Purpose: A new approach to production process monitoring in organization using control chart type X-R has been presented. Design/methodology/approach: The possibility of use of basic element of Statistical Process Control ( SPC method) is connected with continuous quality improvement of each production process in an enterprise. Interdependence of the quality research methods and production process’s requirements have been taken into account. Findings: At the present time the metallurgical enterprises should integrate quality management system and quality control with customer’s requirements, with defined both parameters of processes and quality methods. Such kind of strategy will enable to achieve success for these companies. Research limitations/implications: Control chart type X-R is very important quality tool. Its determined statistical measures are recorded properties of product obtained as a result of inspections taking randomly samples of products in the determined place of the process. Aim of control chart type X-R is observation and registration of the changeability of the characteristic of the researched element of the production process. Practical implications: The example of implementing control chart type X-R shows possibility of monitoring chosen parameters of production process according to an idea of defect prevention. Usage of this method allows for monitoring of production process, providing opportunities for cost reduction, and maintaining of production process stability. Originality/value: Application of basic element of Statistical Process Control in polish metallurgical companies have been presented. Purpose: A new approach to production process monitoring in organization using control chart type X-R has been presented. Design/methodology/approach: The possibility of use of basic element of Statistical Process Control ( SPC method) is connected with continuous quality improvement of each production process in an enterprise. Interdependence of the quality research methods and production process’s requirements have been taken into account. Findings: At the present time the metallurgical enterprises should integrate quality management system and quality control with customer’s requirements, with defined both parameters of processes and quality methods. Such kind of strategy will enable to achieve success for these companies. Research limitations/implications: Control chart type X-R is very important quality tool. Its determined statistical measures are recorded properties of product obtained as a result of inspections taking randomly samples of products in the determined place of the process. Aim of control chart type X-R is observation and registration of the changeability of the characteristic of the researched element of the production process. Practical implications: The example of implementing control chart type X-R shows possibility of monitoring chosen parameters of production process according to an idea of defect prevention. Usage of this method allows for monitoring of production process, providing opportunities for cost reduction, and maintaining of production process stability. Originality/value: Application of basic element of Statistical Process Control in polish metallurgical companies have been presented.
This article is a result of research carried out in foundry casting steel castings for the railway industry. The smelting process (smelting) in induction furnaces, in terms of the compatibility of the actual chemical elements in the metal with the composition laid down in the technological instructions, was included in the study program. In practice, the actual content of elements is determined by the static spectral analysis method and recorded in the documentation created by the traditional record. Entries are evaluated only in terms of compliance with technological instructions, which does not translate into improvement in the quality of the melt as a function of the duration of the production process. The introduction of time analysis in the melting range allows to take into account the variability of a number of factors affecting the actual (final) content of the elements and thus the quality of the cast. An example of time analysis presented in the article is the ability to use I / MR control cards for individual (single) observations composed of smelting processes and CUSUM cards that enable the detection of factor variability based on cumulative sums. Cards of this type can be helpful in achieving the quality of alloys in real time of the melting process.
3
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
Purpose: The paper presents the method to monitor the mean time between failures (MTBF) and detect any change in intensity parameter. Here, a control chart procedure is presented for process reliability monitoring. Control chart based on different distributions are also considered and were used in decision making. Results and discussions are presented based on the case study at different industries. Design/methodology/approach: The failure occurrence process can be modeled by different distributions like homogeneous Poisson process, Weibull model etc. In each case the aim is to monitor the mean time between failure (MTBF) and detect any change in intensity parameter. When the process can be described by a Poisson process the time between failures will be exponential and can be used for reliability monitoring. Findings: In this paper, a new procedure based on the monitoring of time to observe r failures is also proposed and it can be more appropriate for reliability monitoring. Practical implications: This procedure is useful and more sensitive when compared with the λ-chart although it will wait until r failures for a decision. These charts can be regarded as powerful tools for reliability monitoring. λr gives more accurate results than λ-chart. Originality/value: Adopting these measures to system of equipments can increase the reliability and availability of the system results in economic gain. A homogeneous Poisson process is usually used to model the failure
Karta kontrolna jest powszechnie stosowanym narzędziem statystycznej kontroli jakości. Spełnienie podstawowych jej założeń, gwarantuje bezbłędną ocenę poprawności monitorowanego procesu produkcyjnego. Naruszenia założeń klasycznych karty kontrolnych mogą powodować fałszywe sygnały, w przypadku procesu uregulowanego, bądź brak sygnału lub sygnał opóźniony w czasie, w przypadku procesu rozregulowanego. Celem niniejszej pracy jest zwrócenie uwagi na konieczność weryfikacji założeń stosowanej metody i skutki nieupoważnionego jej stosowania, w przypadku braku ich spełnienia. W niniejszej pracy, ponadto, przedstawia się metodę wyznaczania granic kontrolnych w oparciu o zmienną losową powstałą poprzez transformację logarytmiczną danych wyjściowych. Własności proponowanej metody zostały zweryfikowane w oparciu o rzeczywiste dane za pomocą symulacji komputerowych przeprowadzonych w programie R.
