Quality Control Practices Research Articles

QC Constellation: a cutting-edge solution for risk and patient-based quality control in clinical laboratories.

Clinical laboratories face limitations in implementing advanced quality control (QC) methods with existing systems. This study aimed to develop a web-based application to addresses this gap, and improve QC practices. QC Constellation, a web application built using Python 3.11, integrates various statistical QC modules. These include Levey-Jennings charts with Westgard rules, sigma-metric calculations, exponentially weighted moving average (EWMA) and cumulative sum (CUSUM) charts, and method decision charts. Additionally, it offers a risk-based QC section and a patient-based QC module aligning with modern QC practices. The codes and the web application links for QC Constellation were shared at https://github.com/hikmetc/QC_Constellation, and http://qcconstellation.com, respectively. Using synthetic data, QC Constellation demonstrated effective implementation of Levey-Jennings charts with user-friendly features like checkboxes for Westgard rules and customizable moving averages graphs. Sigma-metric calculations for hypothetical performance values of serum total cholesterol were successfully performed using allowable total error and maximum allowable measurement uncertainty goals, and displayed on method decision charts. The utility of the risk-based QC module was exemplified by assessing QC plans for serum total cholesterol, showcasing the application's capability in calculating risk-based QC parameters including maximum unreliable final patient results, risk management index, and maximum run size andoffering risk-based QC recommendations. Similarly, the patient-based QC and optimization modules were demonstrated using simulated sodium results. In conclusion, QC Constellation emerges as a pivotal tool for laboratory professionals, streamlining the management of quality control and analytical performance monitoring, while enhancing patient safety through optimized QC processes.

A (sub)field guide to quality control in hippocampal subfield segmentation on high-resolution T2-weighted MRI.

Inquiries into properties of brain structure and function have progressed due to developments in magnetic resonance imaging (MRI). To sustain progress in investigating and quantifying neuroanatomical details in vivo, the reliability and validity of brain measurements are paramount. Quality control (QC) is a set of procedures for mitigating errors and ensuring the validity and reliability of brain measurements. Despite its importance, there is little guidance on best QC practices and reporting procedures. The study of hippocampal subfields in vivo is a critical case for QC because of their small size, inter-dependent boundary definitions, and common artifacts in the MRI data used for subfield measurements. We addressed this gap by surveying the broader scientific community studying hippocampal subfields on their views and approaches to QC. We received responses from 37 investigators spanning 10 countries, covering different career stages, and studying both healthy and pathological development and aging. In this sample, 81% of researchers considered QC to be very important or important, and 19% viewed it as fairly important. Despite this, only 46% of researchers reported on their QC processes in prior publications. In many instances, lack of reporting appeared due to ambiguous guidance on relevant details and guidance for reporting, rather than absence of QC. Here, we provide recommendations for correcting errors to maximize reliability and minimize bias. We also summarize threats to segmentation accuracy, review common QC methods, and make recommendations for best practices and reporting in publications. Implementing the recommended QC practices will collectively improve inferences to the larger population, as well as have implications for clinical practice and public health.

A-202 Quality control design survey reveals 399 ways to do it wrong

Abstract Background The effectiveness of statistical quality control processes to detect unacceptable patient risk depends on the choices that laboratory professionals make for the design of quality control charts and acceptable patient risk. Recommended best practice consists of putting a meaningful recent mean and SD on the QC chart, selecting rules based on the method’s margin for error to unacceptable risk or Sigma value, and basing acceptable risk on clinical need. Methods A survey was circulated through LinkedIn and Labvine. Forty respondents who included their credentials were included in the final analysis. Respondents were asked to select the one most correct answer four questions regarding the parameters that govern the effectiveness of quality control processes. 1. The best source of the mean on the QC chart? (Four choices) 2. Best source of the SD on the QC chart? (Five choices) 3. Best way to select QC rules for each QC sample? (Six choices) 4. If an analytical process “fails,” we should stop reporting before [errors are reported.] (Five choices) A total of 400 potential patterns of QC selections were chosen. (4 * 5 * 5 * 4). Results When asked acceptable error rate if an analytical process “fails,” responses were More than 5% errors are reported - 11%. Any errors are reported - 66% It varies with clinical use of the test - 16% It varies with capabilities of our method - 8% While most respondents chose at least one of the recommended answers for QC chart design and rules, only three chose the best choice for all parameters. Conclusions Despite decades of recommendations of best practice for quality control, typical practice throughout the laboratory community in general does not reflect this. It is time to consider a new approach to teaching, validating and certifying competency in medical laboratory quality control.

