Key Quality Characteristics Research Articles

A Real-Time Quality Control System Based on Manufacturing Process Data

Quality prediction is one of the key links of quality control. Benefitting from the development of digital manufacturing, manufacturing process data have grown rapidly, which allows product quality predictions to be made based on a real-time manufacturing process. A real-time quality control system (RTQCS) based on manufacturing process data is presented in this paper. In this study, the relationship between the product real-time quality status and processing task process was established by analyzing the relationship between the product manufacturing resources and the quality status. The key quality characteristics of the product were identified by analyzing the similarity of the product quality characteristic variations in the manufacturing process based on the big data technology, and a quality-resource matrix was constructed. Based on the quality-resource matrix, the RTQCS was established by introducing an association-rule incremental-update algorithm. Finally, the RTQCS was applied in actual production, and the performance of RTQCS was verified by experiments. The experiments showed that the RTQCS can effectively guarantee the quality of product manufacturing and improve the manufacturing efficiency during production.

Long-Term Stability and Differentiation Potential of Cryopreserved cGMP-Compliant Human Induced Pluripotent Stem Cells.

The clinical effectiveness of human induced pluripotent stem cells (iPSCs) is highly dependent on a few key quality characteristics including the generation of high quality cell bank, long-term genomic stability, post-thaw viability, plating efficiency, retention of pluripotency, directed differentiation, purity, potency, and sterility. We have already reported the establishment of iPSC master cell banks (MCBs) and working cell banks (WCBs) under current good manufacturing procedure (cGMP)-compliant conditions. In this study, we assessed the cellular and genomic stability of the iPSC lines generated and cryopreserved five years ago under cGMP-compliant conditions. iPSC lines were thawed, characterized, and directly differentiated into cells from three germ layers including cardiomyocytes (CMs), neural stem cells (NSCs), and definitive endoderm (DE). The cells were also expanded in 2D and 3D spinner flasks to evaluate their long-term expansion potential in matrix-dependent and feeder-free culture environment. All three lines successfully thawed and attached to the L7TM matrix, and formed typical iPSC colonies that expressed pluripotency markers over 15 passages. iPSCs maintained their differentiation potential as demonstrated with spontaneous and directed differentiation to the three germ layers and corresponding expression of specific markers, respectfully. Furthermore, post-thaw cells showed normal karyotype, negative mycoplasma, and sterility testing. These cells maintained both their 2D and 3D proliferation potential after five years of cryopreservation without acquiring karyotype abnormality, loss of pluripotency, and telomerase activity. These results illustrate the long-term stability of cGMP iPSC lines, which is an important step in establishing a reliable, long-term source of starting materials for clinical and commercial manufacturing of iPSC-derived cell therapy products.

Analysis of Selected Hop Aroma Compounds in Commercial Lager and Craft Beers Using HS-SPME-GC-MS/MS

In recent years, hop aroma emerged as a key quality characteristic of popular beer styles. Accordingly, the instrumental analysis of hop derived odorants in beer advanced as a must have analytical technique for research and quality control purposes. Still, the analysis of hop aroma compounds is challenging. Substance concentrations might strongly vary depending on the beer style, matrix effects might hinder reliable quantification, and SPME-GC-MS based protocols are suspected to lack (long-term) stability. The current paper describes the validation and application of a headspace solid-phase microextraction (HS-SPME) – gas chromatography (GC) – tandem mass spectrometry (MS/MS) method for analysis of 16 selected hop aroma compounds in beer. To enable rapid and reliable quantification of selected terpenes, terpenoids, and esters across a wide working range (1–1000 µg/L), instrumental parameters were optimized and three stable isotope labeled standards, namely d5-linalool, d2-myrcene, and d6-citronellol were synthesized and characterized by nuclear magnetic resonance (NMR) spectroscopy. Extensive method validation and routine application proves the excellent selectivity, sensitivity, and robustness of the method in all relevant matrices such as light hopped lagers and dry-hopped ales.