EN
The control chart is a commonly used tool of statistical quality control. The fulfillment of its basic assumptions, guarantees faultless estimation of correctness of monitored production process. Breach the assumptions of classical control charts can cause false signals, when the process really is in control, or lack of signal as well as a signal delayed in time when the process is out of control. The purpose of this paper is to pay attention to the need to verify the assumptions of the used method and the effects of its unauthorized use, in case of the absence of their fulfillment. Moreover in this paper, a method for determining the control limits based on a random variable that consists of a logarithmic transformation of the data, is presented. The features of the proposed method were testing based on real data by the computer simulations carried out in R.
5
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
The Box Cox transformation are given for construction of asymmetric quantiles and control limits for control charts. It is shown on simulated and real data that the transformation may significantly improve applicability of control charts.
Artykuł traktuje o metodach rozpoznawania statystycznej stabilności procesu z wykorzystaniem tzw. kart kontrolnych procesu. W pracy wskazano problemy związane z wykorzystaniem tradycyjnych kart kontrolnych bezpośrednio w procesie wytwarzania, na stanowisku roboczym. Zaprezentowano nowe, autorskie podejście do analizowania danych na kartach kontrolnych, oparte na traktowaniu tych danych jako liczbowego szeregu czasowego, tworzącego pewien obraz stanu procesu. Opisano propozycje metod klasyfikowania obrazów na karcie kontrolnej oraz krótką charakterystykę programu CCAUS (ang. Control Charts-Analysis Unnatural Symptoms), wspomagającego te metody. W publikacji zamieszczono także wyniki weryfikacji skuteczności opracowanych metod dla danych uzyskanych z dwóch operacji technologicznych: dogladzania i szlifowania.
EN
The paper takes up some problems connected with the analysis of the process stability with the use of process control charts. An approach of pattern recognition idea and two applications, called OTT and MW, supporting these approach are described. Also an CCAUS software (Control Charts-Analysis Unnatural Symptoms) aided the use these applications is presented. Verification of the worked out methods was performed on the base of data taken from two machining operations
The paper is devoted to soft methods in statistical quality control. A review of existing tools for dealing with vague data or fuzzy requirements is given. Some new procedures are also proposed.
10
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
Celem badań była ocena niezawodności i stabilności procesu oczyszczania ścieków z wykorzystaniem analizy niezawodności i statystycznej kontroli jakości. Ocena ta była przeprowadzona z wykorzystaniem tzw. analizy procesu i kart kontrolnych. Badana oczyszczalnia pracuje niestabilnie, czego przyczyną są okresowe duże ładunki zanieczyszczeń zawarte w ściekach surowych.
EN
Aim of this study was to evaluate the reliability and stability of the treatment process using reliability analysis and statistical quality control. This evaluation was performed using the process analysis and control charts. The study sewage treatment plant works unstable, which is caused by periodic high loads of pollutants in raw wastewater.
11
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
Statistical process control (SPC) is one ingredient for achieving quality improvement. SPC is a method of gathering and analysing data to solve practical quality problems. To SPC belongs among other a process monitoring to assess its stability by distinguishing special from common causes of variation. For this purpose technique control charts is applied. There are dozens of control chart types were the most often applied type is a classical Shewhart's control charts for variables and for attributes. In this work a possibility for application of regression control charts for median to control a process with a trend is presented.
