Production Quality Research Articles

MDC-Net: multimodal defect captioning network for surface steel defects

Abstract During steel production, ensuring the integrity of the product’s surface is crucial for maintaining a competitive edge. Detecting surface flaws is a key component in preserving high standards of production quality, affecting both the end product’s reliability and the efficiency of the manufacturing process. Traditional methods for identifying these defects have relied heavily on manual inspection or basic computer vision techniques, both of which present a significant challenge in terms of accuracy and the health and safety of the inspectors. This paper explores an innovative approach by integrating a sequence generation model incorporating the transformer architecture, enhancing the detection of defects in the production of quality hot-rolled steel sheets. This method, which solves object detection through the lens of sequence generation, offers a more intricate analysis of images, enabling a comprehensive examination of surface anomalies along with detailed annotations regarding their nature and precise location. The approach not only proposes to increase the accuracy of defect detection but also highlights its adaptability for broader industrial uses.

Digital Intelligence Empowerment and New Quality Productivity of Listed Enterprises in Fujian Province

This paper examines the impact of digital intelligence transformation on new quality productivity in enterprises in Fujian Province. It highlights the challenges these enterprises face, such as limited talent and infrastructure, in adopting technologies like cloud computing, big data, and artificial intelligence. The research finds that digital intelligence can enhance innovation, efficiency, and market adaptability, driving significant improvements in productivity. The study emphasizes the need for organizational changes and government support to overcome barriers and accelerate transformation, offering valuable insights for both academia and industry.

Efficient production of honey-enhanced banana chips: A multi-objective optimization approach

Food industries aim to optimize processes for quality products in shorter times. For fruits, specific storage and transport conditions are essential to maintain quality, extend shelf life, and preserve sensory and nutritional properties. This study aims to maximize honey incorporation into banana slices during osmotic dehydration, assisted by ultrasound, while minimizing processing time. The process includes three stages: 1) 20 min ultrasound-assisted immersion in distilled water, 2) osmotic dehydration in hypertonic honey solution, and 3) hot air drying. The second and third stages were mathematically modeled using a multi-objective MINLP optimization in GAMS with the Baron solver. Optimal conditions achieved an 8.75% gain in soluble solids (SG) in 11.48 h, reducing processing time by 64% with a 70% honey solution. This optimization allows a compromise solution between two contradictory objectives for planning the production process: maintaining product quality and reducing production time. The process leads to lower total costs.

Organoleptic Quality and Production Cost Assessment of Muskmelon, Honey and Inulin-based Greek Yoghurt

The present study was undertaken to evaluate the sensory quality and cost of production of Greek yoghurt enriched with Muskmelon (Cucumis melo) pulp, honey, and inulin, targeting the development of a functional and consumer-acceptable fermented dairy product. The experiment was conducted using a Completely Randomized Design (CRD) with five treatments and five replications each. The study was carried out at the Division of Dairy Science, Dr. Sharadchandra Pawar College of Agriculture, Baramati. During the academic year 2023 to 2025. Greek yoghurt was prepared by incorporating muskmelon pulp at levels of 0, 5, 10, 15, and 20 percent along with 12 percent honey and 0.8 percent inulin into standardized cow milk. The yoghurt was fermented using a mixed culture of Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus, followed by straining to obtain Greek yoghurt. Sensory evaluation was carried out by panel of 5 semi-trained judges using a 9-point hedonic scale for parameters like colour and appearance, flavour, body and texture, taste and overall acceptability. Cost of production was calculated for each treatment based on ingredient cost and processing inputs. Among the five treatments, the Greek yoghurt sample containing 15 percent muskmelon pulp (T3) exhibited the highest sensory scores for all attributes, with an overall acceptability score of 7.77. Higher pulp concentrations negatively impacted texture and flavour. The cost analysis showed T3 to be the most economical formulation due to optimal ingredient usage and high acceptability. Greek yoghurt formulated with 15 percent muskmelon pulp, 12 percent honey and 0.8 percent inulin was found to deliver the best balance of sensory quality and cost efficiency.