Effect of high pressure processing on the safety, shelf life and quality of raw milk

High pressure processing (HPP) was investigated as an alternative to standard raw milk processing. Different pressure levels (400–600 MPa) and exposure times (1–5 min) were tested against artificially inoculated pathogenic E. coli, Salmonella and L. monocytogenes. HPP effectively inactivated bacterial concentration by 5 log CFU/ml. The most effective HPP conditions in terms of pathogen reduction were subsequently utilised to determine the effect of pressure on microbiological shelf life, particle size and colour of milk during refrigerated storage. Results were compared to pasteurised and raw milk. HPP (600 MPa for 3 min) also significantly reduced the total viable counts, Enterobacteriaceae, lactic acid bacteria and Pseudomonas spp. in milk thus prolonging the microbiological shelf life of milk by 1 week compared to pasteurised milk. Particle size distribution curves of raw, pasteurised and HPP milk, showed that raw and HPP milk had more similar casein and fat particle sizes compared to pasteurised milk. The results of this study show the possibility of using HPP to eliminate pathogens present in milk while maintaining key quality characteristics similar to those of raw milk.

Key quality characteristics selection for imbalanced production data using a two-phase bi-objective feature selection method

The selection of key quality characteristics (KQCs) that are significantly associated with product quality is essential for improving product quality. Production lines generally yield a larger number of regular products than do premium products, which creates an imbalance in production datasets and complicates KQC selection. In this study, a KQC selection method with an excellent ability to predict product quality is proposed based on a two-phase bi-objective feature selection method. The KQC selection model is established as a bi-objective problem of maximizing feature (i.e., quality characteristic) importance and minimizing percentage of selected features, and the geometric mean (G-mean) is selected as the feature importance metric for imbalanced data. To solve this model, a two-phase multi-objective optimization method is proposed; this method yields a set of candidate solutions (KQC sets) using an improved direct multi-search (DMS) strategy and uses the ideal point method (IPM) to select the final KQC sets from the candidate solutions. The experimental results indicate that the proposed method is effective for selecting KQCs for imbalanced production data.

Massive phenotyping of multiple cranberry populations reveals novel QTLs for fruit anthocyanin content and other important chemical traits.

Because of its known phytochemical activity and benefits for human health, American cranberry (Vaccinium macrocarpon L.) production and commercialization around the world has gained importance in recent years. Flavonoid compounds as well as the balance of sugars and acids are key quality characteristics of fresh and processed cranberry products. In this study, we identified novel QTL that influence total anthocyanin content (TAcy), titratable acidity (TA), proanthocyanidin content (PAC), Brix, and mean fruit weight (MFW) in cranberry fruits. Using repeated measurements over the fruit ripening period, different QTLs were identified at specific time points that coincide with known chemical changes during fruit development and maturation. Some genetic regions appear to be regulating more than one trait. In addition, we demonstrate the utility of digital imaging as a reliable, inexpensive and high-throughput strategy for the quantification of anthocyanin content in cranberry fruits. Using this imaging approach, we identified a set of QTLs across three different breeding populations which collocated with anthocyanin QTL identified using wet-lab approaches. We demonstrate the use of a high-throughput, reliable and highly accessible imaging strategy for predicting anthocyanin content based on cranberry fruit color, which could have a large impact for both industry and cranberry research.

The Effects of Teacher Training on Teachers’ Family-Engagement Practices, Attitudes, and Knowledge: A Meta-analysis

ABSTRACTWhen families are engaged in their education, children’s academic, behavioral, and social-emotional development is indirectly supported. Many teacher-training programs (TTPs) focused on preparing teachers to communicate and work with families have been developed, although inconsistencies regarding their effectiveness exist. The current meta-analysis of 39 studies systematically analyzed the effects of TTPs on teachers’ family-engagement practices, attitudes, and knowledge. TTPs included preservice university courses, teacher in-service, and professional development programs. Studies were coded for key sample, setting, and quality characteristics. Analyses revealed TTPs had a significant positive effect on all teacher family-engagement outcomes. Key intervention components were also determined (e.g., communication strategies, collaborative planning, and problem solving) and can be used to inform the development of future TTPs. Although results are promising, future TTPs should aim to improve methodological rigor and study quality.

Effect of Molecular Weight of Polymers on the Properties of Delicate Facial Foams

AbstractBody wash cosmetics are among the most popular and numerous groups of cosmetic products. In chemical terms, they are solutions of surface active agents with the addition of multiple substances such as preservatives, moisturizing agents, fragrances or viscosity modifiers, the aim of which is to improve specific product properties. The present study evaluated the effect of the molecular weight of polyvinylpyrrolidone (PVP) on the properties of face washing products in the form of foam produced with foaming dispensers. A special focus was on key product quality characteristics including foaming properties and skin irritation potential. An addition of PVP to the formulation was found to contribute to an improvement in product foaming properties and a decrease in skin irritation potential. In addition, the studied properties of samples were shown to improve in proportion to the increasing molecular weight of the polymer.