A-331 Monitoring Operators Proficiency at Point of Care is Crucial for Reliable Patient Values. A Practical Example with Patient Blood Chloride, Potassium and Sodium Measurands Assayed with i-STAT®

Abstract Background While i-STAT® cartridges offer the Physician a spectrum of analytical methods at the point of care for prompt diagnosis and interventions, these methods have to be harmonized with the laboratory methods in order to reliably detect shifts and trends. With this practical example we illustrate the importance of a program of routine comparisons between the i-STAT® and laboratory methods to detect analytical differences exceeding the CLIA’s criterion and potentially having adverse clinical implications. Methods Patient blood chloride (Cl), potassium (K) and sodium (Na) values as obtained by nurses with i-STAT Chem 8 ™ cartridges (Abbott Laboratories) at the point of care, where daily compared with the values as obtained with the Laboratory method (two cobas 6000®, Roche Diagnostics) using green top BD® lithium heparin tubes (Becton Dickinson) collected within thirty minutes of the i-STAT assay. The data were electronically stored in RALS™ (RALS Informatics) and transferred to Minitab® (Version 21, Minitab Inc.) statistical software. The two analytical methods were compared using the orthogonal and the polynomial ordinary least squares (POLS) regression models and their graphic representations. The aptness of the methods was evaluated with the standardized residuals diagnostics for normality, independence, outliers (Standardized residual >|3|) and influential observations (Hi>0.5). For acceptance of the differences the CLIA’s total error criterion was employed. (CI: target value ± 5%; K: target value ± 0.5 mmol/L; Na: target value ± 4 mmol/L). Results In the first four months of the study the number of differences exceeding the CLIA’s criterion was not acceptable. [Cl: 10% (165/1564); K: 7% (109/1593); Na: 4% (66/1586)]. These differences were occurring throughout the analytical range (AMR). Consequently, the operator’s technique was suspected and the POCT senior technologists (CA, FA) adopted operator specific interventions. This strategy was effective in the following month and the improvements were maintained for seven consecutive months. Monthly differences exceeding the CLIA’s criterion decreased significantly [Cl:1.9% (52/2777): K:0.9% (25/2868): Na:0.5% (15/2896)]. This was clearly illustrated with the dot plot by date and the parallel box plots by month. Regression analysis showed that the orthogonal and the OLS models were equivalent. Cl: Orthogonal y=1.7+0.99x, OLS y=12+0.88x. K; Orthogonal y=0.2+1.2x, OLS y=0.1+0.96x. Na: orthogonal y=3+0.98x, OLS y=14+0.9x. Additionally, the POLS model showed a linear relationship within the AMR intervals with few outliers (Cl=11; K=7; Na=9), no influential observations (Hi<0.5) and equality of monthly regression lines (P>0.05). Conclusions The implementation of daily comparisons between patient values as obtained with the i-STAT method and those as obtained by the Laboratory method in the interval of thirty minutes, allowed the identification of individual operators requiring additional training. This strategy ensured reliable performance for eight consecutive months. This study clearly showed that the addition of continuous supervision and training of operators to quality control and quality assurance practices, ensured the interchangeability of patient values as obtained with i-STAT and those as obtained with the Laboratory method. Electronic collection of data and analysis with appropriate statistical software, such as Minitab, was crucial for the implementation of this program.

WHO guidelines for quality control of herbal medicines: From cultivation to consumption