Irrigated cultivation of sour passion fruit under saline stress and application of cassava wastewater biofertilizer

Sour passion fruit is an important fruit crop in the semi-arid northeastern Brazil, but the high salt concentration in irrigation water poses a major challenge for its cultivation expansion. This study studied to the impact of cassava wastewater biofertilizer doses as a salt stress mitigator on the growth, production, and postharvest quality of sour passion fruit cv. BRS Sol do Cerrado under saline irrigation. Conducted in a Campina Grande, PB, Brazil greenhouse, the experiment used a completely randomized design with three replicates in a split-plot scheme. Plots had varying electrical conductivity of irrigation water (ECw) (0.9, 1.8, 2.7, 3.6, and 4.5 dS m−1), while subplots used four cassava wastewater doses were based on potassium content (25, 50, 75, and 100%). ECw at 0.9 dS m−1 adversely impacted the plant’s physiological indices, growth, and production. Cassava wastewater at 75% potassium levels reduced these negative effects for ECw of 0.9 and 1.8 dS m−1. Higher doses exacerbated salt stress damage. ECw levels above 3.0 dS m−1 decreased pulp pH and ascorbic acid. A biofertilizer dose at 100% potassium is excessive under these conditions in a semi-arid environment.

Research on the discrimination of the rate of tobacco silk yielding based on machine learning

To address the problem of anomaly detection and root cause tracing in cigarette production rate data, a novel machine learning algorithm was proposed. This study employs a variety of algorithms to detect anomalies in silk yield data, culminating in a final result derived through a weighted method. Following the identification of anomalous data, key factors are pinpointed using correlation and regression analysis algorithms. Experimental results demonstrate that this algorithm excels in identifying data anomalies and tracing their origins, significantly contributing to the enhancement of tobacco production yields. The application of machine learning in anomaly detection and root cause analysis within the tobacco industry represents a significant advancement in production efficiency and quality control. By accurately identifying anomalies and their underlying causes, this algorithm ensures higher precision in monitoring production processes and facilitates proactive adjustments to maintain optimal yield levels. The integration of multiple algorithms and a weighted method enhances the robustness and reliability of the anomaly detection process. Ultimately, this study provides a valuable tool for improving operational effectiveness and production outcomes in the tobacco industry, highlighting the broader potential of machine learning applications in industrial settings.

Exploring the Influence of MCN Agencies on Content Creation by Short-Video Influencers Among Chinese College Students

This qualitative study explores the complex influence of Multi-Channel Networks (MCNs) on content creation by Chinese college student influencers on short video platforms, with TikTok as the primary focus. Through depth interviews with ten purposefully sampled student influencers affiliated with MCNs, the study uncovers how these networks shape content strategies, enhance audience engagement, and guide career paths. Employing a qualitative research paradigm, the study elicits rich, contextualized data on the subtle ways MCNs impact the content creation process. Findings reveal that MCNs play a crucial role in determining content themes, improving production quality, and facilitating marketing opportunities. However, concerns about creative control and long-term career sustainability also emerge. This research contributes to a deeper understanding of the dynamics between MCNs and content creators in China's digital media landscape, highlighting both opportunities and challenges for college student influencers. The insights provided are vital for researchers, policymakers, and industry stakeholders to foster a more equitable and sustainable environment for content creators in the evolving short video ecosystem.

The Impact of Private Equity Investment on the New Quality Productivity of the Enterprises in Strategic Emerging Industry