Evaluation of service quality in facebook-based group-buying

Abstract In recent years, community platforms have developed into community shopping, and have gradually become an interesting online shopping consumption model. Facebook is Taiwan's most important community platform. Internet shopping is not its main function though, but still Facebook has managed to find a way into the group-buying business. At this stage, in its logistics, the financial flows and information flows are not perfect. This study integrates a model of e-commerce information with an electronic service quality scale, and uses the Kano quality model to assess the key service quality characteristics of community buying. We found that there are six attractive qualities, the most important of which is product recommendation. The key quality elements for attracting customers are price and recommendation features, and that the group that is most attracted are 41- to 50-year-old female home-makers. The results of this research provide people who participating in group-buying on Facebook with useful information on the process, as well as insights on managerial planning for the business model.

Research on Quality Control of Digital Production Lines in Aviation Enterprises

Focusing on the requirements of efficient quality control of digital production lines in aviation enterprises, the framework quality control system of digital production lines were studied in this paper. First, the quality date categories of digital production lines were sorted out, a multi-source quality data acquisition scheme was proposed,. Second, the importance of key quality characteristics in quality control was discussed as well as a solution to find key quality features was established. Again, a multi-channel statistical quality control framework was constructed and a detailed implementation process was proposed. Finally, a digital production line quality control prototype system was designed and developed and validated in an aviation manufacturing enterprise.

Application of DMAIC and SPC to Improve Operational Performance of Manufacturing Industry: A Case Study

Statistical process control (SPC) is an excellent quality assurance tool to improve the quality of manufacture and end-customer satisfaction. It uses process monitoring charts to record the key quality characteristics of the component/part in manufacture. This research paper elaborates on one such key quality characteristics of the manufacturing of a spring support in the Tissue Dissector Device. This paper presents a creative solution through case study approach for improving the issue of rejection rate in the spring support in a medical device manufacturing industry by using SPC and define-measure-analyze-improve-control (DMAIC) approach which provide breakthrough quality improvements in short period of time.

Pairwise Critical Point Detection Using Torque Signals in Threaded Pipe Connection Processes

The quality of threaded pipe connections is one of the key quality characteristics of drill pipes, risers, and pipelines. This quality characteristic is evaluated mainly by a pair of critical points, which are corresponding to the mechanical deformations formed in the pipe connection process. However, these points are difficult to detect because of nonlinear patterns generated by latent process factors in torque signals, which conceal the true critical points. To address this problem, we propose a novel three-phase state-space model that incorporates physical interpretations of connection process to detect pairwise critical points. We also develop a two-stage recursive particle filter to estimate the locations of the underlying critical points. Results of a real threaded pipe connection case show that the detection performance of the proposed method is more powerful than that of other existing methods.

A new quality appearance evaluation technique for automotive bodies including effect of flexible parts tolerances

ABSTRACTPart tolerances have a crucial effect on the quality of products. In vehicle design, tolerance analysis is of central importance in quality appearance evaluation of automotive bodies and significantly taken into consideration by manufacturers in recent decades. This paper evaluates the surface quality of a car’s roof as one of the key quality characteristics in vehicle design. Compared to previous research in the area of quality appearance evaluation of automotive bodies, which are based on the assumption of part rigidity, the current research proposes to include part flexibilities in the analysis. The results of this study shows that input tolerances have a considerable effect on the surface quality of the final assembled product.

Overview of Key Quality Characteristics Identification of Complex Electromechanical Products

Overview of Key Quality Characteristics Identification of Complex Electromechanical Products

Usability: Key characteristic of software quality

The paper emphasizes the importance of software usability as a key quality characteristic of software during its use. At the beginning of the paper, a retrospective of formal definitions of usability is given in order to show the evolution of views on usability for more than three decades. To ensure the required quality in use, it is necessary to measure and evaluate many characteristics that affect the usability of software. The paper gives a brief chronology of attempts to identify different dimensions of usability based on its definitions. Since it is not easy to determine the characteristics that contribute most to the quality in use, two methods are applied in identifying the key attributes that affect usability, and they are to be given special consideration when building a model of usability.

