| 1. |
- Deleryd, Mats, et al.
(författare)
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Process capability plots—a quality improvement tool
- 1999
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Ingår i: Quality and Reliability Engineering International. - 0748-8017 .- 1099-1638. ; 15:3, s. 213-227
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Tidskriftsartikel (refereegranskat)abstract
- We introduce the concept of process capability plots, which are powerful tools to monitor and improve the capability of industrial processes. An advantage of using a process capability plot, compared with using a traditional process capability index alone, when deciding whether a process can be considered capable or not, is that we will instantly get information about the location and spread of the studied characteristic. When the process is non-capable, the plots are helpful when trying to understand if it is the variability, the deviation from target or both that need to be reduced to improve the capability. In this way the proposed graphical methods give a clear direction of quality improvement. We evaluate two different process capability plots, the (δ*, γ*)-plot and the confidence rectangle plot, from a theoretical as well as a practical point of view. When studying them from a theoretical point of view, among other things, a simulation study is conducted to investigate the ability of each of the two methods to identify that a process is capable when it actually is. The comparison from a practical point of view is made by discussing the advantages and disadvantages of the two methods in different practical situations. Based on the above-mentioned comparisons, the recommendation is that the practitioner should use the (δ*, γ*)-plot.
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| 2. |
- Sandvik Wiklund, Pia, et al.
(författare)
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Finding active factors from unreplicated fractional factorials utilizing the total time on test (TTT) technique
- 1999
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Ingår i: Quality and Reliability Engineering International. - 0748-8017 .- 1099-1638. ; 15:3, s. 191-203
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Tidskriftsartikel (refereegranskat)abstract
- Much research has been devoted to improving the process of identifying active factors from designed experiments. Generally, the proposed methods rely on an estimate of the experimental error. Here we present a method based on the TTT (total time on test) plot, where the scaled TTT transform enables an evaluation of the contrasts independently of the experimental error. The method can be separated into two parts. The first part consists of a transformed TTT plot for a visual evaluation of data. The second part is more formal and utilizes the cumulative TTT statistic for testing the significance of contrasts. A simulation study shows the power of the method compared with competing methods. Five data sets are used to show that the conclusions drawn are consistent with those obtained using other suggested methods.
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| 3. |
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| 4. |
- Albing, Malin
(författare)
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Process capability indices for Weibull distributions and upper specification limits
- 2009
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Ingår i: Quality and Reliability Engineering International. - : Wiley. - 0748-8017 .- 1099-1638. ; 25:3, s. 317-334
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Tidskriftsartikel (refereegranskat)abstract
- We consider a previously proposed class of capability indices that are useful when the quality characteristic of interest has a skewed, zero-bound distribution with a long tail towards large values and there is an upper specification with a pre-specified target value, T = 0. We investigate this class of process capability indices when the underlying distribution is a Weibull distribution and focus on the situation when the Weibull distribution is highly skewed. We propose an estimator of the index in the studied class, based on the maximum likelihood estimators of the parameters in the Weibull distribution, and derive the asymptotic distribution for this estimator. Furthermore, we suggest a decision rule based on the estimated index and its asymptotic distribution, and presents a power comparison between the proposed estimator and a previously studied estimator. A simulation study is also performed to investigate the true significance level when the sample size is small or moderate. An example from a Swedish industry is presented.
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| 5. |
- Allahkarami, Zeynab, et al.
(författare)
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Mixed-effects model for reliability assessment of dump trucks in heterogeneous operating environment: A case study
- 2022
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Ingår i: Quality and Reliability Engineering International. - : John Wiley & Sons. - 0748-8017 .- 1099-1638. ; 38:5, s. 2881-2898
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Tidskriftsartikel (refereegranskat)abstract
- Reliability of mining equipment is influenced by different operational and environmental risk factors. However, in practice, including all relevant factors in reliability analysis is not possible. Ignoring the risk factors leads to unobserved heterogeneity and biased estimation of reliability characteristics. This research proposes a semi-parametric mixed-effects model to assess the simultaneous effects of observed and unobserved risk factors on reliability. Furthermore, the model can be used for investigating inter-cluster dependency and variability. To illustrate the model, a comprehensive case study is presented using data from three mines in Iran. The results show that the model can address the effect of unobserved risk factors. Moreover, it is found that the hazard of dump trucks is significantly associated with operator skill, season and the elevation difference between dumping and loading points.
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| 6. |
- Andersen, Emil B., et al.
