Search Results (42)

Although linear overproduction and overconsumption have benefited businesses, they have created an unsustainable society. Converting wood waste into construction material can support the transition to a circular economy. The mechanical properties of beams constructed from wood waste were measured. Squares with 50, 60, and 70 mm side lengths were glued to create beams, to which the three-point test method was applied parallel to the fibres. The stiffness and moduli of elasticity and rupture were analysed with standard industrial statistical techniques. Specifically, a two-stage analysis was performed using the normal distribution and Shewhart control charts. Changes of 100 mm in width and height and 200 mm in length caused a change of 200–400 N/mm² in elasticity and 500–1300 MNmm² in stiffness. Modulus of rupture values were relatively comparable, as they were determined by the properties of oak wood, from which the beams were made. The observed differences in the tested mechanical parameters will be useful in the optimisation of furniture construction, with our research suggesting that it is possible to predict mechanical properties from the dimensions of the waste-wood pieces. Ultimately, this should help to design sustainable furniture that is aesthetic, functional, and safe. Full article

To address the issue that existing GNSS spoofing detection methods are not suitable for intermittent minor spoofing detection and spoofing duration identification, this paper theoretically analyzes the shortcomings of existing detection algorithms in terms of minor spoofing termination detection performance, and proposes comprehensively utilizing two types of control charts and robust estimation to detect the spoofing end moment, laying a foundation for spoofing duration identification and intermittent minor spoofing detection. The Shewhart control chart-based spoofing detection algorithm (M1) is proposed to achieve rapid spoofing termination detection, serving as one of the baseline algorithms for the joint algorithm. The strengths and weaknesses of the two baseline algorithms (M1 and existing EWMA control chart and robust estimation-based detection algorithm (M2)) in minor spoofing detection are analyzed. Under the robust estimation mechanism, a joint spoofing detection metric that can effectively indicate spoofing termination is constructed by combining their respective spoofing test statistics; then, anomaly detection on the joint detection metric is performed based on sample quantiles to identify the spoofing end moment. The experimental results under various typical abrupt spoofing and slowly varying spoofing scenarios demonstrate that the proposed joint spoofing detection algorithm based on dual control charts and robust estimation satisfies the spoofing alert time requirements specified by the International Civil Aviation Organization (ICAO) for the cruise phase. Compared with existing detection algorithms, the joint algorithm maintains excellent spoofing initiation detection performance while significantly improving both the speed and accuracy of spoofing termination detection. This effectively integrates the advantages of the two baseline algorithms and compensates for their individual limitations when operating independently. Upon timely and effective detection of the start and end moments of minor spoofing, it becomes possible to achieve spoofing duration identification and intermittent minor spoofing detection. Full article

In manufacturing and service industries, monitoring processes with correlated input variables and inverse Gaussian (IG)-distributed quality characteristics is challenging due to the limitations of maximum likelihood estimator (MLE)-based control charts. When input variables exhibit multicollinearity, traditional MLE-based inverse Gaussian regression model (IGRM) control charts become unreliable. This study introduces novel Shewhart control charts using Pearson and deviance residuals based on the inverse Gaussian ridge regression (IGRR) model to address this issue. The proposed IGRR-based charts effectively handle multicollinearity, offering a robust alternative for process monitoring. Their performance is evaluated through Monte Carlo simulations using average run length (ARL) as the main criteria, demonstrating that Pearson residual-based IGRR charts outperform deviance residual-based charts and MLE-based methods, particularly under high multicollinearity. A real-world application to a Pakistan air quality dataset confirms their superior sensitivity in detecting pollution spikes, enabling timely environmental negotiations. These findings establish Pearson residual-based IGRR control charts as a practical and reliable tool for monitoring complex processes with correlated variables. Full article