PL
Jednym z instrumentów zarządzania jakością (TQM) jest statystyczne sterowanie procesem (SPC). Do zadań SPC należy przede wszystkim monitorowanie procesu w celu oceny jego stabilności. W tym zakresie wykorzystywana jest technika kart kontrolnych jako metoda on-line. Istnieje wiele rodzajów kart kontrolnych, z których najczęściej i najchętniej stosowane są karty kontrolne Shewharta. Dotyczy to zarówno cech mierzalnych, jak i oceny alternatywnej. W pracy przedstawiono możliwość wykorzystania karty kontrolnej regresji dla mediany do nadzorowania procesu wykazującego trend spowodowany zużywaniem się narzędzia
Environmental laboratory tests are one of the most frequently performed tests to evaluate materials used, among others, for the construction of rail vehicles. The requirements of the EN ISO/IEC 17025 standard for research laboratories, particularly when evaluating the compliance of materials with the specified requirements, impose on laboratories the need to consider the results of final measurements along with the uncertainties of these results. Due to the complexity of the physical and chemical processes occurring during environmental tests, determining the sources of uncertainty of the measurement result can be very complicated. The article presents one of the methods of estimating the complex uncertainty for environmental tests on the example of corrosion tests using the NORDTEST TR 537 concept of uncertainty estimation. The article presents an exemplary method of uncertainty estimation based on a set of empirical data obtained in an accredited Laboratory for Testing Materials and Structural Elements of the Railway Institute with the use of within-laboratory reproducibility and method bias. Examples of uncertainty estimation depending on the type of tested objects (metal details and paint coatings) and the method of their evaluation after corrosion tests (quantitative and qualitative methods) are presented. The article also briefly presents the possibilities of interpreting and processing the obtained data as part of the control carried out inside the laboratory on the basis of a simple statistical tool such as Shewhart control charts and the Ishikawa diagram for the method of determining corrosivity in salt chambers, identifying important factors influencing the measurement uncertainty and at the same time showing the complexity the entire research process.
13
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
W pracy zamodelowano dynamiczny proces neutralizacji pH w postaci sieci neuronowej, a także przeprowadzono diagnostykę, poprzez kontrolę parametrów sieci. Wartość pH oznacza kwasowość i zasadowość roztworów wodnych związków chemicznych. Do badań symulacyjnych został wykorzystany pakiet komputerowy Matlab. Poddano również analizie efektywność wykrywania zmian w procesie na podstawie wykrywania zmian w adaptacyjnym neuronowym modelu procesu. Diagnostyka procesu neutralizacji pH przeprowadzono z zastosowaniem kart kontrolnych Shewharta. W szczególności karty kontrolne umożliwiają wykrycie zmienności parametrów procesu.
EN
The aim of the work is modeling the dynamic process of pH neutralization in the form of neural network, and its diagnosis, through control of network parameters. Neural networks are one of the most rapidly growing areas of artificial intelligence. They have a good chance of success because of the ability to learn nonlinear relationships. They offer cost-effective approach to modeling of chemical processes. For the simulation tests were used Matlab. It should also be analyzed to detect changes in the efficiency of the process based on the detection of changes in adaptive neural model of the process. Diagnosis of pH neutralization process was carried out using Shewhart control charts, as well they are suitable for this type of per-specialties. In particular, control charts allow the detection of process variability caused by certain specific reasons.
W artykule przedstawiono możliwość zastosowania kart kontrolnych, jako łatwej i efektywnej metody dla oceny tendencji zmian gabarytów wyrobisk korytarzowych z wykorzystaniem pomiarów konwergencji. Jako przykład analizy wykorzystano wyniki pomiarów w wyrobisku z kopalni R.A.G Anthratzit Ibbenbűren znajdującego się na głębokości blisko 1200 m.
EN
The article presents possibility of using control charts as an easy and effective method for assessing the propagation of changes dimensions of roadways with measurements of convergence. As an example, the analysis used the results of measurements of the excavation RAG Anthratzit Ibbenbüren located at a depth of 1200 m.
Statistical methods belong to the basic quality tools. Among statistical instruments the statistical process control SPC takes particular place. One of the principal tasks of SPC is monitoring of a process by means of control charts. They are first of all Shewhart's control charts. The aim of investigations was to assess stability of technological process of hot-rolling of steel strip. There were available the results of thickness measurements madę with an X-ray thickness gauge as well as measurements of convexity and wedge shape made with a profile measurement gauge. The assessment of statistical process stability was performed by means of Shewarfs control charts technique. In case of thickness the estimation of capability indices Cp, Cpk and Pp, Ppk have been carried out, in addition.