WHO guidelines serve as a comprehensive framework for ensuring the safety, efficacy, and quality of herbal products throughout their lifecycle, from cultivation to consumption. Here's why adherence to these guidelines is crucial. By following WHO guidelines, manufacturers can implement practices that minimize the risks associated with herbal medicines, including contamination, adulteration, and variability in potency. This helps protect public health and ensures that consumers can use herbal products with confidence. Quality control measures recommended by WHO contribute to the consistency and reliability of herbal medicines. Standardization of production processes and the establishment of quality parameters help maintain the potency and efficacy of herbal products, leading to more predictable therapeutic outcomes. Adherence to WHO guidelines facilitates compliance with regulatory requirements established by national authorities and international bodies. Regulatory agencies often refer to WHO guidelines when developing regulations for the manufacturing, distribution, and labeling of herbal medicines. Compliance with these guidelines helps manufacturers meet regulatory standards and gain market authorization for their products. WHO guidelines provide a harmonized approach to quality control practices, promoting consistency and uniformity in the assessment of herbal medicines worldwide. This facilitates international trade and ensures that products manufactured in one country meet quality standards accepted globally, fostering trust and confidence among consumers and healthcare professionals. The systematic review highlights the ongoing efforts of WHO to review and update guidelines based on emerging scientific evidence and best practices. Adhering to these evolving guidelines encourages continuous improvement in quality control practices and fosters innovation in the herbal medicine industry.

Enhanced Defect Management in Strawberry Processing Using Machine Vision: A Cost-Effective Edge Device Solution for Real-Time Detection and Quality Improvement

Managing defects in agricultural fruit processing is crucial for maintaining quality and sustainability in the fruit market. This study explores the use of edge devices, web applications, and machine vision algorithms to improve defect reporting and classification in the strawberry processing sector. A software solution was developed to utilize edge devices for detecting and managing strawberry defects by integrating web applications and machine vision algorithms. The study shows that integrating built-in cameras and machine vision algorithms leads to improved fruit quality and processing efficiency, allowing for better identification and response to defects. Tested in small organic and conventional strawberry processing enterprises, this solution digitizes defect-reporting systems, enhances defect management practices, and offers a user-friendly, cost-effective technology suitable for wider industry adoption. Ultimately, implementing this software enhances the organization and efficiency of fruit production, resulting in better quality control practices and a more sustainable fruit processing industry.

Quality Management In Ready-Mix Concrete Production In Zambia

The construction industry, a significant contributor to global economies, is projected to yield substantial economic output by 2030 of around $135 trillion. Central to construction is concrete, a widely used material. Ready-mix concrete (RMC), a specialised form of concrete, is gaining prominence due to its rapid setting and superior quality. In Zambia, the increasing demand for RMC highlights the need for stringent quality management to hedge potential structural risks. This study aimed to determine the quality management in ready-mix concrete production in Zambia. Employing a parallel convergent mixed-methods research design to achieve the objectives, qualitative data was collected through semi-structured interviews and desk study and quantitative data was gathered through a structured questionnaire and an observation checklist. The findings of the study reveal that while guidelines exist, adherence varies. Regulatory bodies for standards, engineering and construction play pivotal roles in overseeing RMC quality. However, their execution faces inconsistencies and challenges due to limited resources and a lack of sense of responsibility. Quality control practices were investigated unveiling variations in forward, immediate, and retrospective control phases. Notable trends in proper storage and equipment calibration showed a commitment to precision. Immediate control practices, encompassing sampling and non-compliance management, demonstrated both positive aspects and areas for improvement. Retrospective control showed commitment to comprehensive strength testing and minimal towards split cylinder testing and on-site slump evaluation. In the realm of quality assurance (QA), RMC facilities show substantial adherence to documented QA standard operating procedures and thorough raw material inspections. However, deficiencies in batching and mixing practices and limited adoption of modern weighing systems require improvement. The study recommends creating an industry association for collaboration, enhancing standardised practices, introducing third-party quality audits, and proposing compulsory RMC standards to boost progress in the Zambian RMC industry. Key Words: Quality Management, Ready Mix Concrete, Observation, Desk Study, Zambia.

Study on The Adoption of Historical Record and Chain of Custody By Brazilian Judicial Experts From the Collection to the Disposal of Evidence: A Survey Questionnaire

