A real time quality control application for animal production by image processing.

In view of the problems of lagging and poor predictability for ship assembly and welding quality control, the digital twin technology is applied to realize the quality prediction and control of ship group product. Based on the analysis of internal and external quality factors, a digital twin-based quality prediction and control process was proposed. Furthermore, the digital twin model of quality prediction and control was established, including physical assembly and welding entity, virtual assembly and welding model, the quality prediction and control system, and twin data. Next, the real-time data collection based on the Internet of Things and the twin data organization based on XML were used to create a virtual-real mapping mechanism. Then, the machine learning technology is applied to predict the process quality of ship group products. Finally, a small group is taken as an example to verify the proposed method. The results show that the established prediction model can accurately evaluate the welding angular deformation of group products and also provide a new idea for the quality control of shipbuilding.

Quality transitivity and traceability system of herbal medicine products based on quality markers

In this study, we used artificial intelligence (AI) technology to explore for automated medical record quality control methods, standardize the process for medical record documentation, and deal with the drawbacks of manually implemented quality control. In this study, we constructed a medical record quality control system based on AI. We first designed and built, for the system, a quality control rule base based on authoritative standards and expert opinions. Then, medical records data were automatically collected through a data acquisition engine and were converted into structured data through a post-structured engine. Finally, the medical record quality control engine was combined with the rule base to analyze the data, identify quality problems, and realize automated intelligent quality control. This system was applied to the quality control of medical records and five quality control points were selected, including similarities in the history of the present illness, defects in the description of chief complaints, incomplete initial diagnosis, missing in formation in the history of menstruation, marriage, and childbirth, and mismatch between the chief complaints and the history of the present illness. We randomly selected 2 918 medical records of patients discharged in January 2022 to conduct AI quality control. Then we organized medical record quality control experts to conduct an accuracy review, made a comparison with previous manual quality control records, and analyzed the results. The number of quality problems that were verified in the accuracy review was taken as the gold standard and receiver operating characteristic (ROC) curves were drawn for the 5 quality control points. According to the accuracy review performed by medical record quality control experts, the accuracy of AI quality control reached 89.57%. For the sampled medical records, the results of AI quality control were compared with those of previous manually performed quality control and only one problem detected by manual quality control of the sampled medical records was not detected by the AI quality control system. The number of medical record quality problems correctly detected by AI quality control was about 2.97 times that of manual quality control. Analysis of the ROC curves showed that the AUC of the five quality control points of the AI quality control system were statistically significant (P<0.05) and all the AUC values approximated or exceeded 0.9. In contrast, results obtained through manually performed quality control found significant AUC (0.797) for only one quality control point-similarities in the history of present illness (P<0.05). Comparison of the AUC values of the two quality control methods showed that AI quality control system had an advantage over manually performed quality control for the five quality control points. Through the application of medical record quality control system based on AI, efficient full quality control of medical record documentation can be achieved and the detection rate of quality problems can be effectively improved. In addition, the system helps save manpower and improve the quality of medical record documentation.

For the successful operation of the tuberculosis infection foci monitoring system implemented in the city of Moscow since 2021, a quality assessment and control system was developed and implemented, which is a methodology that includes internal and external information control, separate quality control for household and ‘manufactory’ (not household) TB foci, and the functionality of joint assessment of the data from the «TB Foci» registry with information on indicator patients who created foci from other registries of the city’s tuberculosis monitoring system.The implementation of this system significantly improved the quality of data in the «TB Foci» registry, which is a key element in the successful operation of the monitoring system. As a result of the implementation of the quality control system, in 2023–2024 the number of household TB foci, information about which in the register was recognized as problematic, decreased from 326 to 115; the number of cases of lack of information on an «manufactory» TB foci decreased from 232 to 172; the number of suspected TB foci that were taken under monitoring control increased from 161 to 206; the proportion of newly diagnosed tuberculosis patients registered during the year, in whom TB foci were identified, increased from 69.6 to 72.6% (p &lt; 0.05), and the same proportion of newly diagnosed patients from the permanent population – from 85.9 to 89.8% (p = 0.016). One of the indirect results of the introduction of this system was that, with an overall decrease in the number of patients, district TB doctors registered and checked 146 more addresses (TB foci) in 2024 than in the previous year (3,559 addresses).An analysis of the quality control of primary documentation showed that it is critically important for effective monitoring of tuberculosis infection. Periodic monitoring compatible with methodological support provided feedback for rapid problem solving and included training for employees in record keeping.