Private equity investment brings incremental funds to enterprises, but can it enhance the new quality productivity of enterprises and facilitate their high-quality development? From the perspective of technological innovation, this paper uses the relevant data of 378 listed companies in China’s strategic emerging industries from 2019 to 2023 to study the impact of private equity investment on the new quality productivity of strategic emerging industry enterprises, further examines the mediating role of technological innovation capability and the moderating role of regional science and technology finance levels, and investigates the heterogeneity of enterprise property rights nature, as well as industrial nature. The research results show that: First, private equity investment has a significant positive impact on the new quality productivity of enterprises in strategic emerging industries; Second, private equity investment can promote the development of new quality productivity of enterprises in strategic emerging industries by enhancing their technological innovation capability. Third, the level of regional science and technology finance positively moderate the promoting effect of private equity investment on the new quality productivity of enterprises in strategic emerging industries. Fourth, the new quality productivity of non-state-owned enterprises is more sensitive to private equity investment. The new quality productivity of enterprises in the new generation of information technology industry, new energy vehicle industry, new energy industry, energy conservation and environmental protection industry and digital creative industry is more sensitive to private equity investment. The research conclusion provides relevant inspirations for further utilizing private equity investment to enhance the new quality productivity of enterprises in strategic emerging industries.

A Review of Research on the Coordinated Development of New Quality Productivity and Vocational Education: Connotation, Logic, and Path

This study systematically reviews research on the coordinated development between New Quality Productivity and vocational education, analyzing their connotations, logical relationship, and paths to synergy. New Quality Productivity drives industrial transformation through technological innovation, and its coordination with vocational education carries profound significance. The two are interlinked through mutual driving forces, reciprocal support, and complementary promotion. Achieving coordinated development requires policy guidance, innovation in industry-education integration, optimization of teaching staff, and advancement in digitalization. While current challenges remain, future research should deepen this field to enhance integration and cultivate innovative talent for economic and social development.

Exogenous application of gibberellic acid and brassinosteroids: Synergistic effects on Nutmeg's growth, yield and color attributes

This study evaluates the effects of preharvest spray applications of gibberellic acid (GA3) and brassinosteroids on the growth, fruit drop, fruit set, yield and colour characteristics of nutmeg. Treatments included combinations of GA3 and brassinosteroids with boric acid and calcium nitrate, applied during the flowering stage. The experiment followed a randomized block design with seven treatment combinations; each replicated three times. Among the treatments, the application of GA3 at 75 ppm combined with 0.3 % boric acid yielded the most favourable results. This combination significantly enhanced vegetative growth parameters, including plant height (8.9 m), leaf length (14.5 cm) and leaf width (5.5 cm). It also resulted in the highest fruit set percentage (80.95 %) and the lowest fruit drop rate (43.63 %). Furthermore, this treatment produced the highest yield, with 680 fruits per tree, amounting to 54.46 kg per tree. It also maximized both fresh and dry aril yields (3.19 kg and 2.58 kg per tree, respectively) as well as nut yields (9.08 kg fresh and 6.78 kg dry per tree). In addition, it improved the brightness and vibrancy of the aril colour, achieving the highest values for L* (66.2), a* (53.8) and b* (31.2). Overall, these findings highlight the potential of GA3 and brassinosteroids, especially in combination with boric acid, to enhance mace yield, quality and colour stability offering a promising strategy for improving nutmeg production and postharvest quality.

Harnessing Innovation for a Greener Future: Unpacking the Interplay of Natural Resources, Institutional Quality, and Green Productivity in OECD and BRICS Nations

Harnessing Innovation for a Greener Future: Unpacking the Interplay of Natural Resources, Institutional Quality, and Green Productivity in OECD and BRICS Nations

Usulan Perbaikan Mutu CPO dengan Metode Six Sigma pada PT. PSU PKS Tanjung Kasau

PT. PSU Tanjung Kasau is one of the BUMD’s of North Sumatra Province in the agricultural sector. The product produced is Crude Palm Oil (CPO). CPO has quality parameters, namely free fatty acid (FFA) content, water content and dirt content. Based on data on the results of CPO production quality in January and February 2024, there are still several quality parameters that exceed the standards set by the company. Therefore, to determine the level of quality, factors that cause a decrease in the CPO level, and proposed improvements, research was carried out using the Six Sigma method with the stages of define, measure, analyze, improve and control (DMAIC). After processing, the CPO DPMO value was obtained of 676,451.85 with a sigma value of 1.04. Then using the Pareto diagram, it was obtained that the water content and free fatty acid content caused a decrease in CPO quality. Then based on the fishbone diagram, the human factor was obtained which was a lack of discipline, the material factor was bad qualityof TBS, and the machine factor was less than optimal machine performance and the method factor was not in accordance with the SOP. Proposed improvements to overcome the problems include conducting training and evaluation, increasing the supply of TBS and improving infrastructure, conducting regular monitoring and maintenance of machines, improving SOP’s and implementing SOP’s so that corporate governance can run well. Keywords : CPO, DMAIC, Quality, Six Sigma