Retrial queues are used extensively to model many practical problems in service systems, call centers, data centers, and computer network systems. The average waiting time is the main observable characteristic of the retrial queues. Long queues may cause negative impacts such as waste of manpower and unnecessary crowding leading to suffocation, and can even cause trouble for customers and institutions. Applying control chart technology can help managers analyze customers’ waiting times to improve the effective performance of service and attention. This paper pioneers the developing and detailed study of a waiting time control chart for a retrial queue with general service times. Two waiting time control charts, the Shewhart control chart, and a control chart using the weighted variance method are constructed in this paper. We present three cases for the Shewhart control chart in which the service time obeys special distributions, such as exponential, Erlang, and hyper-exponential distributions. The case of an exponentially distributed service time is also presented for the control chart using the weighted variance method. Based on the numerical simulations conducted herein, managers can better monitor and analyze the customers’ waiting times for their service systems and take preventive measures. Full article

The need, or even the obligation, to take care of the natural environment compels a search for new technological solutions, or for known solutions to be adapted to new applications. The maxim is ‘don’t harm, but improve the world for future generations’. In the wood industry in particular, given that it is based on a natural raw material, we must look for ecological solutions. Trees grow, but the demand for wood exceeds the volume of tree growth. In industrial manufacturing, one of the ways to make full use of wood is through chipless processing, which occurs during rotary cutting (peeling). In addition, wood is a natural material, each fragment of which has a range of properties. In addition, wood defects in quality manipulation generate a lot of waste. The aim of this study was to analyse the quality effect of the tested layered composites for flooring materials on production application. The practical purpose was to exchange actual sawing-based production for chipless production. The composite base layers were made of pine wood (Pinus L.) veneers with differing quality classes. The samples were subjected to three-point bending tests to calculate the moduli of elasticity and stiffness, which are the most important parameters. Because both analysed parameters describe product quality, the analyses were based on the creation of Shewhart control charts for each parameter. In theory, these control charts are tools for analysing whether the production process is stable and yields predictable results. To have full control over the process, five elements have to be applied: central line (target), two types of control lines (upper and lower) and two types of specification lines (upper and lower). New types of layered composites for flooring may be applied to production once verified using Shewhart control charts. It turns out that it is possible to produce the base layer of the flooring materials using the rotary cutting (peeling) method without having to analyse the quality of the raw material. This is a way to significantly increase the efficiency of production in every element of manufacturing. Full article

The digitalization of the high-tech economy is complicated due to several issues. One can mention non-synchrony and imbalance in the development of industrial enterprises and their integrations; changes in the elements and relations between enterprises and the external environment; as well as contradictions between the actors. Therefore, a new institutional system for industrial integrations needs to be formed. This article proposes a concept and scenario of the institutional change needed to bolster industrial integrations in the digital economy. The structural logic and algorithm of the process provides for the gradual progress through seven phases of institutional transformation. The authors have developed an institutional change management platform for strategic transformation, the core of which is a decision-making system. The platform supports the management of digital and material business processes of industrial integrations. The conceptual approach is based on a comparison of the life cycles of enterprises and their markets. The article proposes a methodology for assessing the readiness of industrial integrations to implement institutional change strategies using modified Shewhart control charts. The methodology is based on a two-criterion approach to the analysis of finances, production reserves, human resources, organizational structures, management technologies, corporate institutions, and a personnel motivation system. This approach allows determining the level of compliance of the resources available with the requirements of the transformation strategy implementation plan. The methodology has been tested at 14 enterprises functioning as industrial integration actors. According to the dynamics of the level of readiness to implement the transformation strategy, enterprises within the framework of industrial integrations are divided into three groups: enterprises with consistently high, medium, and low levels of readiness to implement the strategy. Full article

In this article, we establish new distribution-free Shewhart-type control charts based on rank sum statistics with signaling multiple scans-type rules. More precisely, two Wilcoxon-type chart statistics are considered in order to formulate the decision rule of the proposed monitoring scheme. In order to enhance the performance of the new nonparametric control charts, multiple scans-type rules are activated, which make the proposed chart more sensitive in detecting possible shifts of the underlying distribution. The appraisal of the proposed monitoring scheme is accomplished with the aid of the corresponding run length distribution under both in- and out-of-control cases. Thereof, exact formulae for the variance of the run length distribution and the average run length (ARL) of the proposed monitoring schemes are derived. A numerical investigation is carried out and depicts that the proposed schemes acquire better performance towards their competitors. Full article

