By incorporating productive failure, adaptive learning and serious gaming elements into their design, they offer interactive and personalised learning environments. We aimed to design a branching scenario based on a patient presenting with dental pain and evaluate its implementation in a classroom setting. We employed a validated serious gaming model as the framework for our design and mapped a decision tree on a scalable whiteboard for the case. A survey platform was used to build the scenario using rule-based logic. The scenario included multiple ‘learning points’ with tailored feedback. Students can track how many learning points they have ‘unlocked’ and are encouraged to revisit previously uncovered pathways. Classroom observations, learning analytics and student feedback have been collected to evaluate the activity. Preliminary feedback has informed improvements to the branching scenario design and educators have found the learning analytics can be used to tailor future teaching sessions. Future steps include useability testing and design improvements based on student feedback.

HAZOP ANALYSIS OF AN ATMOSPHERIC PETROLEUM DISTILLATION UNIT AND SIMILARITY IN SUSTAINABLE AVIATION FUELS (SAFs) PRODUCTION PROCESSES

The production of petroleum derivatives stands out worldwide among the non-renewable energy production processes, as the most well-known worldwide. In this study, an atmospheric distillation column that processed 100,000 barrels/day (662.5 m3/h) of crude oil was simulated using CHEMCAD® software. From this procedure, the Process Flow Diagram (PFD) and the Piping and Instrumentation Diagram (PI&D) for the unit, corresponding to its automation, were obtained. Subsequently, a HAZOP (Hazard and Operability Study) analysis was conducted in order to identify risks in the unit that, although not dangerous, could compromise its ability to achieve its productivity. The main risks of the process were related to fires, explosions and environmental contamination from leaks and ruptures in pipes, pumps, heat exchangers, the column itself, among other equipment. The HAZOP analysis was able, through the use of guide words, to identify possible operational risks arising from deviations in operating intentions, such as the possibility of fires, explosions, environmental contamination and their consequences. It was possible to identify the risks associated with the selection of materials, the mechanical design of the equipment and the specifications of the accessories. Therefore, the study carried out is an important survey for reducing possible failures in the oil industry. And, since this study is an in-depth study on the distillation processes for petroleum-derived products. It is understood that their in-depth study, as a result of the development of new renewable products, especially sustainable aviation fuels (SAFs), because they are similar purification processes, employ the same methodology to identify possible failures in production.

A Method for Predicting the Remaining Service Life of Finite Data Products Based on Gaussian Stochastic Processes

There is a problem of poor predictive performance when predicting the remaining service life of products. Therefore, this paper proposes a finite data product remaining service life prediction method based on Gaussian stochastic processes. Analyze the types of product failure and degradation under limited data, and determine the factors affecting the degradation performance of product life through constant stress accelerated degradation tests, step stress accelerated degradation tests, and sequential stress accelerated aging tests; using the Wiener process to analyze the performance degradation characteristics of products, setting product failure thresholds, defining the remaining life of the product based on the degradation process, and using equal interval partitioning methods to determine the product health index, and clarifying the product failure process under limited data; by calculating the mathematical expected value, the numerical characteristics of the remaining life of the product are defined. Variance and moments are used to determine the predicted second-order central moment and origin moment. Based on the monotonic increasing characteristics of the inverse Gaussian process, the probability distribution of the random variable of product failure is determined after the Gaussian process. Under limited data, the actual working time of the product and the degradation amount at the time scale are clarified, and a preset threshold is set for the degradation amount. Build a residual life prediction model for product degradation and output the prediction results. The experimental results show that this method can accurately predict the remaining service life of the product and has good predictive performance.

A Review of the Technological Aspects and Process Optimization of Bioethanol Production From Corn Stover Biomass: Pretreatment Process, Hydrolysis, Fermentation, Purification Process, and Future Perspective