Analisis Pengendalian Kualitas Produk Pakan Ternak pada PT XYZ dengan Metode Six Sigma dan FMEA

Product quality has an important role in maintaining customer trust and the sustainability of the company. PT XYZ, which produces various types of animal feed, faces the problem of defects in pellet products, such as different feed size shapes, hot feed temperatures, and uneven feed colors. These defects not only affect production efficiency but can also reduce customer satisfaction. This research needs to be carried out so that PT XYZ can identify the cause of the defect and provide improvement proposals using the Six Sigma method through the DMAIC (Define, Measure, Analyze, Improve, Control) stage with Failure Mode and Effect Analysis (FMEA). The results showed that the main causes of defects were unstable engine condition, suboptimal cooling system, and dirty or worn engines, with the highest RPN values of 504, 210, and 448, respectively. The proposed improvements include standardization of engine settings, routine maintenance, and machine cleaning before use. The implementation of this recommendation is expected to improve product quality, reduce defects, increase operational efficiency, and strengthen the company's competitiveness. In addition, this research also provides continuous guidance for PT XYZ in managing a more standardized and quality production process to achieve a competitive advantage in the market. Keywords: DMAIC, FMEA, Product Quality, Six Sigma

The relationship between FDI quality, new quality productivity forces, and economic resilience in China’s Yangtze River Delta region: insights from an empirical spatial Durbin model

In the context of increasing natural disasters, volatile geopolitical dynamics, and rising anti-globalization trends—particularly in the post-pandemic era—enhancing economic resilience has become crucial. This study investigates how FDI quality and new quality productivity forces influence economic resilience across 41 cities in China’s Yangtze River Delta (2009–2022). We establish measurement systems for FDI quality, new quality productivity forces, and economic resilience, conducting empirical analyses across temporal and spatial dimensions. Three main findings emerge: First, significant spatial disparities exist, with eastern/northern regions outperforming western/southern areas in all three dimensions. While new quality productivity forces and resilience show upward trends with fluctuations, FDI quality exhibits stagnation and regional imbalances. Second, temporal analysis reveals a U-shaped relationship where FDI quality affects both new quality productivity forces and resilience, with new quality productivity forces demonstrating significant mediation effects. Third, spatial econometric results show an inverted U-shaped spillover effect of FDI quality on neighboring regions’ resilience. These findings provide empirical evidence on the mechanisms through which external investments (FDI) and internal innovation capabilities (new quality productivity forces) jointly shape regional economic resilience, offering valuable insights for policymakers to address development disparities and enhance risk resistance capacities in the new era.

A transposon-based transient transfection system in CHO-K1 cells enables quality prediction of stable cell line proteins.

In biologics drug discovery, transient protein expression is widely used to rapidly produce biologics, thereby accelerating the identification of lead candidates. However, the accuracy and consistency of predictingfurther product quality in large-scale production needs to be considered, especially with respect to physicochemical properties and posttranslational modifications. With this in mind, a transient expression system utilizing Chinese hamster ovary K1 (CHO-K1) has been established, whichintegrates high expression capability with quality profiles similar to those of the protein produced by stable cell lines. A well-designed vector containing transposon elements overcomes the blindness of random integration andensuresthe sustained viabilityof cells and production capability, thus addressing the critical bottlenecks in classical transiently transfected workflows. Combined with the optimization of various transfectionparameters, the customized platform achieved a titer over 1.5g/L in the production of abispecific antibodywhile maintaining a proportion of fragments, aggregates and glycosylation patterns that are comparable to those of the stable cell line protein.More importantly, this platform also demonstrated reliability in terms of quality across diverse antibody formats. This innovative protein expression platform bridges the gap between transient and stable expression on the basis of CHO-K1, ensuring the consistency of host cell types throughout the antibody discovery and development process.