This study examines the design and long-term implementation of a feedforward and feedback (FF–FB) mechanism in a control system for cement sulfates applied to all types of cement produced in two mills at a production facility. We compared the results with those of a previous controller (SC) that operated in the same unit. The Shewhart charts of the annual SO₃ mean values and the nonparametric Mann–Whitney test demonstrate that, for the FF–FB controller, the mean values more effectively approach the SO₃ target than the older controller in two out of the three cement types. The s-charts for the annual standard deviation of all cement types and mills indicate that the ratio of the central lines of FF–FB to SC ranges from 0.39 to 0.59, representing a significant improvement. The application of the error propagation technique validates and explains these improvements. The effectiveness of the installed system is due to two main factors. The feedforward (FF) component tracks the set point of SO₃ when the mill begins grinding a different type of cement, while the feedback (FB) component effectively attenuates the fluctuations in the sulfates of the raw materials. Full article

In this work, a control chart with multiple runs rules is proposed and studied in the case of monitoring inflated processes. Usually, Shewhart-type control charts for attributes do not have a lower control limit, especially when the in-control process mean level is very low, such as in the case of processes with a low number of defects per inspected unit. Therefore, it is not possible to detect a decrease in the process mean level. A common solution to this problem is to apply a runs rule on the lower side of the chart. Motivated by this approach, we suggest a Shewhart-type chart, supplemented with two runs rules; one is used for detecting decreases in process mean level, and the other is used for improving the chart’s sensitivity in the detection of small and moderate increasing shifts in the process mean level. Using the Markov chain method, we examine the performance of various schemes in terms of the average run length and the expected average run length. Two illustrative examples for the use of the proposed schemes in practice are also discussed. The numerical results show that the considered schemes can detect efficiently various shifts in process parameters in either direction. Full article

Assessment of process stability is a key to ensuring the high quality of any product, service, activity, etc. The main tool for doing this is a Shewhart control chart. However, it becomes difficult to analyze hundreds or thousands of control charts at a time for some up-to-date complex processes. In order to solve this problem, various indicators of process stability have been recently proposed with the Stability Index (SI) being the latest one, and, in many opinions, the best one. We have thoroughly analyzed different suggestions and found many of them ambiguous and sometimes even harmful to practitioners. Some examples of possible problems with the SI are provided below. It is argued that abnormal values of the SI can be caused not only by process instability, but by non-homogeneity, non-randomness, nonnormality, and autocorrelation as well. It is proved that the SI can be helpful for practitioners as an index to attract primary attention to the process. A proposal to rename the SI and widen significantly its application is given. Finally, some ways that practitioners could use this index more effectively are discussed. Full article

The control chart is a fundamental tool in statistical process control (SPC), widely employed in manufacturing and construction industries for process monitoring with the primary objective of maintaining quality standards and improving operational efficiency. Control charts play a crucial role in identifying special cause variations and guiding the process back to statistical control. While Shewhart control charts excel at detecting significant shifts, EWMA and CUSUM charts are better suited for detecting smaller to moderate shifts. However, the effectiveness of all these control charts is compromised when the underlying distribution deviates from normality. In response to this challenge, this study introduces a robust mixed EWMA-CUSUM control chart tailored for monitoring processes characterized via symmetric but non-normal distributions. The key innovation of the proposed approach lies in the integration of a robust estimator, based on order statistics, that leverages the generalized least square (GLS) technique developed by Lloyd. This integration enhances the chart’s robustness and minimizes estimator variance, even in the presence of non-normality. To demonstrate the effectiveness of the proposed control chart, a comprehensive comparison is conducted with several well-known control charts. Results of the study clearly show that the proposed chart exhibits superior sensitivity to small and moderate shifts in process parameters when compared to its predecessors. Through a compelling illustrative example, a real-life application of the enhanced performance of the proposed control chart is provided in comparison to existing alternatives. Full article

