Academic literature on the topic 'Quality control – Charts, diagrams, etc'
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Journal articles on the topic "Quality control – Charts, diagrams, etc"
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Chie, Ho Hwi, Januar Nasution, Ketut Gita Ayu, Nike Septivani, and Yualfin Renaldi. "Porcelain Product Quality Analysis in PT XYZ." ComTech: Computer, Mathematics and Engineering Applications 6, no. 4 (2015): 580. http://dx.doi.org/10.21512/comtech.v6i4.2195.
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PT. XYZ is a company engaged in manufacturing porcelain dinner ware such as plates, cups, teapot, bowl, etc Porcelain product is safe for use and product defect will only affect the aesthetic not the functional side. The company always maintain the quality of the products produced as by maintaining a good product, in terms of visuals, will keep customers interested in the product. Good quality products characterized by quality A / B and C, and the product defect characterized by the quality of D, Lost, and BU. Concepts and methods used to analyze is a statistical process control (SPC) which includes Pareto diagram, fraction nonconformities, flow charts and fishbone diagrams and management tools (fault tree analysis). Statistical Process Control (SPC) is one of the methods, which includes Pareto charts, fraction nonconformities, flow chart, and fishbone diagram and also management tools (fault tree analysis). SPC is useful to find the facts from the problems and factors that affect the quality of the products, while fault tree analysis is useful to analyze each of the production process.
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Ahammed, Rubel, and Md Zahid Hasan. "Humming noise reduction of ceiling fan in the mass production applying DMAIC-six sigma approach." World Journal of Engineering 18, no. 1 (2020): 106–21. http://dx.doi.org/10.1108/wje-07-2020-0329.
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Purpose Success and business reputation depend upon the quality of products where product quality depends upon the capability of a process, yield value and sigma score, etc. Poor quality of ceiling fan and mass rejection from quality check resulted in an alarming amount of cost for rework. As a result, the fulfillment of the production target was getting difficult day by day. The main purpose of this research is to identify the crucial causes for humming noise of ceiling fans and control it to a tolerable level so that maximum quality can be achieved. Design/methodology/approach The poor quality of ceiling fans was determined from the Pareto analysis of the define, measure, analyze, improve and control model which was humming noise during running and further actions were undertaken regarding the reduction of the humming noise. Project charter was formed before initiating the measure phase to study the suppliers, inputs, processes, outputs and customers diagram with process parameters and existing noise data were collected from random samples to determine the rolled throughput yield (94.95% existing) and existing sigma score which value of 3.14 and also the poor value (1.05) of process potential index implied that the process condition was below standard (<1.33) and need to be improved badly. Then root causes analysis and relationship diagram was prepared to identify the possible causes and with the design of experiments and correlation analysis, it was clear that the air gap between the stator and rotor was the main culprit behind the humming noise. Findings The minimum value of air gap was determined from boxplot analysis which was 0.2 mm–0.225 mm and the corresponding mean, the minimum and maximum value of sound level in dB (37.5–40.3 dB) for 0.225 mm air gap with the watt consumption (83 w) from the hypothesis test for the corresponding air gap. Finally, the updated sigma score and process capability analysis were performed with control charts to show the comparison after applying the DMAIC-six sigma methodology. The final sigma score was 5.1 which indicates a significant improvement of the process with the capability of saving US$23,438/year caused by the poor quality of ceiling fans. Practical implications Only quantitative values of the causes behind the humming noise were possible to identify. Other trivial many causes elimination might improve the sigma score closer to 6.00. The final sigma score that was achieved from this research was sustainable. Originality/value A structural approach with proper data analysis and application of various tools to detect the actual cause behind the humming noise of ceiling fans with numerical value has not been found in any literature. This research study can be a valuable asset for ceiling fan mass producers.
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Antony, Jiju, E. V. Gijo, Vikas Kumar, and Abhijeet Ghadge. "A multiple case study analysis of Six Sigma practices in Indian manufacturing companies." International Journal of Quality & Reliability Management 33, no. 8 (2016): 1138–49. http://dx.doi.org/10.1108/ijqrm-10-2014-0157.
