Product Lifetime Research Articles

Enhancing Circular Economy Practices in the Furniture Industry through Circular Design Strategies

The furniture industry represents a substantial segment of Europe’s economy, with the European Union producing approximately 25% of the world’s furniture. This sector is currently transitioning towards a circular economy. This study aims to thoroughly examine the circular initiatives undertaken by European furniture companies, emphasising the role of design in fostering innovative solutions. By employing a multiple case study methodology, the research demonstrates that existing circular solutions predominantly focus on materials and products, with significant adoption of circular design strategies. The majority of furniture companies are implementing these strategies to enhance resource efficiency and prolong product lifespans. Additionally, some companies are developing complementary service systems to improve product performance and longevity further. However, only a few have successfully implemented circular business models alongside circular product design strategies. This study also highlights that increasing user engagement and adopting a systemic perspective that includes various stakeholders in creating mutually beneficial solutions are areas that are still underdeveloped. Finally, we propose a framework to effectively guide furniture companies in implementing design strategies from a systemic perspective, aiming to generate comprehensive circular solutions within the European furniture sector.

Reducing, reusing, and recycling in the furniture industry: A mini-review

This study explores sustainable practices within the furniture industry, focusing on the principles of reduce, reuse, and recycle. Through a comprehensive review of scholarly literature retrieved from databases like Scopus, Web of Science, and Google Scholar a moderate corpus of articles is identified. The analysis reveals a predominant emphasis on strategies aimed at minimizing resource consumption, extending product lifespans, and optimizing material recovery. While reduce, reuse and recycle serve as foundational pillars of sustainable furniture production, the literature also highlights complementary principles such as "rethink" and "refuse," urging critical reassessment and rejection of unsustainable practices. Despite the diversity in research interests and methodologies, the synthesis of findings underscores the need for standardization and comprehensive approaches to address environmental challenges throughout the furniture lifecycle. The study advocates for further research and collaboration to drive meaningful progress towards a more sustainable future for furniture production and consumption. This abstract encapsulates the key findings and implications of the study, providing a concise overview of the state of research on sustainable practices within the furniture industry. The aim of this short review is to analyse the scientific articles and their quantity relating to ecodesign in the furniture industry, with particular emphasis on the principles of reduce, reuse and recycle, as well as complementary concepts such as ‘rethinking’ and ‘refuse’.

Using Version Control Information to Visualize Developers' Knowledge

It is not always clear in case of a software project who has the right amount of knowledge concerning a certain module or file. Programmers frequently ask questions like "Who knows the most about this code?" or "Who can I ask for help when I work on this module?". In a large, long-term software product, knowledge is distributed in an uneven way among developers. Developer fluctuation during the product lifetime might cause some parts of the code to be known very well by a multitude of developers, while other parts might sink to the "gray zone", where developer competence is dangerously scarce. It is important for the project management to identify such critical points, to avoid the complete loss of competence. Version control repositories contain loads of useful information about the evolution of a software project. This paper presents a developer-centered visualization that is intended to show individual, team-bound and company-bound knowledge of large legacy projects. The competence information is computed from the extracted version control information from Git repositories. The calculated competence value is based on the number of commits per developer and their significance. Aggregated views for teams and companies are available based on various heuristics. The visualization is implemented as a new plugin in CodeCompass, a standalone, open-source code comprehension software. Project managers and individual developers may both profit from the tool, whether it concerns software evolution, human-resource management, architecture, knowledge catch-up, or blame.

Genetic parameters, genome-wide association study, and selection perspective on gestation length in 16 French cattle breeds