With the rapid development of world economy, the quality control of products becomes the core and key of competitivenessin the enterprise. The requirements of the complex quality control model are more urgent. Therefore, based on the background of the quality control of steelmaking and rolling material in metallurgy process industry, this paper presents a comprehensive backtracking model of quality control based on the hierarchical. Firstly, analyze the steelmaking and rolling process, then analyze and partition hierarchical operation structure. Secondly, introduce the comprehensive backtracking model, to establishbacktracking model ofthe quality control process. Finally, associatively combine the quality grading hierarchical system structure scheme with backtracking model of the quality control process, and apply it to the actual quality control. Its operation result shows that the classification control and coordination function of the model is good.

本研究旨在探讨申办者在医疗器械临床试验中构建文件质量控制体系的必要性，并介绍基于量化评价的全面质量控制体系。该体系以国内相关规范为指导，涵盖研究中心和申办者文件夹的质控，通过评分机制客观评估文件质量，并结合质控员–监查员–研究者反馈环路以及质控员–质控体系负责人–质控体系环路，实现问题发现、整改和持续改进。超过85%的临床试验质控评分呈现出逐次上升的趋势，质控中问题的发生率也呈现出下降趋势。该体系有效提升了临床试验文件质量，为申办者提供了标准化、可操作的质控流程，为提升我国医疗器械临床试验整体管理水平提供了参考。This study aims to investigate the necessity for sponsors to establish a quality control system for clinical trial documentation in medical device clinical trials and to introduce a quantitatively assessed total quality control system. Guided by domestic regulations, this system encompasses the quality control of both investigator and sponsor Trial Master File (TMF). TMF quality can be assessed objectively through a scoring mechanism, which is integrated with a feedback loop involving quality controllers, monitors, and investigators, as well as a loop between quality controllers, quality control management, and the quality control system, to facilitate problem identification, rectification, and continuous improvement. Over 85% of clinical trial quality control scores showed a trend of successive increase, and the incidence of issues identified during quality control also demonstrated a decreasing trend. The system effectively enhances the quality of clinical trial documentation, providing sponsors with a standardized and operational quality control process, and serves as a reference for improving the overall management level of medical device clinical trials in our country.

The presented article discusses the problems of quality control of construction materials. As we know, the quality of construction materials is one of the most pressing issues at the moment. Quality control means checking whether the quality indicators of goods meet the requirements of the adopted technical normative documents (standards, specifications, etc.). Quality control – set of quality indicators of the material is to check compliance with the requirements. This article also studies analysis of recent research and publications, the effectiveness of quality control methods and structure of functional diagnostics of quality control system. One of the most important areas of quality control is the diagnosis of control problems. Diagnostics – the identification and study of features that characterize the condition of building, structures of buildings and structures in order to identify possible deviations and prevent violations of the normal mode of operation. There are two main types of diagnostics, functional and systematic diagnostics. The main directions of functional diagnostic are described in tabular form. The structure of concrete is also considered here. Execution of concrete structures is a complex process that includes various activities. The basic principle of the development and the application of quality control system during the execution of concrete structures is the process approach. Defining the processes, identification and interaction of sub-processes are performed with the objective of quality monitoring and control that are required in order to achieve concrete structures’ specifications. Quality control system in the area of execution of concrete structures must also comply with national acts, rules, regulations and standards that are essential for concrete structures design, execution and concrete production. The analysis of specific compositions is presented in terms of diagnosing that structure

To deal with the complicated quality tracking and control problem of interenterprise and meet the rapidly changing customer needs in networked manufacturing environment, combined with the similarity of multilayer organization structure and work flow among core enterprise and member enterprises, a multi-agent quality tracking and control model based on fractal for inter-enterprise is proposed. With the aid of fractal concept, the complicated quality tracking and control process of inter-enterprise could be decomposed into multiple quality tracking and control units which are also fractals. Each fractal consists of six function modules: fractal organizer, quality monitor, quality analyzer, quality controller and quality reporter. Using agent technology, each of these modules could autonomously cooperate and negotiate with others while processing its own jobs. By the interaction and negotiation activities of multiagent, quality tracking and control of inter-enterprise could be realized. The dynamic restructuring process (DRP) allows inter-enterprise quality tracking and control to be more efficient and effective by reconfiguring fractals. This research reduces the difficult of inter-enterprise quality tracking and control and lays foundation for the cooperative quality control of manufacturing process.