(författare)
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An easy to use GUI for simulating big data using Tennessee Eastman process
- 2022
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Ingår i: Quality and Reliability Engineering International. - : John Wiley & Sons. - 0748-8017 .- 1099-1638. ; 38:1, s. 264-282
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Tidskriftsartikel (refereegranskat)abstract
- Data-driven process monitoring and control techniques and their application to industrial chemical processes are gaining popularity due to the current focus on Industry 4.0, digitalization and the Internet of Things. However, for the development of such techniques, there are significant barriers that must be overcome in obtaining sufficiently large and reliable datasets. As a result, the use of real plant and process data in developing and testing data-driven process monitoring and control tools can be difficult without investing significant efforts in acquiring, treating, and interpreting the data. Therefore, researchers need a tool that effortlessly generates large amounts of realistic and reliable process data without the requirement for additional data treatment or interpretation. In this work, we propose a data generation platform based on the Tennessee Eastman Process simulation benchmark. A graphical user interface (GUI) developed in MATLAB Simulink is presented that enables users to generate massive amounts of data for testing applicability of big data concepts in the realm of process control for continuous time-dependent processes. An R-Shiny app that interacts with the data generation tool is also presented for illustration purposes. The app can visualize the results generated by the Tennessee Eastman Process and can carry out a standard fault detection and diagnosis studies based on PCA. The data generator GUI is available free of charge for research purposes at https://github.com/dtuprodana/TEP.
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| 7. |
- Bergquist, Bjarne, et al.
(författare)
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Data Analysis for Condition-Based Railway Infrastructure Maintenance
- 2015
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Ingår i: Quality and Reliability Engineering International. - : Wiley. - 0748-8017 .- 1099-1638. ; 31:5, s. 773-781
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Tidskriftsartikel (refereegranskat)abstract
- Condition assessment is crucial to optimize condition-based maintenance actions of assets such as railway infrastructure, where a faulty state might have severe consequences. Hence, railways are regularly inspected to detect failure events and prevent the inspected item (e.g. rail) to reach a faulty state with potentially safety critical consequences (e.g. derailment). However, the preventive measures (e.g. condition-based maintenance) initiated by the inspection results may cause traffic disturbances, especially if the expected time to a faulty state is short. The alarm limits are traditionally safety related and often based on geometrical properties of the inspected item. Maintenance limits would reduce the level of emergency, producing earlier alarms and increasing possibilities of planned preventive rather than acute maintenance. However, selecting these earlier maintenance limits in a systematic way while balancing the risk of undetected safety-critical faults and false alarms is challenging. Here, we propose a statistically based approach using condition data of linear railway infrastructure assets. The data were obtained from regular inspections done by a railway track measurement wagon. The condition data were analysed by a control chart approach to evaluate the possibility for earlier detection of derailment hazardous faults using both temporal and spatial information. The study indicates that that the proposed approach could be used for condition assessment of tracks. Control charts led to earlier fault warnings compared to the traditional approach, facilitating planned condition-based maintenance actions and thereby a reduction of track downtime
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| 8. |
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| 9. |
- Cacciarelli, Davide, et al.
(författare)
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Robust online active learning
- 2024
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Ingår i: Quality and Reliability Engineering International. - : John Wiley & Sons. - 0748-8017 .- 1099-1638. ; 40:1, s. 277-296
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Tidskriftsartikel (refereegranskat)abstract
- In many industrial applications, obtaining labeled observations is not straightforward as it often requires the intervention of human experts or the use of expensive testing equipment. In these circumstances, active learning can be highly beneficial in suggesting the most informative data points to be used when fitting a model. Reducing the number of observations needed for model development alleviates both the computational burden required for training and the operational expenses related to labeling. Online active learning, in particular, is useful in high-volume production processes where the decision about the acquisition of the label for a data point needs to be taken within an extremely short time frame. However, despite the recent efforts to develop online active learning strategies, the behavior of these methods in the presence of outliers has not been thoroughly examined. In this work, we investigate the performance of online active linear regression in contaminated data streams. Our study shows that the currently available query strategies are prone to sample outliers, whose inclusion in the training set eventually degrades the predictive performance of the models. To address this issue, we propose a solution that bounds the search area of a conditional D-optimal algorithm and uses a robust estimator. Our approach strikes a balance between exploring unseen regions of the input space and protecting against outliers. Through numerical simulations, we show that the proposed method is effective in improving the performance of online active learning in the presence of outliers, thus expanding the potential applications of this powerful tool.
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| 10. |
- Capaci, Francesca, et al.
(författare)
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Exploring the Use of Design of Experiments in Industrial Processes Operating Under Closed-Loop Control
- 2017
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Ingår i: Quality and Reliability Engineering International. - : John Wiley & Sons. - 0748-8017 .- 1099-1638. ; 33:7, s. 1601-1614
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Tidskriftsartikel (refereegranskat)abstract
- Industrial manufacturing processes often operate under closed-loop control, where automation aims to keep important process variables at their set-points. In process industries such as pulp, paper, chemical and steel plants, it is often hard to find production processes operating in open loop. Instead, closed-loop control systems will actively attempt to minimize the impact of process disturbances. However, we argue that an implicit assumption in most experimental investigations is that the studied system is open loop, allowing the experimental factors to freely affect the important system responses. This scenario is typically not found in process industries. The purpose of this article is therefore to explore issues of experimental design and analysis in processes operating under closed-loop control and to illustrate how Design of Experiments can help in improving and optimizing such processes. The Tennessee Eastman challenge process simulator is used as a test-bed to highlight two experimental scenarios. The first scenario explores the impact of experimental factors that may be considered as disturbances in the closed-loop system. The second scenario exemplifies a screening design using the set-points of controllers as experimental factors. We provide examples of how to analyze the two scenarios
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