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Purpose The purpose of this paper is to explore the fundamental barriers/challenges, benefits, commonly used tools and techniques, organisational infrastructure and impact on organisational performance in three Indian manufacturing companies. Design/methodology/approach A multi-case study analysis using the exploratory case study research was adopted by the authors to obtain a deeper insight into the Six Sigma implementation within three distinctive manufacturing organisations in India. Interviews were conducted with relevant staff (Six Sigma Deployment Champions, Six Sigma Master Black Belts and Six Sigma Black Belts) in all three companies. Findings Some of the barriers in implementing and sustaining Six Sigma identified from the case studies include: lack of accuracy of data generated from the processes, lack of understanding of the benefits of Six Sigma in the early stages of its adoption, high-attrition rate of Six Sigma Black Belts and so on. The benefits of Six Sigma included improvement of process yield, reduction of rework and rejection, reduction of raw material inventory, improved on-time delivery, on-time availability of material for production and so on. Supplier-input-process-output-customer, cause and effect diagram, process mapping, hypothesis tests (two sample test, F-test, etc.), control charts (X-bar-R chart, individual chart, etc.), simple graphical tools such as histograms, box plots and dot plots were the most commonly used tools of Six Sigma across the companies that participated for this research. All three companies have reported that Six Sigma had a positive impact on organisational performance and moreover the study also revealed that Six Sigma had positive impact on customer satisfaction, return-on-investment, productivity and product quality. Research limitations/implications The study was carried out in three Indian companies and therefore the findings cannot be generalised. The authors are extending the study to three more companies and the findings will be reported in the forthcoming months. Practical implications The findings of the study provide a good foundation to understand the fundamental barriers, benefits, commonly used tools and whether Six Sigma is having any impact on business performance in the Indian context. Very few empirical studies have been carried out on Six Sigma implementation in the Indian manufacturing companies and this research sets an agenda for a number of studies to follow on in the forthcoming years. Originality/value In authors’ opinion, this is possibly one of the first multi-case empirical studies on Six Sigma implementation in the Indian manufacturing companies. The results of the study can be used to benchmark with similar studies in other countries to understand the good and bad management practices of Six Sigma implementation.
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AHMAD, RAHMAWATY, RESMAWAN RESMAWAN, and DEWI RAHMAWATY ISA. "ANALISIS STATISTICAL QUALITY CONTROL DALAM UPAYA MENGURANGI JUMLAH PRODUK CACAT DI PABRIK ROTI THE LI NO’U BAKERY." Jambura Journal of Probability and Statistics 1, no. 1 (2020): 24–36. http://dx.doi.org/10.34312/jjps.v1i1.4578.
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Quality control is a technical and management activity which measures the quality characteristics of a product or service. Statistical quality control can be used to find production errors that result in defective products so that further corrective action can be taken to overcome them. The objective to be achieved in this research is to determine the Statistical Quality Control (SQC) method with pareto diagrams, control charts, cause and effect diagrams and 5W+1H analysis applied to The Li No'u Bakery in controlling quality to minimize failed products. The data in this study were obtained through direct observation and field interviews. Data analysis tools used are control charts, pareto diagrams, cause and effect diagrams and 5W + 1H analysis. Through a cause and effect diagram, the main factors causing the failure of bakery products at The Li No'u Bakery are manufacturers/employees. This is because the operator fails in making bakery products both the preparation of raw materials, the production process and packaging. So training is needed on making the dough, how to put bread and how to covenant and employee order according to the standard of The Li No'u Bakery.
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Hignasari, L. Virginayoga. "Tinjauan Teoritis Pengendalian Kualitas Produk Hasil Industri Dengan Metode Statistik." Jurnal Ilmiah Vastuwidya 3, no. 1 (2020): 24–29. http://dx.doi.org/10.47532/jiv.v3i1.97.
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This study was aimed to determine the quality control process of an industrial product with theoretical statistical methods. This research was a qualitative research with literature study method. Data obtained from several studies that take samples in the field of goods industry. The data obtained was then analyzed and described descriptively. The quality of a product was one of the basic decisions of consumers to be satisfied with the products they buy according to their wishes and expectations. Statistical quality control was a problem solving technique that was used as a monitor, controller, analyzer, manager and improve the process by using statistical methods. The quality control process of an industrial product with statistical methods was as follows: 1) Made Chech Sheets, 2) Made Pareto Diagrams, 3) Made Control Charts, 4) Made Cause and Effect Diagrams, 5) Made Failure Mode Effect Anlaysis (FMEA) table.
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Zach, Martin. "Applicable quality management tools in a production cycle of a selected company." Global Journal of Business, Economics and Management: Current Issues 8, no. 1 (2018): 10–19. http://dx.doi.org/10.18844/gjbem.v8i1.3295.