Lifetime productivity is a trait of great importance to dairy cattle populations as it combines information from production and longevity variables. Therefore, we investigated the genetic background of lifetime productivity in high-producing dairy cattle by integrating genomics and transcriptomics data sets. A total of 3,365,612 test-day milk yield records from 134,029 Chinese Holstein cows were used to define 6 lifetime productivity traits, including lifetime milk yield covering full lifespan and 5 cumulative milk yield traits covering partial lifespan. Genetic parameters were estimated based on univariate and bivariate linear animal models and the Restricted Maximum Likelihood (REML) method. Genome-wide association studies (GWAS) and weighted gene co-expression network analyses (WGCNA) were performed to identify candidate genes associated with lifetime productivity based on genomic data from 3,424 cows and peripheral blood RNA-seq data from 23 cows, respectively. Lifetime milk yield averaged 24,800.8 ± 14,396.6 kg (mean ± SD) across an average of 2.4 parities in Chinese Holstein population. The heritability estimates for lifetime productivity traits ranged from 0.05 (±0.01 for SE) to 0.10 (±0.02 for SE). The estimate of genetic correlation between lifetime milk yield and productive life is 0.88 (±0.3 for SE) while the genetic correlation with 305d milk yield in the first lactation was 0.49 (±0.08 for SE). Absolute values for most genetic correlation estimates between lifetime productivity and type traits were lower than 0.30. Moderate genetic correlations were found between udder related traits and lifetime productivity, such as with udder depth (0.33), rear udder attachment height (0.33), and udder system (0.34). Some single nucleotide polymorphisms and gene co-expression modules significantly associated with lifetime milk yield were identified based on GWAS and WGCNA analyses, respectively. Functional enrichment analyses of the candidate genes identified revealed important pathways related to immune system, longevity, energy utilization and metabolism, and FoxO signaling. The genes NTMT1, FNBP1, and S1PR1 were considered to be the most important candidate genes influencing lifetime productivity in Holstein cows. Overall, our findings indicate that lifetime productivity is heritable in Chinese Holstein cattle and important candidate genes were identified by integrating genomic and transcriptomic data sets.

Weakly Supervised Deep Embedding for Product Review Sentiment Analysis

Online reviews have become an important source of information for users before making an informed purchase decision. Early reviews of a product tend to have a high impact on the subsequent product sales. In this project, we take the initiative to study the behavior characteristics of early reviewers through their posted reviews on two real-world large e-commerce platforms, i.e., Amazon and Yelp. In specific, we divide product lifetime into three consecutive stages, namely early, majority and laggards. A user who has posted a review in the early stage is considered as an early reviewer. We quantitatively characterize early reviewers based on their rating behaviors, the helpfulness scores received from others and the correlation of their reviews with product popularity. We have found that (1) an early reviewer tends to assign a higher average rating score; and (2) an early reviewer tends to post more helpful reviews. Our analysis of product reviews also indicates that early reviewers’ ratings and their received helpfulness scores are likely to influence product popularity. By viewing review posting process as a multiplayer competition game, we propose a novel margin-based embedding model for early reviewer prediction. Extensive experiments on two different e-commerce datasets have shown that our proposed approach outperforms a number of competitive baselines. In our project we have used algorithms like Decision Tree (DT) and Multi Layer Perceptron (MLP). All are measured in terms of accuracy

Application and efficacy of beidellite clay for the adsorption and detoxification of deoxynivalenol (vomitoxin)

The incidence of mycotoxin occurrence throughout the entire lifespan of some agricultural products could be due to climatic conditions and environmental factors (including high temperature, drought, and heavy rainfall) that enhance growth of fungi. Deoxynivalenol (DON) which is also referred to as vomitoxin is a mycotoxin produced from many Fusarium species. DON ranks high among the prominent mycotoxins in cereal products and is a ubiquitous toxin in livestock feeds. DON's adverse effects present major health challenges in both livestock and humans. The use of natural sorbents including smectite clays, is an economically feasible strategy to mitigate mycotoxin toxicities. Previous studies have demonstrated the potential of edible clays as protective components of human food and animal feed to alleviate toxicity associated with short-term exposure to mycotoxins including DON. Hence, this study was designed to investigate the sorption mechanisms of DON onto the binding surfaces of beidellite clay, assessing essential binding parameters such as enthalpy, free energy, binding capacity, affinity, and plateau surface density. These markers were used to predict availability of DON under the experimental conditions. Furthermore, the protection of beidellite clay against DON-induced toxicity was carried out using living organisms susceptible to DON toxicity, including Hydra vulgaris and Lemna minor. These studies investigated the dose-dependent detoxification of DON by 0.05–2 % inclusion of beidellite. Beidellite exhibited more than 75 % protection in Lemna minor and 53 % in Hydra vulgaris validating that this clay is effective in detoxifying DON. During emergencies, or after disasters, inclusion of edible clay like beidellite in food, water or capsules could reduce bioavailability of DON and halt potential exposures to humans and animals.