A model study of the effects of river discharges and winds on hypoxia in summer in the Pearl River Estuary

The deterioration of dissolved oxygen conditions in the Pearl River Estuary (PRE) in summer has recently attracted considerable-scientific and political-attention. This paper documents the development, calibration, and verification of a coupled three-dimensional hydrodynamic and water quality model for the PRE. A comparison of the model's performance against field observations indicated that the model is capable of reproducing key hydrodynamic and water quality characteristics of the estuary within an acceptable range of accuracy. Furthermore, a scenario analysis showed that the extent of the hypoxic zone responds differently to changes in the river discharge at different inlets. Moreover, the hypoxic zone also changes in response to variations in the southwest wind in summer; specifically, a larger hypoxic zone develops as southwest winds blow in a more southward direction. However, the hypoxic conditions are much more sensitive to changes in the wind speed than changes in the wind direction.

Bi-objective variable selection for key quality characteristics selection based on a modified NSGA-II and the ideal point method

A product, or even a part, may contain hundreds of quality characteristics (QCs), but not all of them are key characteristics that determine product quality. Selecting possible key quality characteristics (KQCs), while eliminating redundant or noisy QCs, is a necessary step before implementing quality control or improvement tools. In this paper, we propose a two-phase variable selection algorithm based on a modified non-dominated sorting genetic algorithm II (NSGA-II), a multi-objective evolutionary algorithm, and the ideal point method (IPM) for KQC selection. In modified NSGA-II, we use a modified fast non-dominated sorting approach to increase the diversity of population in the evolutionary process. The uniqueness of the algorithm is that IPM can select KQC sets with few QCs from the candidate QC subsets found by the modified NSGA-II. Experimental results show that the proposed algorithm outperforms benchmarked KQC selection algorithms in terms of classification accuracy rates and number of noisy or redundant QCs.

Using modified IPA to define quality improvement strategies

Purpose – The purpose of this paper is to propose a modified Importance-Performance Analysis (IPA) model and calculates the performance of quality characteristic for the purpose of defining quality improvement strategy. Design/methodology/approach – This study developed modified IPA by introducing the Mahalanobis Distance and multiple regression analysis to evaluate the performance gap and implicit importance of quality characteristics. This paper used a large air-conditioning manufacturer in Taiwan as the case analysis and study targets. It discussed and validated the modified IPA analytical results by studying case history and market analysis. Findings – Through the case study, the quality characteristics of air-conditioning product and service needed to be improved immediately are Green product (Q3) and Repair service (Q10), and the Price (Q11) and Serviceability (Q2) could be kept or enhanced to win the market competitive advantages. Originality/value – This study developed a modified IPA to help organization identifying key quality characteristics of product and service, and choosing its improvement strategies to win the market competitive advantages effectively.

Key Quality Characteristics Identification Method for Mechanical Product

All quality characteristics(QCs) need to be constantly tested in the process of mechanical parts machining. The efficiency is low and the cost is high. Therefore, the key quality characteristics(KQCs) identification is helpful for narrowing the scope of inspection and improving the detection efficiency. Aiming at this problem, this paper puts forward Mahalanobis-Taguchi System(MTS) method based on ReliefF algorithm. The main steps are as follows: (1)calculate the weigh of each characteristics by applying ReliefF algorithm, and then eliminate irrelevant quality characteristics (2)find out mechanical parts’ final KQCs by using the orthogonal table and Signal/Noise Ratio(SNR) of MTS. Finally, the paper introduces the application of this method by setting a mechanical shaft as an example. The example shows that the method can improve the efficiency of the identification of mechanical parts quality characteristics.

A robust-tolerance design model for destructive quality characteristics: a case study in cement industry

Although remarkable considerations has been devoted to tolerance design (TD) and robust design (RD) by researchers recently and many methodologies have been proposed for the TD and RD optimisation, less attention has been focused on the integration of tolerance design and robust design. In this research, we aim to develop a sequential robust-tolerance design method through best factor settings when several related quality characteristics should be evaluated using destructive tests. Due to the nature of the tests, we could not measure key product quality characteristics directly and this issue added a constraint to the optimisation problem. The developed model under the defined scenario above was evaluated in the cement industry. Results show that the proposed model simulates the operational conditions satisfactorily.