Gastroesophageal Reflux Disease and Its Associations with Depression, Other Psychiatric Disorders and Patient Quality of Life: A Literature Review

Gastroesophageal reflux disease (GERD) is a prevalent gastrointestinal disorder whose incidence has been increasing in recent years. Due to its potential extraesophageal manifestations, diagnosing GERD can be challenging. Emerging evidence suggests that GERD may have significant implications not only in the digestive tract, including effects on mental health. This review investigates the potential associations between GERD and psychiatric disorders such as depression, anxiety, bipolar disorder and sleep disturbances, as well as its impact on quality of life and productivity. Relevant literature was found through databases including PubMed, ResearchGate and Google Scholar with a focus on meta-analyses and systematic reviews. The findings indicate that GERD is associated with a higher risk of mental health disorders, particularly depression and sleep disorders. These relationships may be bidirectional. Additionally, recent studies highlight promising non-pharmacological interventions that may alleviate GERD symptoms. Understanding the psychological consequences of GERD and integrating mental health screening into gastroenterological practice could potentially improve patient outcomes. However, further research is needed to clarify the mechanisms linking GERD and mental health.

Research on a Method for Identification of Chinese Rose Leaf Pests and Diseases Based on a Lightweight CR-YOLO Model.

Accurate and rapid detection of pests and diseases on Chinese rose leaves is crucial for horticultural management and production quality. Despite advances in detection methods, challenges such as complex backgrounds, variable lighting conditions, and subtle disease manifestations in natural environments often lead to diminished detection accuracy and high computational costs. Traditional detection models typically require substantial computational resources, limiting their practical applicability in real-world horticultural settings. In response to these challenges, we introduce CR-YOLO (Chinese Rose YOLOv7-tiny), an enhanced lightweight detection framework derived from YOLOv7-tiny. Replacement of standard convolutions with distributed offset convolutions in the backbone network to reduce computational complexity while preserving feature extraction capabilities, integrating SimAM (parameter-free attention) to boost feature discrimination, and adopting Focal-EIOU loss to accelerate convergence. Experimental results on a comprehensive Chinese rose leaf pest dataset collected under natural conditions demonstrate that CR-YOLO achieves impressive metrics with precision, recall, mAP0.5, and mAP0.5-0.95 of 95.1%, 94.5%, 97.6%, and 93.7%, respectively. Compared to YOLOv7-tiny, CR-YOLO improves key metrics by 11.8-26.7 percentage points. When evaluated against other prevalent detection models, CR-YOLO shows superior performance with mAP0.5 improvements of 6.9-11.4 percentage points while reducing computational overhead by 3.8-31.5%. The model's exceptional performance and lightweight architecture make it particularly suitable for resource-constrained platforms, enabling real-time monitoring in practical horticultural applications and advancing precision agriculture through efficient, automated pest and disease detection.

Mediating Effect of Psychological Inflexibility, Insomnia, and Resilience on the Association Between Pain and Depression Among Patients With Chronic Pain.

Chronic pain, impacting roughly 20% of the population, significantly affects quality of life and productivity. This study explored the mediating effects of psychological inflexibility, insomnia, and resilience on the association between pain and depression in patients with chronic pain. Data on demographics, pain characteristics, and psychological factors were obtained through an online survey involving 100 patients from the Asan Medical Center Pain Clinic. Measures included the Patient Health Questionnaire-9, Insomnia Severity Index (ISI), Acceptance and Action Questionnaire-II (AAQ-II), and Brief Resilience Scale (BRS). Statistical analyses involved correlation, linear regression, and mediation analyses. A linear regression analysis revealed that the severity of depression was predicted by pain severity (β=0.18, p=0.018), ISI (β=0.22, p=0.010), AAQ-II (β=0.32, p<0.001), and BRS (β=-0.28, p=0.002). The mediation analysis showed that pain severity directly influenced depression severity. This relationship was partially mediated by ISI, AAQ-II, and BRS. This study underscores the necessity for holistic approaches in chronic pain management that address the mediating effect of psychological factors. Targeted interventions focusing on insomnia, psychological inflexibility, and resilience can significantly enhance mental health outcomes for patients with chronic pain.