Why is longevity an important metric for the modern dairy herd?

Longevity of a dairy herd can reflect the health and welfare status of the herd and has a role in terms of public perception of the dairy industry. The natural lifespan of a dairy cow has been reported to be approximately 20 years; however, research has highlighted that it is more like 3.6 lactations (approximately 6 years) in the UK and 2.8 lactations (approximately 5 years) in the USA. This indicates that management decisions are having large impacts on the average productive lifespan of dairy cows, with the removal of cows from a herd due to old age being rare. Increasing the longevity of a dairy herd has been promoted as it decreases the requirement for replacement heifers and increases the average herd production level.

Genetic Structure of Ganoderma boninense Populations Associated with Oil Palm at Neighboring Fields with Different Planting Ages in Malaysia.

Ganoderma boninense is a basidiomycete pathogen of African oil palm (Elaeis guineensis) and the causal agent of basal stem rot (BSR) disease, which is the most destructive fungal disease of oil palm in Southeast Asia. The disease is fatal for infected palms and can result in 50 to 80% losses in oil yields because of a reduction in productive life span and a yield decline of infected oil palms. In this study, G. boninense isolates collected from different locations and planting blocks with different palm ages were molecularly characterized using microsatellite genotyping. Results showed high pathogen genetic diversity (He = 0.67 to 0.74) among planting blocks and between oil palm estates. Two nearby planting blocks with similar planting ages (i.e., 1999 and 2001) had a similar percentage of BSR incidence (>20%) but showed distinct Ganoderma genetic structure as detected using STRUCTURE. Similar results were obtained from another trial site where planting blocks differing in planting age but located only less than 1 km apart showed a diverse genetic background. The pathogen genetic admixture of the oldest planting (>30% BSR incidence) differed significantly from the younger planting (1.8 to 2.8% BSR incidence, breeding trial block), suggesting that the host-pathogen genotype interaction may impact the Ganoderma genetic variation over time. The genetic structure of G. boninense, as revealed in this study, implies positive selection resulting from the pathogen genetic variation, host-pathogen interaction, and possible introductions of novel genetic variants (through spores) from adjacent plantings. These findings offer new insights into the genetic changes of G. boninense over time. The information is essential to design disease management strategies and breeding for BSR resistance in oil palm.

An integrated planning approach for perishable goods with stochastic lifespan: Production, inventory, and routing

This paper focuses on addressing the crucial challenges posed by the uncertainty surrounding perishable goods within the supply chain. With staggering socioeconomic costs and significant environmental implications, effective management of perishable goods emerges as a critical imperative. Globally, the annual loss of approximately 14% of food, amounting to a staggering USD 1 trillion, highlights the urgency of the issue. However, Prevailing classification methods for perishable products oversimplify their complexity by dividing them into fixed or variable lifespans, neglecting the random lifespans endured due to fluctuating storage conditions, blurring traditional boundaries between fixed and variable classifications. In response to these pressing challenges, the research proposes a novel approach: the development of a nonlinear mixed-integer programming model for a green closed-loop supply chain. This innovative model seamlessly integrates production, inventory, and routing decisions for both main and secondary products of a manufacturer. Moreover, it optimizes order splitting and transportation modes to efficiently convert perished items into raw materials under conditions of uncertainty. Central to the approach is the adoption of a scenario-based methodology to model uncertainties, particularly focusing on the variability in the lifespan of perishable products. This approach allows for a more nuanced understanding of the complex dynamics inherent in managing perishable goods within the supply chain. To solve the proposed model, a novel hybrid algorithm is introduced: the Particle Swarm Optimization (PSO) and Simulated Annealing (SA) algorithm, or PSOSA, ensuring robust optimization under uncertainty and enhancing decision-making within the perishable goods supply chain. The research findings underscore the inadequacy of prevailing assumptions regarding the fixed lifespan of perishable products, commonly observed in the literature. By accounting for uncertainty in perishable goods’ lifespan, a more accurate representation of total producer costs is achieved, highlighting the misleading reduction of 25% observed when neglecting such uncertainty.