Objective: The aim of this study is to analyze the practices and protocols of the chain of custody adopted by forensic experts in Brazil, with the intent of evaluating the effectiveness and compliance of these procedures in the evidence production process. Theoretical Framework: This research is based on theories of forensic computing and the importance of evidence preservation. It highlights concepts of quality control and standardized practices in the chain of custody, providing a foundation for understanding best practices and relevant protocols. Method: The methodology employed involves administering a specific questionnaire to a group of forensic experts across Brazil. Data was collected to gather information on chain of custody procedures, including collection, acquisition, examination, analysis, transfer, and disposal of evidence. The study aims to measure the adoption and application of standardized practices by these professionals. Results and Discussion: Results revealed significant variations in the adoption of chain of custody practices among forensic experts. The discussion contextualizes these variations in relation to established theories and practices, identifying gaps and weaknesses in protocols and suggesting areas for improvement. Implications of the Research: The implications of this research include potential improvements in evidence preservation practices and the need for greater adherence to standardized protocols, impacting the reliability and credibility of evidence in judicial processes. Originality/Value: This study contributes to the literature by identifying deficiencies in current practices and suggesting directions for enhancement. The relevance is underscored by the need to improve evidence quality and ensure the integrity of judicial processes.

Deep learning-based quality prediction for multi-stage sequential hot rolling processes in heavy rail manufacturing

Traditional quality control practices in heavy rail manufacturing primarily rely on experiential knowledge and numerical simulations. However, these methods come with significant drawbacks, including high costs, safety concerns, and limited accuracy due to the inadequate consideration of various influencing factors. Despite the accumulation of extensive data by some heavy rail manufacturers in recent years, achieving data-driven quality modeling remains a formidable challenge, mainly due to the complexity of the multi-stage sequential production process. This study presents the Temporal-Spatial Mapping approach to transform isochronous sampling data into spatially aligned data. Additionally, it introduces a multi-objective prediction model, Temporal-Fusion-LSTM (TFL), designed for evaluating the quality of heavy rails. The proposed model presents the Double-Layer LSTM with Time-Steps Fusion (DLL) architecture. The first layer of the DLL architecture targets the temporal transfer regularity within a single stage, while the second layer addresses the transition dynamics across multiple rolling stages in the heavy rail rolling process. Following this, the Local Process Correlation Matrix (LPCM) based on the Maximal Information Coefficient (MIC) is employed to empower the model to comprehend the intricate interactions among parameters in each stage of the rolling process. Finally, the Multi-Gate based Shared-Bottom architecture is employed to accentuate manufacturing processes highly correlated with the target quality indicators during multi-objective prediction. Real production data from a heavy rail factory is utilized to validate the effectiveness of the method. The experimental results unequivocally demonstrate that the proposed method accurately predicts heavy rail quality and facilitates cross-stage prediction, thus establishing the groundwork for data-driven quality diagnosis and pre-control in heavy rail production.

Low-cost, immediate, general-purpose, and high-throughput (LIGHt) smartphone colorimetric screening assay for water-soluble protein

An efficient and rapid method for the detection of total soluble protein in tobacco leaves, utilizing a smartphone-based colorimetric approach has been developed. The proposed low-cost, immediate, general-purpose, and high-throughput (LIGHt) smartphone colorimetric screening assay integrates commercially available microplates, enabling on-site, high-throughput screening of tobacco leaf quality. The study involves preparing protein standard solutions and constructing standard curves using both spectrophotometric and smartphone-based methods. The LIGHt smartphone colorimetry yielded an average relative standard deviation of 10.6 %, a limit of detection of 2 μg/mL, and an average recovery of 93 %. The results demonstrated a comparable performance between intensities from the blue channel and the absorbance values in reflecting protein concentrations, validating the feasibility of utilizing smartphone colorimetry for protein concentration determination. Our approach demonstrates the potential for practical implementation in the field, providing a cost-effective and user-friendly solution for rapid quality assessment in the tobacco industry. The LIGHt smartphone colorimetry enhances quality control practices in the tobacco sector and offers a promising tool for on-site production quality testing in various industries, such as fruits and vegetables.

Minimally invasive cardiac surgeries in 2021: annual report by Japanese society of minimally invasive cardiac surgery.