Appropriate quality assurance (QA) and quality control (QC) procedures have been well developed and validated for dual X-ray absorptiometry (DXA), and are widely applied in multicenter clinical trials to monitor device stability used to check the treatment effects on bone mineral density. This is not yet the case for quantitative ultrasound (QUS) technology, for which no QC approaches have yet been fully tested. The first Achilles (GE-Lunar Corporation, Madison, WI, USA) has been on the market for 10 years (1991). The goal of this study was to develop the QC methodology for the QUS Achilles+ device using its past/current experience (log and maintenance files.) as well as by integrating the progress made over the last years in the ultrasound domain so as to better understand the influence of temperature on ultrasound parameters. Because of the lack of confidence in the external black rubber phantom used in daily QC with the Achilles+, to monitor the device stability, we selected several QC parameters known to be influenced by potential malfunctions as experienced by the maintenance department of GE-Lunar company as well as the physical approach. These are phantom temperature-adjusted speed of sound (PSOS-TC) and broadband ultrasound attenuation (PBUA-TC), water speed of sound error (WSE), water spectrum slope (WSS) and water gain (WG). We used four Achilles+ devices perfectly stable during their entire QC range, to calculate the optimum thresholds (based mostly on 95% confidence interval) for each of these parameters as well as the precision for the in vitro SOS and BUA. An additional not fully stable Achilles device has been used to run a QC procedure example. The precision expressed as the CV was 0.22% and 0.65% for the PSOS-TC and PBUA-TC, respectively. The alarm thresholds used for QC process are +/- 0.6%, +/- 1.9%, +/- 6.8 m/s, +/- 5.3% and +/- 7.3% for the PSOS-TC, PBUA-TC, WSE, WSS and WG, respectively. Applying a logical approach on the impact of each parameter on each other as well as their respective reactivity to malfunctions, we build a QC process flowchart meant to detect real malfunction in the daily QC. We found that in case of real malfunctions, the in vivo SOS should be decreased by 1.33 m/s for each 1 m/s increase in WSE. Unfortunately, in vivo BUA can not be adjusted when real malfunction occurs. Nevertheless, the BUA can be qualified as bad quality data and excluded from the medical interpretation. Using the currently available phantom and parameters, the best possible QC procedures to detect long-term drift in the daily QC of the Achilles+ was developed. To fully validate our approach and gain confidence in the defined limits it is our plan to apply this QC processing to a higher number of QUS devices.

BackgroundColorectal and gastric cancer are major causes of cancer-related deaths. In Korea, gastrointestinal (GI) endoscopic biopsy specimens account for a high percentage of histopathologic examinations. Lack of a sufficient pathologist workforce can cause an increase in human errors, threatening patient safety. Therefore, we developed a digital pathology total solution combining artificial intelligence (AI) classifier models and pathology laboratory information system for GI endoscopic biopsy specimens to establish a post-analytic daily fast quality control (QC) system, which was applied in clinical practice for a 3-month trial run by four pathologists.Methods and findingsOur whole slide image (WSI) classification framework comprised patch-generator, patch-level classifier, and WSI-level classifier. The classifiers were both based on DenseNet (Dense Convolutional Network). In laboratory tests, the WSI classifier achieved accuracy rates of 95.8% and 96.0% in classifying histopathological WSIs of colorectal and gastric endoscopic biopsy specimens, respectively, into three classes (Negative for dysplasia, Dysplasia, and Malignant). Classification by pathologic diagnosis and AI prediction were compared and daily reviews were conducted, focusing on discordant cases for early detection of potential human errors by the pathologists, allowing immediate correction, before the pathology report error is conveyed to the patients. During the 3-month AI-assisted daily QC trial run period, approximately 7–10 times the number of slides compared to that in the conventional monthly QC (33 months) were reviewed by pathologists; nearly 100% of GI endoscopy biopsy slides were double-checked by the AI models. Further, approximately 17–30 times the number of potential human errors were detected within an average of 1.2 days.ConclusionsThe AI-assisted daily QC system that we developed and established demonstrated notable improvements in QC, in quantitative, qualitative, and time utility aspects. Ultimately, we developed an independent AI-assisted post-analytic daily fast QC system that was clinically applicable and influential, which could enhance patient safety.

This study describes and analyses a practical implementation of basic sensory analysis principles in a productive context related to typical products. As a case study, we investigated the quality control (QC) system of Trentingrana cheese, a variety of the protected designation of origin Grana Padano. The production of Trentingrana cheese factories is supervised by their consortium through the assessment of sensory quality attributes by an expert panel; and, depending on the evaluation, the associated dairies receive price premiums or penalties. The procedures applied and the data collected over 8 years were evaluated, and critical points were identified. Ameliorations were suggested in accordance with good sensory practice and were verified over an additional 3‐year period. The QC system has been improved by increasing the number of evaluated samples proportionally to the amount of the production of each dairy, by introducing a balanced experimental design, by monitoring experts' performance and by controlling the sample presentation to avoid systematic effects and psychological errors.Practical ApplicationsWith this work, we demonstrate the viability of applying the sensory approach to quality control (QC) within the food industry of typical products. The QC proposed here is a compromise between the practical constraints of implementing sensory testing procedures in an industrial context and the basic requirements of good sensory practice for collecting reliable data. Nevertheless, the implemented QC represents an example of an efficient strategy for protected designation of origin product valorization, fundamental for preserving both market position and consumer confidence and loyalty toward the product.