A Robust Design for the Omnibus SPRT Control Chart Under Skewed Data Distributions

Control charts are widely used in manufacturing industries to ensure that production levels are stable and satisfactory. Recently, the omnibus sequential probability ratio test (OSPRT) control chart was developed for the purpose of monitoring the mean and variability of a process simultaneously. As the OSPRT chart was proposed for the first time in literature, its development relied entirely on the assumption that data follow the Normal distribution. Nonetheless, researchers are frequently reminded that the quality characteristics of manufacturing processes do not necessarily follow the Normal distribution, e.g., strengths of glass fibres, and lifetimes of products. In this paper, we investigate the extent to which the performances of the OSPRT chart designed for the Normal model deteriorate, in situations where the data distributions are Gamma and Lognormal. Results show that the in-control average run length (ARL) and standard deviation of the run length of the OSPRT chart designed for the Normal distribution deteriorate rapidly as skewness increases. To address this issue, we propose a robust design for the OSPRT chart by adjusting its control limits, known as the skewness correction method. It is shown that the skewness-corrected OSPRT chart enjoys a guaranteed in-control ARL, with a justifiable degradation in its out-of-control performances. Besides, we also show some insights into selecting the charting parameters for the skewness-corrected OSPRT chart in order to achieve an optimum out-of-control ARL performance over various shift sizes. The paper wraps up with an illustrative example of the skewness-corrected OSPRT chart for monitoring the weights of radial tyres.

Petroleum engineering innovations: Evaluating the impact of advanced gas injection techniques on reservoir management

Gas injection techniques have emerged as a critical aspect of modern reservoir management in petroleum engineering. This paper explores the impact of advanced gas injection techniques on reservoir management strategies and their implications for oil recovery. By evaluating recent innovations in gas injection technology, including the use of CO₂, nitrogen, and hydrocarbon gases, this study sheds light on their effectiveness in enhancing oil recovery rates and extending the productive lifespan of reservoirs. Through a comprehensive review of literature and case studies, this paper examines the mechanisms and benefits of various gas injection methods. It delves into the technological advancements that have revolutionized gas injection techniques, such as real-time reservoir simulation, 4D seismic monitoring, smart well technologies, and machine learning integration. These advancements have provided reservoir engineers with unprecedented insights into reservoir behavior, enabling more informed decision-making processes and optimization of EOR operations. However, alongside these advancements come significant challenges that must be addressed. Economic feasibility, technical hurdles, and environmental concerns pose persistent challenges to the widespread adoption of advanced gas injection techniques. The paper discusses these challenges in detail and explores potential solutions to overcome them, emphasizing the importance of sustainable practices and cross-industry collaboration. By analyzing real-world case studies and industry trends, this paper provides valuable insights into the current state of gas injection techniques in reservoir management and offers recommendations for future research and development. It highlights the need for continued innovation, collaboration, and sustainability in petroleum engineering to maximize the potential of advanced gas injection techniques and ensure the efficient and responsible recovery of hydrocarbon resources. This review provides a concise overview of the paper's scope, findings, and implications, inviting readers to delve deeper into the topic of advanced gas injection techniques in reservoir management.

Nanoindentation Response of Structural Self-Healing Epoxy Resin: A Hybrid Experimental-Simulation Approach.

In recent years, self-healing polymers have emerged as a topic of considerable interest owing to their capability to partially restore material properties and thereby extend the product's lifespan. The main purpose of this study is to investigate the nanoindentation response in terms of hardness, reduced modulus, contact depth, and coefficient of friction of a self-healing resin developed for use in aeronautical and aerospace contexts. To achieve this, the bifunctional epoxy precursor underwent tailored functionalization to improve its toughness, facilitating effective compatibilization with a rubber phase dispersed within the host epoxy resin. This approach aimed to highlight the significant impact of the quantity and distribution of rubber domains within the resin on enhancing its mechanical properties. The main results are that pure resin (EP sample) exhibits a higher hardness (about 36.7% more) and reduced modulus (about 7% more), consequently leading to a lower contact depth and coefficient of friction (11.4% less) compared to other formulations that, conversely, are well-suited for preserving damage from mechanical stresses due to their capabilities in absorbing mechanical energy. Furthermore, finite element method (FEM) simulations of the nanoindentation process were conducted. The numerical results were meticulously compared with experimental data, demonstrating good agreement. The simulation study confirms that the EP sample with higher hardness and reduced modulus shows less penetration depth under the same applied load with respect to the other analyzed samples. Values of 877 nm (close to the experimental result of 876.1 nm) and 1010 nm (close to the experimental result of 1008.8 nm) were calculated for EP and the toughened self-healing sample (EP-R-160-T), respectively. The numerical results of the hardness provide a value of 0.42 GPa and 0.32 GPa for EP and EP-R-160-T, respectively, which match the experimental data of 0.41 GPa and 0.30 GPa. This validation of the FEM model underscores its efficacy in predicting the mechanical behavior of nanocomposite materials under nanoindentation. The proposed investigation aims to contribute knowledge and optimization tips about self-healing resins.