PL
Metody statystyczne należą do podstawowych narzędzi jakości. Szczególne miejsce wśród tych metod zajmuje statystyczne sterowanie procesem (SPC). Jednym z podstawowych zadań SPC jest monitorowanie procesu za pomocą kart kontrolnych; są to przede wszystkim karty kontrolne Shewharta. Celem badań była ocena stabilności procesu walcowania na gorąco taśmy stalowej ze względu na następujące parametry: grubość, wypukłość, klinowatość. Pomiar grubości przeprowadzono za pomocą gruboś domierza rentgenowskiego, natomiast do pomiarów wypukłości i klinowatości użyto profilomierza. Ocenę statystycznej stabilności procesu przeprowadzono za pomocą techniki kart kontrolnych. W przypadku grubości wyznaczono również współczynniki zdolności procesu Cp, Cpk oraz Pp, Ppk.
W artykule omówiono narzędzia statystycznego sterowania procesem dla krótkich serii. Przedstawiono podstawowe problemy związane z krótkimi przebiegami produkcyjnymi i sposoby ich rozwiązania, a także zaprezentowano najczęściej stosowane karty kontrolne: kartę wartości nominalnej x-R, kartę krótkich serii x—R. Zastosowanie tych narzędzi zilustrowano przykładem z produkcji przemysłowej.
EN
The tools of statistical process control for short production runs were presented. Main problems connected with short runs and their solutions were shown as well as the most often used control charts: Nominal x —R Chart and Short Runjc—R. Application of tools mentioned above were illustrated on the base of an example from industry.
Jakość powietrza oddechowego odgrywa kluczowe znaczenie dla bezpieczeństwa nurków i obiektów hiperbarycznych. Paradoksalnie, zmiana przepisów dotyczących wymagań jakościowych dla czynników oddechowych, wymusiła konieczność weryfikacji bazy technicznej i laboratoryjnej wykorzystywanej do ich produkcji i kontroli. W artykule przedstawiono wyniki badań związanych z racjonalizacją procesu otrzymywania i dystrybucji powietrza oddechowego przeznaczonego na tlenowe warunki hiperbaryczne. Pracę przeprowadzono przy wykorzystaniu metody SixSigma.
EN
The quality of breathing air plays a key role in the safety of divers and hyperbaric facilities. Paradoxically, the change of regulations concerning quality requirements for breathing mixes has imposed the need for verification of the technical and laboratory bases used in their production and control. This article presents the results of research related to the rationalisation of the process of production and supply of breathing air for the purposes of hyperbaric oxygenation. The work was carried out using the SixSigma method.
19
Dostęp do pełnego tekstu na zewnętrznej witrynie WWW
for casting of brake discs. Some specific characteristics were presented that should be taken into consideration when statistical methods are used for technology improvement. The stability of the cast iron melting process was evaluated using data read out from the thermal analysis curve and true data, i.e. the results of spectrometric analysis of the chemical composition and measured values of the mechanical properties. The method for assessment of process stability was discussed on the example of carbon content and Brinell hardness. The examined parameters of the technological process of grey iron melting and casting are independent of each other (the results of carbon content determination in successive melts, the results of hardness measurements, etc.). Therefore, for analysis, the IX - MR type charts were chosen, where single measurements of the selected property (n=1) serve as a measure of location, while a measure of variability are the, so called, Moving Ranges (MR), which are an absolute value of the difference between the two successive measurements.
This study focuses on ISO evaluation of process capability in the production of hydraulic components according to ISO 9001: 2008 Quality Management Systems requirements. Statistical process control is analysed on the basis of normality and stability of the process, and c cutting process capability indices Cp and Cpk are calculated. The values obtained for indices are Cp = 3.29 and Cpk = 0.73. Therefore, it can be considered the process is capable.
PL
Przedstawione badania dotyczą analizy zdolności jakościowej procesu produkcji elementów h hydraulicznych zgodnie z normą ISO 9001: 2008 (W Wymagania dotyczące systemów zarządzania jakością). Statystyczna kontrola procesu cięcia jest analizowana na podstaw wie rozkładu normalnego i analizy zdolności jakościowej procesu w oparciu o współczynniki Cp i Cpk. Uzyskane wyniki współczynników wynoszą odpowiednio Cp = 3,29 i Cpk = 0,73. W oparciu o uzyskane wyniki możemy uznać, że proces jest statystycznie uregulowany, ale przesunięty względem wartości nominalne ej.
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.