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The paper deals with quality control in a Czech manufacturing company, especially at its quality department. The objective is to define the identified production failures, using selected quality management tools, and to determine the causes of technological problems. The following methods and tools were used: cause and effect analysis—Fishbone diagrams (Ishikawa diagrams); Pareto charts, flowcharts and others methods, whose results have been visually displayed. Based on a detail analysis of the production failures, the proposal to eliminate them as well as a draft implementation of the corrective action and its effect on enhancing quality in the production company are presented. The elements such as frequency of controls, adherence to regular inspections and replacement of filters in air conditioning units, cleaning and compliance with the work rules were monitored, as these elements have an impact on product quality and customer satisfaction. The implementation of the corrective actions and the related financial estimate are presented.
 
 Keywords: Quality, production process, quality management tools, quality management, implementation, Pareto diagrams, cause and effect diagrams, safety.
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Plourde, Collin L., William T. Varnado, Barbara J. Gleaton, and Devika G. Das. "Reducing Infusion Clinic Wait Times Using Quality Improvement." JCO Oncology Practice 16, no. 8 (2020): e807-e813. http://dx.doi.org/10.1200/jop.19.00643.
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PURPOSE: Long wait times are a common occurrence for chemotherapy infusion patients and are a source of decreased patient satisfaction. Our facility sought to decrease outpatient infusion clinic wait times by 20% using the Model for Improvement, quality improvement tools, and Plan-Do-Study-Act cycles. METHODS: A multidisciplinary team was formed to address clinic wait times. Patient interviews, time studies, process mapping, brainstorming sessions, affinity diagrams, fishbone diagrams, and surveys were used to define the problem and to develop an intervention. Wait times from check-in until medication administration were analyzed using statistical process control charts. Our Plan-Do-Study-Act cycle led to the addition of a “fast-track” clinic title for patients not waiting for laboratory results on the day of treatment and changes in clinic communication. The fast-track clinic signaled for those patients to have priority for vital sign collection and earlier notification to pharmacy to begin preparing medications. RESULTS: Baseline wait times for patients not requiring laboratories on the day of treatment averaged 1 hour and 33 minutes. After intervention, using statistical process control charts, a shift was observed with a new average wait time of 1 hour and 12 minutes (a 23% decrease). Wait times for patients requiring laboratories on the day of treatment did not change significantly. CONCLUSION: Implementation of a fast-track clinic title and improving communication resulted in a significant reduction in wait times for patients not requiring laboratories on the day of treatment. Future efforts will focus on sustainment and improving wait times for all patients.
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Bates, Katherine E., Jean Connor, Nikhil K. Chanani, et al. "Quality Improvement Basics: A Crash Course for Pediatric Cardiac Care." World Journal for Pediatric and Congenital Heart Surgery 10, no. 6 (2019): 733–41. http://dx.doi.org/10.1177/2150135119881393.
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Background: Lack of knowledge of quality improvement (QI) methodology and change management principles can explain many of the difficulties encountered when trying to develop effective QI initiatives in health care. Methods: An interactive QI workshop at the 14th Annual Meeting of the Pediatric Cardiac Intensive Care Society provided an overview of the role of QI in health care, basic QI frameworks and tools, and leadership and organizational culture pitfalls. The top five QI projects submitted to the meeting were later presented to an expert QI panel in a separate session to illustrate examples of QI principles. Results: Workshop presenters introduced two major QI methodologies used to design QI projects. Important first steps include identifying a problem, forming a multidisciplinary team, and developing an aim statement. Key driver diagrams were highlighted as an important tool to develop a project’s framework. Several diagnostic tools used to understand the problem were discussed, including the “5 Why’s,” cause-and-effect charts, and process flowcharts. The importance of outcome, process, and balancing measures was emphasized. Identification of interventions, the value of plan-do-study-act cycles to fuel continuous QI, and use of statistical process control, including run charts or control charts, were reviewed. The importance of stakeholder engagement, transparency, and sustainability was discussed. Later, the top five QI projects presented highlighted multiple “QI done well” practices discussed during the preconference QI workshop. Conclusions: Understanding QI methodology and appropriately applying basic QI tools are pivotal steps to realizing meaningful and sustained improvement.
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Park, Chanseok, and Min Wang. "A Study on the X ¯ and S Control Charts with Unequal Sample Sizes." Mathematics 8, no. 5 (2020): 698. http://dx.doi.org/10.3390/math8050698.