ABSTRACTBioethanol, a sustainable energy solution derived from renewable biomass, has gained prominence, with corn stover emerging as a substantial biomass resource in Indonesia. Corn stover, a corn residue, is one of the top three agricultural wastes worldwide and is abundantly available. However, a significant portion of corn stover is burned in fields rather than utilized for bioethanol production, whereas it has potential as a bioethanol feedstock. As the world strives to realize sustainable and environmentally friendly energy security, bioethanol production from corn stover can be one of the solutions to be developed. Nonetheless, the current immaturity of bioethanol production technology is one of the causes of large‐scale production failure. The present paper comprehensively reviews the technological aspects and process optimization of bioethanol production using corn stover as a feedstock comprising pretreatment, hydrolysis, fermentation, and bioethanol purification processes. According to our critical review, ammonia fiber expansion (AFEX) pretreatment is the most effective conventional pretreatment, with glucose yield up to 90%. Moreover, ultrasound appears to be the most viable option for nonconventional pretreatment of corn stover for producing bioethanol. However, combining ultrasound pretreatment and dilute aqueous ammonia produced 80.6% sugar output. Furthermore, enzymatic hydrolysis emerges as the most effective saccharification, yielding up to 81.39%. Moreover, the fermentation process of corn stover with the saccharification and co‐fermentation (SScF) method and the process optimization with response surface methodology (RSM) could produce bioethanol with a concentration of up to 59.8 g/L and 92.07% ethanol yield, respectively. This review also reveals that pervaporation for the purification process is the best choice for producing bioethanol with high purity up to > 99%. In addition, this method could reduce the energy used by 6.6% lower, 24.2% lower carbon footprint, and have the lowest total capital and production costs compared to conventional molecular sieves and extractive distillation. We believe this review article can provide a reference for selecting the best bioethanol production process from corn stover for further research.

Decomposing the Cognition-influential Aspects of Instructional Designs A Systematic Review of Induced Causal Relationships by the Constructional Components of the Direct Instruction and Productive Failure Designs

A substantial debate on the effectiveness of two instructional designs, namely “Productive Failure (PF)” and “Direct Instruction (DI)” has been prolonged for almost two decades. Indeed, from many studies we have seen if being deliberately designed and carried out, then both designs can be sophisticated not only in instructional procedures but also in how each function takes effect on learning. The constituting components could each be specified preceding the instruction as a design, but these activities carry its own goal in facilitating learning. In this article, we summarized the reasoning in the specifications of connection, construction and criticization. Thus, from our review, we debated how instructional stages, problem-led learning and failure-driven learning can each deliver good outcomes for learners.

The Competition between Productive Failure and Direct Instruction Is not Determinable: A Review of the Deviations and Reasons

Teaching the learner new information demands careful implementation. The implementational protocols are derived from instructional ideologies and purpose of the design. It not only requires the instructors to grasp the essence of instructional designs without an extemporaneous amending or exchanging of the theoretically proven meaningful teaching events, but also, a precise actualization of structure and approach as well as its behind ideology is demanded. Those rationales and references for instructors to determine when and how to implement instruction, what practice or what strategies are needed to be taught ought to be precise enough to separately explain their advantages and prediction of outcomes in learning. In this article, we explored how both problem-proceeding learning and guidance-proceeding learning are beyond control regarding the deviated cognitive processing those instructional procedures can possibly elicited.

Genotype‐phenotype associations in individuals with Diamond Blackfan anaemia

AbstractIntroductionDiamond Blackfan anaemia (DBA) is a rare disorder characterized by failure of red blood cell production, congenital abnormalities and cancer predisposition, primarily caused by pathogenic germline variants in genes encoding ribosomal proteins.MethodsWe conducted a genotype‐phenotype and outcome study of 121 patients with DBA spanning the 20‐year history of the National Cancer Institute's Inherited Bone Marrow Failure Syndromes study. Patient phenotypes were compared by large versus small ribosomal protein genes, across genes with >5 cases (RPS19, RPS29, RPS26 and RPL35A) and by type of pathogenic variants (hypomorphic versus null, large deletions versus others).ResultsA pathogenic germline variant was identified in 71% of patients (n = 86/121) from 54 families. After adjusting for multiple testing, we found that patients with RPS29 variants were least likely to need treatment for anaemia while those with large ribosomal protein subunit variants had a higher proportion of intellectual disability and gastrointestinal abnormalities compared with small ribosomal protein subunit variants (p < 3.5 × 10−4). There were no statistically significant differences in overall survival or cancer incidence among patients with large or small ribosomal subunit genes.ConclusionThis detailed genotype‐phenotype study of DBA improves our understanding of the role of germline genetics in the clinical manifestations that may help guide the management of people with DBA.

Retraction Note: Intelligent root cause detection in Industry 4.0: a secure cross-validation of blockchain architecture for product failure checker

Retraction Note: Intelligent root cause detection in Industry 4.0: a secure cross-validation of blockchain architecture for product failure checker

Defining quality by quantifying degradation in the mechanical recycling of polyethylene

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).