Although minimally invasive cardiac surgery (MICS) procedures are widely performed throughout Japan, nationwide data regarding treated cases are limited. Up-to-date results for cardiovascular surgery are vital for quality control in clinical practice. Presented here is the 2021 annual report based on data from the Japan Cardiovascular Surgery Database (JCVSD). Records noted in the JCVSD of patients who underwent mitral valve surgery, aortic valve replacement (AVR), coronary artery bypass grafting (CABG), atrial septum defect (ASD) closure, or cardiac tumor resection via right or left minithoracotomy, as well as thoracoscopic- or port-assisted, or robotic-assisted approaches, in 2021 were examined. Perioperative parameters including mortality and morbidity was evaluated. The 30-day and in-hospital mortalities for isolated mitral valve repair (n = 1211) were 0.1% and 0.2%, respectively, while those for all mitral valve repair (n = 2017) were 0.05% and 0.2%, respectively. More than 100 facilities were found to perform fewer than five MICS mitral valve surgery cases per year. As for MICS-AVR, 30-day and in-hospital mortalities for isolated AVR (n = 818) were 0.5% and 0.5%, respectively, while those for all AVR (n = 987) were 0.6% and 1.1%, respectively. Additionally, those for MICS-CABG (n = 400) were 0.8% and 0.5%, respectively. Those for ASD (n = 183) and cardiac tumor (n = 96), were 0.5% and 0.5%, respectively, and 0% and 1.0%, respectively. This is the first report of MICS results of procedures performed in Japan based on the 2021 JCVSD data. Additional results obtained with a similar data collection method are expected and details on MICS are being collected starting 2024.

Comparison of quantitative detection of BCR::ABL1 p210 transcript levels: a multicenter study

Objective: To assess the capability of seven reference medical laboratories to detect BCR::ABL1 p210 transcription levels and to compare the results among those laboratories. Methods: The interlaboratory comparison was carried out in two stages. The samples were prepared by the reference laboratory. The quantitative values of BCR::ABL1 p210 of the comparison samples covered 0.001%-0.01%, 0.01%-0.1%, 0.1%-1%, 1%-10% and>10% in each stage. Real-time quantitative PCR (RT-PCR) and dPCR (digital PCR) were used to examine the samples. The conversion factor (CF) was calculated and validated for each laboratory. Results: In the RT-PCR comparison, one laboratory was failed to detect BCR::ABL1 p210 in fourteen samples at the first stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.133-0.338) and 95% limits of agreement within ±5 folds (upper limit 0.147-0.785, lower limit -0.770--0.109), and the corresponding CF values were calculated and validated. In the dPCR comparison, one laboratory did not report results at the second stage. The results of the other six laboratories were qualified with the bias <±1.2 folds (-0.026-0.267) and 95% limits of agreement within±5 folds (upper limit 0.084-0.991, lower limit -0.669--0.135), and the corresponding CF values were calculated and validated. The samples with BCR::ABL1 p210 quantitative values of 0.01%-0.1%, 0.1%-1%, 1%-10% and >10% could be detected by both RT-PCR and qPCR. When the quantitative value of BCR::ABL1 p210 was 0.001%-0.01%, the detection rate of dPCR was higher than that of RT-PCR (85.56% vs. 68.00%). Conclusions: A good consistency is present among various laboratories. The quantitative value of BCR::ABL1 p210 is comparable among laboratories as shown by the CF value conversion. For quantitative detection of BCR::ABL1 p210 deep molecular reaction, dPCR has a higher positive detection rate and more advantages than RT-PCR. To ensure the accuracy and reproducibility of the BCR::ABL1 p210 test, it is imperative for every laboratory to enhance their daily quality control practices.

Agricultural Engineering Vocational School in Aceh Besar with Behavior Architecture Approach

Currently, Aceh Besar District has a PP Negeri Saree Vocational School in the agricultural section in Saree Aceh Besar, but this school only studies agricultural information. The condition of Aceh Besar District shows that their land use majority is used for agriculture, animal farming and husbandry, fisheries and paddy fields, farm, and other plantations. Abundant natural resources are not processed into a good business due to a shortage of human resources in the field of agricultural engineering. Therefore, it is necessary to include an Agricultural Engineering in those vocational school with aims to create human resources in the field of agricultural machinery and agribusiness. The object design location is on SIM Airport Street, Gani, Kec. Want Jaya, Aceh Besar. The classification of the Agricultural Engineering Vocational School includes the Department of Agricultural Engineering and Agricultural Product Processing Agribusiness. The approach of behavior architecture into the design is behavior setting in completing spatial design, spatial cognition in completing circulation, and environment perception in completing image or building appearance. The analysis used is functional analysis, site analysis and user analysis. The Agricultural Engineering Vocational School in Aceh Besar is designed on an area of 14,950 m2 with multiple building masses. The ground coverage area (KDB) is 40% which is 5,980 m². The facilities in the building meant to support students in the learning process and as well as supporting facilities, those facilities are practice rooms, namely rice threshing machine engineering rooms, rice processing , rice polisher machine, hand tractor, technology for processing agricultural products, quality testing and quality control practice room.