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The control charts based on X ¯ and S are widely used to monitor the mean and variability of variables and can help quality engineers identify and investigate causes of the process variation. The usual requirement behind these control charts is that the sample sizes from the process are all equal, whereas this requirement may not be satisfied in practice due to missing observations, cost constraints, etc. To deal with this situation, several conventional methods were proposed. However, some methods based on weighted average approaches and an average sample size often result in degraded performance of the control charts because the adopted estimators are biased towards underestimating the true population parameters. These observations motivate us to investigate the existing methods with rigorous proofs and we provide a guideline to practitioners for the best selection to construct the X ¯ and S control charts when the sample sizes are not equal.
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Zhang, Yin Zi, Liang Cai Cai, and Min Fan. "Schedule Management of Airport Flying Area Construction Based on BIM." Applied Mechanics and Materials 584-586 (July 2014): 2653–58. http://dx.doi.org/10.4028/www.scientific.net/amm.584-586.2653.
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Airport flying area construction is a complex dynamic process. Its typical features including: complex construction process, large construction area, underground pipe trench interwoven and so on. Traditional construction schedule management of airport flying area is based on Gantt charts and network diagrams, which is generated before the construction, not supporting real-time updates. A preliminary exploration of BIM-based schedule management in airport flying area engineering is conducted. Using Civil3D,Revit, Navisworks and MS Project software, the construction image progress model can be established. Manager also can achieve laying on the type of runway, the number of layers, daily progress charts and updates, and to achieve global control so as to improve management efficiency and management quality.
Dissertations / Theses on the topic "Quality control – Charts, diagrams, etc"
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Myslicki, Stefan Leopold 1953. "A VARIABLE SAMPLING FREQUENCY CUMULATIVE SUM CONTROL CHART SCHEME." Thesis, The University of Arizona, 1987. http://hdl.handle.net/10150/276503.
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This study uses Monte Carlo simulation to examine the performance of a variable frequency sampling cumulative sum control chart scheme for controlling the mean of a normal process. The study compares the performance of the method with that of a standard fixed interval sampling cumulative sum control chart scheme. The results indicate that the variable frequency sampling cumulative sum control chart scheme is superior to the standard cumulative sum control chart scheme in detecting a small to moderate shift in the process mean.
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Korpela, Kathryn Schuler 1960. "A COMPARISON OF TWO MULTIVARIATE CUMULATIVE SUM CONTROL CHART TECHNIQUES." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/275513.
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Lu, Chao-Wen. "Control charts based on residuals for monitoring processes with correlated observations." Diss., Virginia Tech, 1993. http://hdl.handle.net/10919/40300.
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In statistical process control, it is usually assumed that observations on the process output at different times are lID. However, for many processes the observations are correlated and control charts for monitoring these processes have recently received much attention. For monitoring the process level, this study evaluates the properties of control charts, such as the EWMA chart and the CUSUM chart, based on the residuals from the forecast values of an ARMA model. It is assumed that the process mean is a ftrst order autoregressive (AR(l)) model and the observations are the mean plus a random error. Properties of these charts are evaluated using a Markov chain approach or an integral equation approach. The performance of control charts based on the residuals is compared to the performance of control charts based on the original observations. A combined chart using forecasts and residuals as the control statistics as well as a combined chart using the EWMA of observations and the EWMA of residuals as the control statistics are also studied by simulation. It is found that no universally "good" chart exists among all the charts investigated in this study.
In addition, for monitoring the process variance, two kinds of EWMA chart based on residuals are studied and compared.<br>Ph. D.
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Shobe, Kristin N. "Variable sampling intervals for control charts using count data." Thesis, Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/52076.
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This thesis examines the use of variable sampling intervals as they apply to control charts that use count data. Papers by Reynolds, Arnold, and R. Amin developed properties for charts with an underlying normal distribution. These properties are extended in this thesis to accommodate an underlying Poisson distribution.<br>Master of Science
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Zou, Xueli. "A robust Shewhart control chart adjustment strategy." Diss., This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-06062008-164701/.
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Vining, G. Geoffrey. "Determining the most appropiate [sic] sampling interval for a Shewhart X-chart." Thesis, Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/94487.