The strength of stance: The impact of brand activism on resistance to negative information, purchasing, and premium paying intents across different types of failures

This paper represents a pioneering exploration of how brand activism influences consumer responses to performance and value-related failures. Specifically, across two experiments, the research explores how brand activism influences consumer resistance to negative information, purchase intent, and willingness to pay more, in response to product, service, and value-related failures. Study 1 (N = 237) reveals that consumers who are more involved in activism and are exposed to a product failure from activist brands exhibit higher resistance to negative information compared to those who encounter product failures from non-activist brands. This suggests that activist branding may protect companies by cultivating a resilient, loyal consumer base in such adverse situations. Study 2 (N = 261) extends these findings by examining whether value-related (vs service-related) failures impact the buffering effect generated by a brand’s activist stance. Results indicate that activist brands particularly benefit from a protective buffer in the context of service failure scenarios. However, this buffer does not extend to value-related failures, leading to harsher consumer judgments and intentions. The research significantly contributes to brand activism literature by uniquely integrating the themes of brand activism and brand transgressions, exploring how brand activism affects consumer responses to both performance and value-related failures.

Transgenic zebrafish as a model for investigating diabetic peripheral neuropathy: investigation of the role of insulin signaling.

Diabetic peripheral neuropathy (DPN), a complication of diabetes mellitus (DM), is a neurodegenerative disorder that results from hyperglycemic damage and deficient insulin receptor (IR) signaling in peripheral nerves, triggered by failure of insulin production and insulin resistance. IR signaling plays an important role in nutrient metabolism and synaptic formation and maintenance in peripheral neurons. Although several animal models of DPN have been developed to identify new drug candidates using cytotoxic reagents, nutrient-rich diets, and genetic manipulations, a model showing beneficial effects remains to be established. In this study, we aimed to develop a DPN animal model using zebrafish to validate the effects of drug candidates on sensory neuropathy through in vivo imaging during the early larval stage. To achieve this, we generated Tg (ins:gal4p16);Tg (5uas:epNTR-p2a-mcherry) zebrafish using an enhanced potency nitroreductase (epNTR)-mediated chemogenetic ablation system, which showed highly efficient ablation of pancreatic β-cells following treatment with low-dose metronidazole (MTZ). Using in vivo live imaging, we observed that sensory nerve endings and postsynaptic formation in the peripheral lateral line (PLL) were defective, followed by a disturbance in rheotaxis behavior without any locomotory behavioral changes. Despite defects in sensory nerves and elevated glucose levels, both reactive oxygen species (ROS) levels, a primary cause of DPN, and the number of ganglion cells, remained normal. Furthermore, we found that the activity of mTOR, a downstream target of IR signaling, was decreased in the PLL ganglion cells of the transgenic zebrafish. Our data indicates that peripheral neuropathy results from the loss of IR signaling due to insulin deficiency rather than hyperglycemia alone.

Integrating risk management in implementing circular economy principles in the healthcare sector: a case study from Indonesia

Purpose The purpose of this study is to explore the integration of risk management and circular economy (CE) principles within the healthcare sector to promote sustainability and resilience. Specifically, the study aims to demonstrate how risk management can support the transition to a circular economy in healthcare supply chains. By integrating risk management practices with CE principles, healthcare organizations can identify potential risks and opportunities associated with circular initiatives. Design/methodology/approach This study adopts a qualitative research approach, using a case study methodology with semi-structured interviews conducted at primary care facilities to understand the application of CE principles in practice. The study uses fuzzy logic methods to assess and mitigate risks associated with strategies promoting CE principles. Additionally, key performance indicators are identified to evaluate the effectiveness and enhance the resilience of these strategies within healthcare supply chains. Findings The study highlights the critical role of robust risk management strategies in facilitating the transition to a circular economy within healthcare organizations. Primary care facilities, which are critical to frontline healthcare delivery, are particularly vulnerable to product shortages due to supply risks. This study focuses on critical protective equipment, specifically latex gloves and assesses operational risks, including supply, demand and environmental risks, using a fuzzy logic-based model. Import delays were found to be a moderate risk, typically occurring once a year. The research highlights critical KPIs for a successful CE transition within healthcare supply chains, such as on-time delivery and service quality, which are directly related to the risk of supply chain disruption. In addition, the study highlights the significant impact of other CE strategies on healthcare supply chains, including localized production and manufacturing, innovation in product development, reverse logistics, closed-loop supply chains and the adoption of lean principles. Practical implications This study provides valuable insights for healthcare organizations to optimize resource efficiency, reduce waste and promote circularity in their operations. By implementing the proposed solutions and focusing on the identified KPIs, organizations can develop strategies to achieve sustainability goals and enhance resilience in healthcare supply chains. Originality/value This study contributes to the literature by demonstrating the application of risk management in facilitating the transition to a circular economy in the healthcare sector. The use of fuzzy logic methodology offers a novel approach to assessing and mitigating risks associated with critical product failures in supply chain activities. The study’s findings provide practical guidance for healthcare organizations seeking to integrate circular economy principles and improve sustainability performance.