The requirements to the system of control over the quality of audit services are analyzed, which are specified in the Law of Ukraine “Audit of Financial Statements and Auditing” from 21.12.2017 No 2258-VIII; Directive of the Ministry of Finance of Ukraine “Approval of the Procedure for Inspection of the Quality Control of Audit Services” from 29.08.2019 No 362; Resolution of the Council for Supervision over Auditing at the State Institution “The Body of Public Supervision over Auditing” from 30.08.2019 No 6/7/13 “Information Questionnaire of Auditing Entity”. It is demonstrated that the quality control system requires corrections of the following: responsibilities of administration and staff of auditing entities for use of the adopted intra-firm provisions on the quality control system, requirements of ISQC1, IAS, the Law of Ukraine “Audit of Financial Statements and Auditing”; the requirements to staff (quality controller, reviewer, assignment partner); identification of threats to the independence and the auditor’s response on the assessed threats; the requirements to reviews of complaints, complicated issues; issues related with non-stop professional training of auditors. Special attention of auditors need to be drawn to the fact that the policies and procedures of the quality control system do not have to be confined to the audit of financial statements, but have to apply to other assignments on giving confidence and related auditor services. Besides that, assessment of threats to the independence has to be conducted for non-auditor services specified in Article 6 of the aforementioned Law of Ukraine.&#x0D; The studies conducted by the author allowed to elaborate procedures for quality control of auditor services; measures to stimulate staff of auditing entities to scrutinize requirements to implementation of the quality control system; obligating documents of auditing firms on assessment of ethical threats; sharing of duties among assignment group members; requirements to qualification of the key partner, quality controller; identification of auditor assignments; solutions of complicated issues and their documenting, measures on control of the assignment at the final phase and quality control of the assignment. The proposed measures are supposed to help auditing entities revise the already operating quality control systems in a timely manner, which will facilitate supply of high quality information to all the users of auditing reports, external quality controllers from the Body of Public Supervision over Auditing and the Auditor Chamber of Ukraine.

HLA typing is a laboratory test that allows to determine HLA antigens or HLA genes of a specific individual. The purpose of this article is to summarize the principles of organizing HLA laboratories, requirements for laboratory personnel, quality management, handling of biological material and standardization of laboratory equipment. Materials and methods. To achieve this goal, we analyzed the current domestic and international regulatory documents, as well as the main scientific publications of the last 5 years. Results. This article provides a detailed description of the general principles of organizing HLA laboratories, including requirements for the education and work experience of personnel, regular advanced training of personnel; management requirements, including maintaining an up-to-date fund of standard operating procedures; control of the correctness of the results obtained through a set of activities for internal laboratory quality control; a system of external quality control of HLA typing; a system of control over the maintenance of equipment in good condition, a system of quality control and continuous monitoring of the reagents used; prevention of conflicts of interest and ensuring the independence of research results from any pressure; regular internal audits of all work processes. The requirements for standardization of laboratory equipment and handling of biological material are also set out. Conclusion. A laboratory performing HLA typing is a complex system, the work of which involves many elements: personnel, infrastructure, technological processes, equipment, work methods, documentation, etc. The quality system of the HLA laboratory is ensured by the interconnectedness and interaction of all the above elements, which must be coordinated. The application of the presented requirements to the organization of HLA laboratories can contribute to increasing the efficiency and optimization of their activities, which, in turn, will improve the efficiency of selecting donor-recipient pairs for transplantation, determining diagnostically significant immunogenetic characteristics.

This study analyzes the implementation of the Crude Palm Oil (CPO) quality control system at an Indonesian palm oil mill, focusing on procedures, methods, and technologies used, as well as the challenges in maintaining product quality according to company standards. A qualitative approach was employed, utilizing participatory observation, in-depth interviews, and document analysis. Data were analyzed thematically and through Juran’s Trilogy framework, encompassing quality planning, quality control, and quality improvement. The quality control system involves the implementation of Standard Operating Procedures (SOPs), manual sorting, Statistical Quality Control (SQC), manual testing, Foss NIRS technology, and data reporting via paper-based forms, WhatsApp, Excel, SAP, and the WD application. Identified challenges include inconsistent adherence to SOPs, delayed reporting, limited technological use, and weak interdepartmental coordination. The analysis indicates that while quality planning and control are adequately implemented, quality improvement remains suboptimal. Recommendations include staff training, SOP simplification, real-time reporting systems, enhanced cross-divisional coordination, and supplier development. Gradual implementation of these strategies is expected to enhance system effectiveness and support long-term sustainability.

Wutou decoction: A latest review on molecular mechanisms, clinical studies, quality control, pharmacokinetic studies, pharmacological effects, toxicity, and target prediction.