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A common problem encountered in practice is determining when it is appropriate to change the sampling interval for control charts. This thesis examines this problem for Shewhart X̅ charts. Duncan's economic model (1956) is used to develop a relationship between the most appropriate sampling interval and the present rate of"disturbances,” where a disturbance is a shift to an out of control state. A procedure is proposed which switches the interval to convenient values whenever a shift in the rate of disturbances is detected. An example using simulation demonstrates the procedure.<br>M.S.
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Hanson, Robert Alexander. "The application of a single control chart for dependent variables in multivariate quality control." Thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-05022009-040726/.
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Chung, Jain. "Control chart procedures based on cumulative gauging scores." Diss., Virginia Polytechnic Institute and State University, 1985. http://hdl.handle.net/10919/54277.
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Control charts based on cumulative gauging scores rely on gauge scoring systems used for transforming actual observations into integer gauging scores. In some cases, the gauging scores are easy to obtain by using a mechanical device such as in the go-no-go inspection process. Thus, accurate measurements of selected quality characteristics are not necessary. Also, different control purposes can be achieved p by using different scoring systems.
Cumulative gauging score charts based on two pairs of gauges are proposed to control the process mean or the standard deviation by either gauging one or several observations. Both random walk and cusum type cumulative gauging score charts are used. For controlling the process mean and standard deviation at the same time, a cusum type and a two-dimensional random walk type procedure are proposed. A gauging scheme can be applied to multivariate quality control by gauging either x² or T² statistics. A simple multivariate control chart which is based on the multivariate sign score vector is also proposed.
The exact run length distribution of these cumulative gauging score charts can be obtained by formulating the procedures as Markov chain processes. For some procedures, the average run length (ARL) can be obtained in a closed form expression by solving a system of difference equations with appropriate boundary conditions.
Comparisons based on the ARL show that the cumulative gauging score charts can detect small shifts in the quality characteristic more quickly than the Shewhart type X-chart. The efficiency of the cusum type gauging score chart is close to the regular CUSUM chart. The random walk type gauging score chart is more robust than the Shewhart and CUSUM charts to observations which have heavy a tailed distribution or which are serially correlated. For multivariate quality control. A procedure based on gauging the x² statistic has better performance than the x² chart. Also, a new multivariate control chart procedure which is more robust to the misspecification of the correlation than the x² chart is proposed.<br>Ph. D.
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Stoumbos, Zachary G. "Control charts applying a sequential test at fixed sampling intervals with optional sampling at fixed times." Diss., This resource online, 1993. http://scholar.lib.vt.edu/theses/available/etd-07132007-143152/.
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Hall, Deborah A. "A comparison of alternative methods to the shewhart-type control chart." Thesis, Virginia Tech, 1989. http://hdl.handle.net/10919/44642.
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<p>A control chart that simultaneously tracks the mean and variance of a
normally distributed variable with no compensation effect is defined in this
work. This joint control chart is compared to five other charts: an Χ chart,
an s<sup>2</sup> chart, a Reynolds and Ghosh chart, a Repko process capability plot, and
a t-statistic chart. The criterion for comparison is the probability of a Type
II sampling error. Several out-of-control cases are examined. In the case of
Repko, an equation is defined to compute the Type II error probability. The
results indicate that the Reynolds and Ghosh statistic is powerful for cases
when the variance shifts out of control. The Χ chart is powerful when the
mean shifts with moderate changes in the variance. The joint chart is
powerful for moderate changes in the mean and variance.<br>Master of Science
Books on the topic "Quality control – Charts, diagrams, etc"
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Wise, Stephen A. Innovative control charting: Practical SPC solutions for today's manufacturing environment. ASQ Quality Press, 1998.
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H, Olwell David, ed. Cumulative sum charts and charting for quality improvement. Springer, 1998.
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Advanced topics in statistical process control: The power of Shewhart's charts. SPC Press, 1995.
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Hart, Marilyn K. Quantitative methods for quality and productivity improvement. ASQC Quality Press, 1989.
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The methods and findings of quality assessment and monitoring: An illustrated analysis. Health Administration Press, 1985.
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Fair, Douglas C., and Stephen A. Wise. Innovative Control Charting: Practical Spc Solutions for Today's Manufacturing Environment. ASQ Quality Press, 1997.
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Wheeler, Donald J. The Power of Shewhart's Charts: The Power of Shewhart's Charts. SPC Press, Inc., 1995.
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Chokethaworn, Nantawong. An economic comparison of X[bar], cumulative sum and geometric moving average control charts for controlling process mean. 1986.