Mathematical modelling of induction motors taking into account design-parameter asymmetry

Due to their numerous technical and economic advantages, induction machines (IM) with squirrel-cage rotors are important components of many industrial processes. Their reliability, durability, and ease of operation make them indispensable in various industries, ensuring stable and efficient equipment performance. However, to minimise the risk of costly production failures caused by sudden stoppages, it is important to implement effective diagnostic and monitoring methods. The most common type of fault in squirrel-cage induction motors is the breakage of cage bars and end ring segments, particularly in motors with high inertia loads and frequent stops and starts. Regular maintenance and the implementation of modern control systems in the industry will help ensure the reliable and uninterrupted operation of these machines. In the technical literature, various diagnostic methods have been proposed. Some are based on analysing data collected from the induction motor (IM), detecting characteristic perturbations that indicate faults in the machine. Other methods involve comparing the data obtained from the actual induction motor with its digital model. It is clear that accurate and adequate IM models are necessary for the development and optimisation of fault diagnosis methods. This paper focuses on developing a mathematical model of an induction motor (IM) in a stator-fixed coordinate system, where the squirrel-cage rotor of the IM is represented as a multiphase, symmetrically distributed winding system in space. The adequacy of the obtained model is demonstrated. The developed model allows for the analysis of various types of asymmetries in both stator and rotor of squirrel-cage induction motors

Machine learning technologies for predicting and preventing production failures

Machine learning technologies for predicting and preventing production failures

The use of Oral Anti-Diabetic Medications in Diabetes Mellitus type 1: An Educational Article and Expert Opinion

Diabetes mellitus type 1 is lifelong condition resulting from failure of production of insulin because of the loss of pancreatic islet beta-cells because of autoimmune damage. Patients with this type of diabetes need lifelong treatment with insulin to remain alive. Poor diabetic control which predisposes to a variety of complications is not uncommon in patients treated with insulin alone. Therefore, the use of medications that can possibly enhance the therapeutic effect of insulin and reduce the risk of diabetic complications has been considered. Oral anti-diabetics including acarbose, an inhibitor of intestinal α-glucosidase, metformin, a biguanide, sulfonylureas including glipizide, and sitagliptin, an inhibitor of dipeptidyl peptidase 4 (DPP-4) are primarily used for the treatment of non-insulin dependent diabetes (Type 2). The aim of this paper is to provide an overview of the use of oral anti-diabetics in the treatment of insulin dependent diabetes (Type 1). Expert opinion: The current evidence-based expert opinion recommends the judicious use of oral anti-diabetics especially acarbose and metformin in the treatment of unsatisfactorily controlled insulin dependent diabetes type 1. These medications can help in improving diabetic control through reducing glucose levels after meals, and can contribute to lowering the levels of glycosylated hemoglobin (HbA1c). The use of these oral anti-diabetics can also help in reducing insulin requirement.

Enhancing Government Services to Rice Farmers in the Philippines: A Service Quality–Sustainability-Focused Approach for Long-Term Agricultural Resilience

In the Philippines, where agriculture plays a vital role in the economy, nearly half of the country’s 30 million hectares of land is used for agricultural purposes. Despite government efforts to support rice farmers, challenges, such as production failures and profit losses, remain prevalent. This study evaluates the quality of government services provided to rice farmers through a service quality-based framework (SERVQUAL), assessing five key dimensions: assurance (AS), empathy (EM), reliability (RL), responsiveness (RS), and tangibility (TA). Structural equation modeling (SEM) is employed to examine the relationships among these service quality dimensions and other latent variables, including service quality (SQ), farmers’ satisfaction (FS), farmers’ trust (FT), perceived security (PS), and perceived effectiveness (PE). Data were gathered from 400 respondents using a 55-item survey. The findings indicate that perceived security (PS) is the most critical factor in enhancing the overall quality of government services. The study emphasizes the importance of adopting a SERVQUAL-based approach, with a focus on reliability and responsiveness to improve farmers’ satisfaction and trust. Additionally, fostering trust between farmers and the government is crucial to increasing the effectiveness of government programs and strengthening farmer–government collaboration. The study further advocates for prioritizing sustainable agricultural practices to ensure long-term productivity and environmental resilience. By improving service quality with a focus on sustainability, the Philippines can work towards achieving broader sustainable development goals.