Uncertainty Evaluation of the TGA Oxidation Data

Thermogravimetric analysis (TGA) involves the measurement of the changes in mass that occur when a constant heat is applied to an unknown specimen as a function of time or temperature. It is used to evaluate thermal stability, oxidative stability, composition, and estimated lifetime, among other parameters. Given that accurate TGA data is important information for lifetime and stability evaluation of parts and products, an uncertainty evaluation procedure is required to ensure the reliability of the data. In this study, the uncertainty evaluation procedure was established according to the Guide to the Expression of Uncertainty in Measurement (GUM). The mathematically expression of the relationship between the measurand and the input quantities, evaluation of the standard uncertainty of each input estimate, determination of the combined standard uncertainty, and calculation of the expanded uncertainty were performed. The biggest factor affecting the uncertainty of TGA data is the uncertainty of correction factor caused by system calibration

Building smart product-service systems capabilities for circular supply chains in the Industry 4.0 era

A smart product-service system is an integrated digital infrastructure that brings together products and services to provide clients with a full range of options. A smart product-service system is a crucial capability that enhances collaboration among several parties in a supply chain and gives businesses valuable insights into performance. This study investigates (a) the zero-level capabilities (also known as organizational capabilities) that influence dynamic capabilities (i.e., smart circular product-service systems capabilities) building in the Industry 4.0 era while environmental dynamism acts as a moderator, and (b) how the smart circular product-service systems capabilities can support firms’ (financial and environmental) performance. Based on the data collected from the manufacturers who have been actively involved in smart circular product-service system based projects, our findings reveal that three zero-level capabilities (i.e., product lifetime database creation capabilities, analytics and business intelligence capabilities and actuating capabilities) are crucial for building dynamic capabilities (i.e., smart circular product-service systems capabilities) in a volatile business environment. Besides, we also highlight how these capabilities can positively affect firms’ financial and environmental performance.

The declining availability of wild mussel seed for aquaculture in a coastal upwelling system

A general decline in foundation species at the rocky intertidal has been observed during the last decades all around the world and primarily related to climate change. In agreement with that trend, the mussel aquaculture sector in Galicia (NW Spain), the main production area in Europe, has warned over the last years about a decline in the availability of wild mussel seed from the rocky coast. Here we compile for the first time, mussel seed collection reports by mussel farmers in Galicia for the period 2006–2021. We employed that dataset as a proxy of mussel recruitment evolution in the rocky shore for the last 16 years. Temporal analysis of our data confirmed the reported decline (-148 t yr-1), particularly pronounced from 2012 onwards. The data base also allowed us to analyze inter-annual variability according to both, climatic variations and management scenarios. Since cultivated mussels conform a meta-population with wild mussels from the rocky shore, alterations on the market preferences towards smaller individuals at harvest, could also contribute to a reduction in reproductive output. Our results show a decrease in life-time egg production under certain scenarios. Nonetheless, coastal upwelling seems to be the largest factor conditioning recruitment abundance, explaining as much as 60% of the variability observed. Decline on recruitment abundance was highly modulated by the observed increment in frequency of intense upwelling events, exceeding 500 m3 km-1 s-1 between July and November. Meridional winds also determined the spatial recruitment patterns, pointing to the large role of wind forcing on mussel larval dispersal. Our results highlights how alterations on upwelling regimes related to climate change can interact with mussel population dynamics and also condition aquaculture sustainability and food security.