Find full textBook chapters on the topic "Quality control – Charts, diagrams, etc"
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Sivagami, Arasu, Michael Angelo Kandavalli, and Bhaskarrao Yakkala. "Design and Evaluation of an Automated Monitoring and Control System for Greenhouse Crop Production." In Next-Generation Greenhouses for Food Security. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97316.
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An embedded system integrated with sensors based on nanomaterial is proposed for closely monitoring and control microclimate parameters 24 hours a day to maximise production over the whole crop growth season by introducing greenhouse for the cultivation of plants or specific plant species. The system will also eliminate errors in human intervention to optimise production of crops. This system consists of sensors and actuators, an Analogue to Digital Converter (ADC) and a Raspberry Pi. The system will determine whether a defined threshold is passed by any climate parameter and systematically changes via the controller. The current work reduces human input through automated irrigation to optimally utilize a scarce resource, namely water. Climatic parameters for plant growth such as, moisture, humidity, temperature, water pressure in drip pipe, soil salinity etc. are monitored and optimized. Furthermore, work was extended to include GSM to control the entire farm remotely. For its success, it is very important to choose a greenhouse location. For instance, the problems are quite different when choosing an adjoining greenhouse, for instance a sunroom or greenhouse. The greenhouse location should be chosen for sunlight, proximity to power and water sources, wind, drain and freeze pockets, and the proximity of the garden and house. The intention behind accomplishment and devise of GSM based Fertigation System is to construct and evaluate the requirement of water in the yield as farming is the major resource of production which habitually depends on the water accessibility. Irrigation of water is usually done by manual method. To ease the work of the farmer GSM based automatic Fertigation (includes chemigation too) system can be implemented so that water wastage can be reduced and also the fertilizer can be added accordingly. Also the Soil Salinity can be checked and reduced if exceeds certain limit. By using GSM, only GSM command via GSM mobile can control the start and stop action of a motor that feeds the field with the water. GSM is used for controlling the entire process and the entire system backbone. It can be used from any distance to control irrigation. The results are assessed by electronic simulator PROTEUS using the desired optimised parameters, the design of this automated greenhouse system with PIC controller. As the inputs to the microcontroller and as an LCD screen record the respective outputs, the model produces a soil moisture sensor, light sensor and temperature sensor. The system performance is accurate and repeatable for measuring and controlling the four parameters that are crucial for plant growth - temperature, humidity, soil moisture and light intensity. With the reduction in electricity consumption, maintenance and complexity, and a flexible and precise environment control form for agriculture, the new system successfully cured quite a couple of defects in existing systems. Nano composite film sensors (Graphene and Graphene mixed in order to optimise the input of fertilisers for chemical composition determination. Using nano technology in agriculture enforces the firm bond between the engineer and farmer. Nano material film-based gas sensors were used to measure the presence of oxygen and CO2.using graphene nano composite sensors integrated into an embedded system, to detect the presence and levels of gases. Improve crop growth with combined red and blue light for lighting under the leavened and solar-powered LED lighting modules. This was achieved by graph/solar cells. The light was measured at the photosynthesis flux (PPFD) of 165 μmol m-2 s-1 by 10 cm of its LED module. LED lights were provided between 4:00 a.m. and 4:00 p.m. in the daytime treatments and night treatments from 10 to 10 hours. The use of the nighttime interlumination of LEDs was also economical than the interlumination of charts. Thus, nightlighting LEDs can effectively improve plant growth and output with less energy than the summer and winter times. Solar panels are best functioning during times of strong sunlight today, but begin to wan when they become too hot and cloudy. By allowing Solar Panels to produce electricity during harsh weather conditions and increase efficiency, a breakthrough in graphene-based solar panels can change everything. Ultimately with a fully autonomous system, agricultural productivity and efficiency, the length of the growing season, energy consumption and water consumption were recorded and monitored by exporting the data over GSM environment. With the steady decrease in the cost of high-performing hardware and software, the increased acceptance of self-employed farming systems, and the emerging agricultural system industry, the results will be reliable control systems covering various aspects of quality and production quantity.
Conference papers on the topic "Quality control – Charts, diagrams, etc"
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Nithyanandam, Ganesh Kumar, Matthew Franchetti, and Radhakrishnan Pezhinkattil. "Near Minimum Material Zone: A New Concept to Reduce the Weight of the Aircraft Components in Machining Using Lean Six Sigma Methodology." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-65555.