Effects of Legume–Grass Mixture Combinations and Planting Ratios on Forage Productivity and Nutritional Quality in Typical Sand-Fixing Vegetation Areas of the Mu Us Sandy Land

Monoculture and legume–grass mixed cropping are the two most common planting methods, with mixed cropping generally demonstrating higher hay yield and superior nutritional quality compared to monoculture. However, research on legume–grass mixed cropping for establishing cultivated pastures in typical sand-fixing vegetation areas of the Mu Us Sandy Land remains scarce. These knowledge gaps have hindered the synergistic integration of forage production and ecological restoration in the region. This study conducted mixed cropping trials in the sand-fixing vegetation zone of the Mu Us Sandy Land using Dahurian wildrye (Elymus dahuricus), Mongolian wheatgrass (Agropyron mongolicum), and Standing milkvetch (Astragalus adsurgens) to investigate the effects of species combinations and planting ratios on forage productivity and nutritional quality, aiming to determine the optimal planting strategy. Results showed that in the first establishment year, the yield of all mixed cropping systems significantly exceeded that of monocultured Dahurian wildrye and Mongolian wheatgrass. All mixed cropping combinations exhibited land equivalent ratios (LER) and relative yield totals (RYT) below 1, indicating varying degrees of interspecific competition during the first year, with grass species generally demonstrating stronger competitive abilities than legumes. Mixed-cropped forages showed higher crude protein, crude fat, and crude ash content compared to monocultures, alongside lower neutral detergent fiber (NDF) and acid detergent fiber (ADF) levels, suggesting improved relative feed value (RFV). Among the combinations, E5A5 and E6A4 (5:5 and 6:4 ratio of Dahurian wildrye to Standing milkvetch) achieved higher RFV, with RFV gradually declining as the legume proportion decreased. In conclusion, both monoculture and legume–grass mixed cropping are viable in the Mu Us Sandy Land’s sand-fixing vegetation areas and the E5A5 combination (5:5 ratio of Dahurian wildrye to Standing milkvetch) as having the highest overall score, demonstrating that this mixed cropping ratio optimally balances yield and nutritional quality, making it the recommended planting protocol for the region. This mixed cropping system offers a theoretical foundation for efficiently establishing artificial pastures in the Mu Us Sandy Land, supporting regional pastoral industry development and desertification mitigation.

The impact of soil treatments and fertilizer application rates on increasing the yield of winter wheat varieties in southeastern Kazakhstan

New and resource-saving tillage technologies meet the requirements of soil and environmental agriculture to a greater extent than traditional ones (soil structure disturbance, degradation, erosion, etc. are excluded). In agricultural culture, including in irrigated agriculture of irrigated regions of Kazakhstan, new, non-traditional approaches based on the cultivation of field crops are required, ensuring the achievement of potential opportunities for varieties and hybrids of cultivated crops, with the aim of rational use of land and water resources, as well as preserving and increasing potential soil fertility. The article provides long-term experimental data on the advantages of resource-saving technologies and their positive impact on the quality and cost of crop production, which compete with previously used traditional technologies. The purpose of our research is to determine the effectiveness of tillage, the seeding rate of different varieties of winter wheat and the dose of fertilizers to obtain a high yield of grain with the best qualities. In the conditions of semi-secured bogara in the south-east of Kazakhstan, plowing to a depth of 20-22 cm and minimal tillage turned out to be the optimal sowing period for the second with a seed sowing rate of 3 million. germinated seeds per hectare and with the addition of 60 kg of nitrogen and phosphorus fertilizers. The optimal sowing period with zero tillage was the third with a seed sowing rate of 3 million. germinated seeds per hectare and with the addition of 60 kg of nitrogen and phosphorus fertilizers.