Nutrient balance for enhanced recovery of stressed Spirulina platensis.

The failure of mass production of Spirulina plateaus can be attributed to an imbalance of nutrients (C:N) and an increase in accumulated sodium ions, coupled with the traditional harvesting process. The current study aims at the recovery of stressed and red cultures of Spirulina platensis as well as enhanced phycocyanin accumulation. The stressed Spirulina platensis cultures were obtained from a local Egyptian Spirulina production farms, which were further subjected to water analyses after removing the Spirulina biomass. Optimization was performed within 300-ml water path photobioreactor. Spirulina platensis samples were incubated with Zarrouk medium comparing with those modified using ammonium bicarbonate or ammonium acetate instead of sodium bicarbonate. Continuous batching was performed every 12days during three sequenced batches. Growth measurements (dry weight and pigments) were performed along the incubation time. It was found that carbon content of the growth medium seems to be more effective in Spirulina growth and biomass characteristics. Under different carbon sources, acetate resulted in the maximum dry weight of 1.48g·l-1 and recovery percentage of 463.3%. Such effect was extended along the different incubation batches. Various carbon concentrations revealed that moderate concentration of carbon in the form of acetate (0.699g·l-1) leads to the maximum growth under the same nitrogen content. A similar trend was observed with chlorophyll and phycocyanin accumulation, while carotenoids showed the opposite manner.

EXPRESS: The Minority Ownership Awareness Effect: When Promoting Minority Ownership Increases Brand Evaluations

Recent social movements, such as Black Lives Matter, have prompted brands and retailers to increase the use of minority ownership labels (e.g., Black-owned or woman-owned). The current research examines when and why minority ownership awareness influences consumer behavior, particularly for brand failures. When a brand failure occurs, minority ownership awareness can result in higher brand evaluations and greater willingness to pay, a phenomenon referred to as the minority ownership awareness effect. This effect and its boundary conditions are demonstrated through five experiments and analyses of over 27,000 Google reviews for Black-owned restaurants. The authors propose that minority ownership awareness invokes a type of underdog effect which is pronounced in situations involving product (vs. moral) failures, among people with low (vs. high) social dominance orientation, and among those people with a high (vs. low) internal motivation to respond without prejudice.

Surface one-step modification of graphene oxide with N-cyclohexylbenzothiazole-2-sulfonamide to enhance the wear resistance of natural rubber/butadiene rubber composites

Natural rubber (NR) and butadiene rubber (BR) composites are frequently used in manufacturing tires and conveyor belts, which are susceptible to severe wear, leading to product failure and significant losses. To enhance the wear resistance of NR/BR composites, we prepared NR/BR composites reinforced with a synergy of N-cyclohexylbenzothiazole-2-sulfonamide surface one-step modified reduced graphene oxide (CZ-rGO) and carbon black N234 (CB) using a latex co-precipitation method. This study explored the effects of GO content and CZ modification on the structure, wear resistance, thermal conductivity, and mechanical properties of the NR/BR blended composites. It showed that adding 2 phr of GO resulted in excellent filler dispersion, significantly improving the tensile strength, elongation at break, tear strength, thermal conductivity, and wear resistance of the composites. The incorporation of CZ-rGO further increased the crosslinking density, vulcanization performance, and filler dispersion with enhanced mechanical properties, thermal conductivity, and wear resistance of the composites. Notably, the DIN abrasion volume was reduced to 77.88 mm³, surpassing the ISO 10247 standard for conveyor belt cover rubber in terms of wear resistance. The wear resistance of NR/BR/CZ-rGO composites is not only significantly higher than that of single NR- or SBR-based rubber composites, but also significantly higher than that of other binary rubber blend composites, and the CZ-rGO filler is simpler in composition and structure and exhibits a more prominent wear enhancement. This work provides guidance for an efficient and environmentally friendly approach to GO surface modification, as well as useful insights for the development of high wear-resistant rubber composites with excellent overall performance.