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A component in machining is accepted when the dimensions are within the tolerance specifications. In aircraft components machining, controlling the weight of the components is of high importance. In this paper, a new concept called near minimum material zone was introduced, which would address the control of the weight of the aircraft components in machining. To prove this concept, two sets of experiments with 20 samples were conducted using Deckel Maho CTX310 ECO VI CNC machine. The first experiment was conducted with normal machining processes. The second experiment was conducted using a new concept. Lean Six Sigma DMAIC methodology was adopted for this study. Several Six Sigma tools such as process capability analysis (Cp, Cpk), cause and effect diagram, X Hi/Lo and R-charts, etc. were used. The paper suggests that this new concept not only helped to control the weight of the aircraft components but also improved the desired quality by minimizing the dispersion of the component dimensions to obtain higher sigma level.
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Tulke, Klaus-Dieter, and Friedrich Schoeckle. "Assessment of the Real Fatigue Usage of the Volume Control System." In ASME 2008 Pressure Vessels and Piping Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/pvp2008-61524.
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As a major task of aging management, the quality status of every safety related system has to be assessed regularly. Thus the safety margin can be verified (and demonstrated) at every stage of operation and — if necessary — it can be reacted in time. One of the main aspects regarding the assessment of the quality status is the fatigue usage. Regarding the example of the volume control system of the nuclear power plant KKP 2 (PWR), the procedure to determine the actual fatigue usage is shown. There is a comprehensive monitoring of the global and the local loads of this system. The global monitoring is done using the plant instrumentation, the local monitoring is performed on the basis of individually installed transducers like thermocouples, displacement transducers, etc. Using the results of the monitoring the load cases are identified first and then their partial fatigue usage factors are summarized using the number of cycles determined by monitoring, usually. Thus it is demonstrated that all fatigue usage factors are below limits. However, if there are relevant new (i.e. not specified) transients these have to be analyzed and assessed. Regarding the volume control system the local monitoring showed “new” transients (thermal stratification) near a recuperative heat exchanger that were due to bypass operation. Consequently, the real actual fatigue usage was evaluated. In a first step, the relevant load cases (that were identified during the “local” monitoring history from 1991) were re-analyzed and correlated to the global signals. On this basis, the relevant transients and the number of cycles of the operation time without local monitoring (first startup of the plant in 1984) have been determined using the global signal records (digital and paper charts stored in archive). A conservative fatigue analysis showed that the maximum usage is related to the region of the inlet nozzles of the volume control system into the main coolant loops. With the proven history of transients the maximum fatigue usage D of this system was extrapolated to D = 0.27 (60 years of operation). The comprehensive global and local monitoring will be continued. On this basis the fatigue usage will be reviewed, regularly, and updated if necessary in future operation.
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De, Soumen, Nagarajan Sethuraman, and Chengyin Yuan. "A Formal Approach on Specification Modeling to Support Industrial PLC Program Verification." In ASME 2008 International Mechanical Engineering Congress and Exposition. ASMEDC, 2008. http://dx.doi.org/10.1115/imece2008-67458.
Full textAbstract:
Intensive global competition requires the automotive manufacturers to launch new vehicle models with a shorter launch time, better quality, lower cost and more customization. One of the key enablers for achieving these objectives is to have an efficient & error-free manufacturing automation system which is typically controlled by Programmable Logic Controllers (PLC). The current PLC logic code testing process in automotive industry is usually performed manually by individual engineer, and the overall testing quality highly depends on the engineer’s expertise and experience. The PLC logic code testing normally consists of two parts, testing requirements (specification) and testing methods. One of the major hurdles for applying rigorous testing methods on PLC logic verification in industry is the lack of formal testing specifications. The current PLC testing specifications and requirements are documented in various formats, such as sequence of operation document, process instrument diagram, wiring diagrams, and time motion diagrams, etc. These varied documents cannot be directly used for control logic testing and require a better alternative. Formal methods, the latest technology widely used in software testing, is an approach selected for generating comprehensive test cases to ensure the correctness and consistency of PLC programs. This paper presents a novel approach for specifying the expected behavior of the already implemented industrial PLC code. The generated formal specification models can work with math-based logic verification tool to facilitate the usage of formal verification in manufacturing automation control. The specification modeling methodology contains all the required information from different logic design and testing phases, such as process sequence, wiring information, logic pattern, code comments, and domain knowledge, etc. And the statecharts is used as model formalism, because of its capability to model states hierarchically and provide a better visual representation.