Reproductive and Physiological Responses and Egg Quality Traits of Isa Brown Chickens fed Diets fed Ginger or Turmeric Powder under Tropical Hot Environments

The increasing demand for healthy and low-fat poultry products by consumers has necessitated the use of natural growth promoters to enhance hens’ laying performance. This study investigated the reproductive response and egg quality traits of pullet chickens fed dietary turmeric (Curcuma longa) and ginger (Zingiber officinale) powder. Four hundred and twenty egg-type chicks of Isa Brown at three weeks old were assigned to 5 treatments: basal diet (G0); basal diet supplemented with 1.5 % (G1.5) or 3% (G3) ginger or 1.5(T1.5) or 3% (T3) turmeric during a 60 week trial period. A complete randomized design arrangement was applied. The results showed that the best (p<0.05) hen-day production, hen-housed production, egg mass, feed conversion ratio (FCR), age at first lay and weight at first lay were obtained for birds receiving the 1.5% ginger ration. A higher mortality rate was experienced among the control groups (9.82%), while egg traits revealed significantly higher values of albumen height in hens placed on 1.5 and 3% turmeric powder compared to the other treatment groups. The study concluded that dietary ginger and turmeric enhanced the reproductive performance and egg quality of egg-type chickens over their commercial production lifespan without impairing their overall well-being.

Utilizing Repetitive Sampling in the Construction of a Control Chart for Lindley Distribution with Time Truncation

The monitoring of the process relies on the average product lifetime, which adheres to the Lindley distribution and employs a truncated life test-based attribute control chart. Control limits for these charts are determined through a repetitive sampling procedure. Two inner and outer control limits are established based on the desired average run length (ARL). Tables are generated for varying ARL values by adjusting shift values while keeping the shape parameter of the Lindley distribution constant. The effectiveness of the control charts is assessed through application to real-time data, and the performance of the proposed chart is evaluated using simulation data. A comparative analysis is conducted with single sampling scheme based on ARL values, and the results are presented and discussed.

Connected product lifetime extension tokens (CPLET): Eliciting longevity concepts of connected audio products

Designing longer-lasting connected products is a complex problem, as they include multiple components such as connectivity chipsets, batteries etc. Discussing longevity concepts with industry experts can therefore be challenging due to a lack of framework and ambiguous terminology. In this paper, we are proposing a tangible token kit called Connected Product Lifetime Extension Tokens (CPLET) that allows us to elicit data in interviews. CPLET includes longevity concepts derived from Design for sustainability and Sustainable ICT literature. We utilized CPLET as conversation enablers during semi-structured interviews with 16 participants from nine different companies in the audio industry. This paper introduces CPLET, and an overview of the longevity concepts currently applied to improve the longevity of connected sound products. Utilising such a complementary method contributed to richness of the data, simulated further reflections. guided and broadened the discussions and mitigated terminology confusion.

Two-Stage Life Test Acceptance Sampling Plans for the Weibull Distribution using Trinomial Distribution

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 [.. formula..] 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.. KEYWORDS :Quantile, Two-stage censoring, Trinomial distribution, Weibull distribution.

Flexible, self-healing, and degradable polymeric dielectrics cross-linked through metal–ligand for resistive memory device

The ability to self-heal is a crucial feature in nature, where living organisms can repair themselves when subjected to minor injuries. With an increasing emphasis on environmental sustainability, the concept of biomimetic self-healing polymeric materials has emerged as a prominent trend, promising to significantly extend the lifespan and reliability of products. Studies have shown that one-third of proteins in living organisms require metal cofactors to function properly. It is known that protein-metal interactions can enhance the performance of certain biomaterials, and different choices of metals and ligands can create diverse material properties, influencing characteristics such as hardness, toughness, adhesion, and self-healing abilities. Gelatin is a natural polymer derived from the hydrolysis of collagen, and its unique amino acid structure has led to a wide range of applications. In this research, by introducing aluminum ions that form metal coordination complexes with the carboxyl groups in gelatin, an elastic network with self-healing properties was constructed. This gelatin-based material was utilized as an insulating layer in resistive switching devices. Furthermore, by employing a gelatin substrate of the same composition, the device demonstrated strong interfacial adhesion. The device based on the self-healing gelatin film exhibited excellent electrical performance and mechanical properties. Even after self-healing, it maintained a high ON/OFF ratio of up to 105 and a concentrated distribution of switching parameters. Supported by compelling physical and electrical evidence, this study showcases significant development opportunities for biomimetic materials in green electronic devices.