Exponentially weighted moving average (EWMA) and Shewhart control charts are commonly utilized to detect the small to moderate and large shifts in the process mean, respectively. This article introduces a novel Bayesian AEWMA control chart that employs various loss functions (LFs), including square error loss function (SELF) and LINEX loss function (LLF). The control chart incorporates an informative prior for posterior and posterior predictive distributions. Additionally, the control chart utilizes various paired ranked set sampling (PRSS) schemes to improve its accuracy and effectiveness. The average run length (ARL) and standard deviation of run length (SDRL) are used to evaluate the performance of the suggested control chart. Monte Carlo simulations are conducted to compare the performance of the proposed approach to other control charts. The results show that the proposed method outperforms in identifying out-of-control signals, particularly under PRSS schemes compared to simple random sampling (SRS). The proposed CCs effectiveness was validated using a real-life semiconductor manufacturing application, utilizing different PRSS schemes. The performance of the Bayesian AEWMA CC was evaluated, demonstrating its superiority in detecting out-of-control signs compared to existing CCs. This study introduces an innovative method incorporating various LFs and PRSS schemes, providing an enhanced and efficient approach for identifying shifts in the process mean. Full article

Process capability index (PCI) is a convenient and useful tool of process quality evaluation that allows a company to have a complete picture of its manufacturing process in order to prevent defective products while ensuring the product quality is at the required level. The aim of this study was to develop a control chart for process incapability index $C_{pp}$, which differentiates between information related to accuracy and precision. Index $C_{ia}$ measures process inaccuracy as the degree to which the mean departs from the target value, while index $C_{ip}$ measures imprecision in terms of process variation. The most important advantage of using these control charts of $C_{pp}$, $C_{ia}$, and $C_{ip}$ is that practitioners can monitor and evaluate both the quality of the process and the differences in process capability. The $C_{ia}$ and $C_{ip}$ charts were instead of Shewhart’s $\overline{X}$ and $S$ chart since the process target values and tolerances can be incorporated in the charts for evaluation as a whole, which makes the charts capable of monitoring process stability and quality simultaneously. The proposed $C_{pp}$, $C_{ia}$, and $C_{ip}$ control charts enable practitioners to monitor and evaluate process quality as well as differences in process capability. The control charts are defined using probability limits, and operating characteristic (OC) curves used to detect shifts in process quality. The method proposed in this study can easily and accurately determine the process quality capability and a case is used to illustrate the application of control charts of $C_{pp}$, $C_{ia}$, and $C_{ip}$. Full article

Technical and technological developments in recent decades have stimulated the rapid development of methods and tools in the field of statistical process quality control, which also includes control charts. The principle of control charts defined by Dr. W. Shewhart has been known for more than 100 years. Since then, they have been used in many industries to monitor and control processes. This paper aims to assess the possibilities of use and the selection of the most suitable type of control chart for monitoring the quality of a process depending on its nature. This tool should help operators in monitoring coking time, which is one of the important control variables affecting the quality of coke production. The autoregressive nature of the variable being monitored was considered when selecting a suitable control chart from the group of options considered. In addition to the three traditional types of control charts (Shewhart’s, CUSUM, and EWMA), which were applied to the residuals of individual values of different types of ARIMA models, various statistical tests, and plots, a dynamic EWMA control chart was also used. Its advantage over traditional control charts applied to residuals is that it works with directly measured coking time data. This chart is intended to serve as a method to monitor the process. Its role is only to alert the process operator to the occurrence of problems with the length of the coking time. Full article

Protein misfolding and aggregation are pathological hallmarks of various neurodegenerative diseases. In Alzheimer’s disease (AD), soluble and toxic amyloid-β (Aβ) oligomers are biomarker candidates for diagnostics and drug development. However, accurate quantification of Aβ oligomers in bodily fluids is challenging because extreme sensitivity and specificity are required. We previously introduced surface-based fluorescence intensity distribution analysis (sFIDA) with single-particle sensitivity. In this report, a preparation protocol for a synthetic Aβ oligomer sample was developed. This sample was used for internal quality control (IQC) to improve standardization, quality assurance, and routine application of oligomer-based diagnostic methods. We established an aggregation protocol for Aβ1–42, characterized the oligomers by atomic force microscopy (AFM), and assessed their application in sFIDA. Globular-shaped oligomers with a median size of 2.67 nm were detected by AFM, and sFIDA analysis of the Aβ1–42 oligomers yielded a femtomolar detection limit with high assay selectivity and dilution linearity over 5 log units. Lastly, we implemented a Shewhart chart for monitoring IQC performance over time, which is another important step toward quality assurance of oligomer-based diagnostic methods. Full article