Operators Need to Know Process Control Laboratory QA/QC

Understanding the importance of quality assurance and quality control practices in the process control laboratory is key for operators to produce reliable data and make informed treatment decisions.

DEVELOPMENT AND VALIDATION OF METHODS FOR THE SPECTROPHOTOMETRIC DETERMINATION OF PROSPIDIUM CHLORIDE FOR IDENTIFICATION AND ASSAY ANALYSIS

Objective. The work is devoted to the development and validation of UV-spectrophotometric analysis of propidium chloride, an antitumour drug of the dyspyropiperazine group. The relevance of the study is due to the need to introduce into the practice of quality control of prospidium chloride analysis method characterised by high sensitivity, accuracy, rapidity and availability. Material and methods. The object of the study was a medicinal substance-powder Prospidin (Prospidium chloride, series 271222, expiry date until 12.2027g, produced by «Unitehprom BSU», Minsk). Solutions with working concentration range from 0.05 mol/l to 0.2 mol/l for spectrophotometric analysis were prepared using purified water. Absorption spectra with determination of analytical wavelength (λmax, nm) and value of molar absorption coefficient ε, (l mol-1cm-1) in the range from 200 nm to 400 nm were obtained and analysed on Agilent Cary 60 equipment. Validation parameters were determined in accordance with the regulations of the General Pharmacopoeial Article 1.1.0012.15. Results. Validation evaluation of the developed analytical techniques for the determination of authenticity and active ingredient content by UV spectro-photometry included tests for specificity (in the presence of NaCl 0.9% solution), analytical range (0.05−0.2 mol/L), linearity (r=0.9997), accuracy, preci-sion in terms of repeatability 3.89±0.24 ( ±SD) and intra-laboratory reproducibility (ε=2.1%) and stability. Conclusion. The analysis of electronic spectra of aqueous solutions of propidium chloride demonstrated the presence of R-band absorption (German radikalartig − radical, for systems with unshared electron pairs) with a characteristic wavelength in the far-UV region at λmax=282±0.4 nm, and λmin=255±0.4 nm. It was found that the absorption at λmax in the concentration range from 0.05 mol/L to 0.2 mol/L of a solution of propidine chloride containing nitrogen heteroatoms with unshared electron pairs is due to the implementation of the so-called formally forbidden n→σ* electronic transition involving molecular orbitals. The characteristic appearance of the electronic spectrum with λmax and λmin, compliance with the Beer–Lambert law in the given concentration range, the calculated value of the molar extinction coefficient ε (l mol1cm1) − allow to use the above described spectral characteristics to determine the authenticity and content of the active substance in quality control of prospidium chloride.

An improved skip-lot sampling scheme with resampling mechanism using an advanced capability index

In today’s competitive market, product quality holds significant importance for consumers, motivating companies to prioritise high-quality product development and enhance their competitiveness. Acceptance sampling plans have proven to be indispensable tools in quality control practices, enabling producers and consumers to protect their interests by establishing evaluation rules for product batches. As defective rates decrease in modern manufacturing, skip-lot sampling plans (SkSP) have emerged as a suitable way for lots exhibiting stable and excellent product quality. Additionally, repetitive group sampling plan (RGSP) offers a cost-effective way to maintain desired protection for both parties, especially in costly or destructive inspection scenarios. Therefore, this study integrates the benefits of process capability indices, SkSP, and RGSP to develop a new variables SkSP with RGSP as its reference plan based on an advanced capability index Cpmk (called Cpmk -based SkSP-RGSP). The proposed plan achieves comparable discriminatory power to traditional sampling plans while significantly reducing the required sample size. Detailed tables of plan parameters are given to facilitate effective implementation for practitioners.

Electronic Technologies for Quality Control in the Biscuit Manufacturing Process

By 2030, the biscuit industry may go global due to advancements in electronic tools like eNose, eTongue, and eVision. This shift is governed by precision, productiveness, and regulatory compliance. Ultimately, the automation increase is driven by this consequence. This article will critically look at the issues and benefits arising within the biscuit production field after the shift towards the use of electronic control systems. It analyses the present situation and figures out the ineffectiveness on the part of conventional tools in solving the problem as it currently exists and shows how electronic instruments can be better in aiding visual and sensory inspections. While there have been remarkable achievements, these are persisting, of course, and they include high investment costs, specific skills requirements, and less flexibility when adapting to different production conditions. Without thorough research and development, the challenges in the production of the electronic control systems will still stand and no technology will be created to resolve the problems of the system. This study further reaffirms the need for the invention of modern and improved quality control processes for biscuit manufacturing plants. Through identifying previous methods and approaches and, the advantageous features of each, as well as highlighting shortcomings of current quality control strategies, this paper serves as an effective driving force for the future evolution and further improvement of quality control practices during biscuit production. Comprehensive product evaluation is attended to by employed approaches that analyse future benefits and opportunities as well as drawbacks and risks of the application of electronic quality control systems in the biscuit industry.

MARKETING ON WHEY PROTIEN

Whey protein has emerged as a prominent player in the health and fitness industry, recognized for its numerous benefits and versatile applications. This abstract provides an overview of key considerations and strategies involved in the marketing of whey protein products. The marketing of whey protein requires a multifaceted approach that encompasses regulatory compliance, quality control, consumer education, market research, and sustainability practices. Regulatory compliance is essential to ensure adherence to labeling requirements, health claims regulations, and product safety standards across different jurisdictions. Quality control measures play a pivotal role in maintaining product integrity and safety, encompassing raw material testing, manufacturing processes, and finished product testing. Consumer education is critical for dispelling myths and misinformation surrounding whey protein, providing consumers with accurate information about its benefits, usage guidelines, and safety considerations. Market research is indispensable for understanding consumer preferences, identifying market trends, and informing marketing strategies. Sustainability practices are increasingly important considerations, with consumers favoring brands that prioritize ethical sourcing, environmental stewardship, and corporate social responsibility.

A STUDY ON QUALITY CONTROL AND WASTE MANAGEMENT PROCESS IN MODERN BREAD COMPANY

The modern bread industry faces challenges in maintaining stringent quality control standards while effectively managing waste. This study aims to explore and propose strategies to enhance quality control and waste management processes in modern bread companies, contributing to their sustainability and competitiveness. Utilizing a mixed-methods approach, data will be collected through surveys, interviews, and case studies from multiple modern bread companies. The research will investigate current quality control practices, waste management systems, and their associated challenges. Additionally, the study will identify industry best practices and technological innovations in quality control and waste management. The findings will inform the development of a comprehensive framework for improving quality control and waste management processes tailored to the specific needs of modern bread companies. This framework will encompass strategies for optimizing production processes, implementing advanced quality control measures, and adopting sustainable waste management practices. Moreover, the study will address the integration of digital technologies and data analytics to enhance monitoring and decision-making in quality control and waste management. The proposed framework aims to enhance product quality, reduce waste generation, and minimize environmental impact, thereby contributing to the overall sustainability and profitability of modern bread companies. The research outcomes will provide valuable insights and actionable recommendations for industry practitioners, policymakers, and stakeholders involved in the bread manufacturing sector. Keywords: Quality Control, Waste Management, Bread Industry, Sustainability, Digital Technologies, Production Optimization, Environmental Impact, Competitiveness.

Machine Learning for Quality Control in Traditional Textile Manufacturing

This research is centered on the practical implementation of machine learning and computer vision technologies to enhance production quality control within the traditional textile industry. The traditional textile sector, known for labor-intensive practices, has slowly adapted to digital transformation. We present a practical case study from Bandung, Indonesia, to validate the effectiveness of our approach in real-world textile manufacturing. By emphasizing machine learning and computer vision, this research narrows the gap between traditional textile practices and digitalization, offering tailored solutions for manufacturers seeking to excel in today's rapidly changing global market. The findings provide valuable insights into the challenges and opportunities of using machine learning and computer vision for production quality control in traditional textile manufacturing. The machine learning models in the study showed good accuracy, ranging from 75% to 100% under various lighting conditions in real-world textile manufacturing environments, confirming their suitability for practical quality control applications.