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Statistical Process Control (SPC) is a powerful collection of problem solving tools and the most sophisticated useful method in achieving process stability and improving the process capability through the reduction of variability. In the manufacturing process, every product doesn’t meet the desired range of quality consistently with the customer specification. This inconsistency occurs due to several sources of variations such as machines, operators, materials etc. The Ultimate target of control chart is to monitor the variations, and subsequently control the process. On account of applying SPC methods, this study deals with the control and improvement of the quality of bolt by inspecting the bolt’s height, diameter and weight from a bolt manufacturing company. In this inspection, we have developed X bar chart, S and Range control chart for each three variables. Furthermore, we have also focused on Estimated Weighted Moving Average (EWMA) for detecting small process shifts and multivariate Hotelling’s T2 for simultaneous monitoring of height and diameter of bolt. These inspections show that either the process is in control or out of control. For the out of control situation, the assignable reasons behind it should be identified and prevented by taking necessary steps.
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Statistical Process Control (SPC) is a powerful collection of problem solving tools and the most sophisticated useful method in achieving process stability and improving the process capability through the reduction of variability. In the manufacturing process, every product doesn’t meet the desired range of quality consistently with the customer specification. This inconsistency occurs due to several sources of variations such as machines, operators, materials etc. The Ultimate target of control chart is to monitor the variations, and subsequently control the process. On account of applying SPC methods, this study deals with the control and improvement of the quality of bolt by inspecting the bolt’s height, diameter and weight from a bolt manufacturing company. In this inspection, we have developed X bar chart, S and Range control chart for each three variables. Furthermore, we have also focused on Estimated Weighted Moving Average (EWMA) for detecting small process shifts and multivariate Hotelling’s T2 for simultaneous monitoring of height and diameter of bolt. These inspections show that either the process is in control or out of control. For the out of control situation, the assignable reasons behind it should be identified and prevented by taking necessary steps.
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statistical quality control, the use of statistical methods in the monitoring and maintaining of the quality of products and services. One method, referred to as acceptance sampling, can be used when a decision must be made to accept or reject a group of parts or items based on the quality found in a sample. A second method, referred to as statistical process control, uses graphical displays known as control charts to determine whether a process should be continued or should be adjusted to achieve the desired quality.Statistical process control (SPC) or statistical quality control (SQC) is the application of statistical methods to monitor and control the quality of a production process. This helps to ensure that the process operates efficiently, producing more specification-conforming products with less waste scrap. SPC can be applied to any process where the "conforming product" (product meeting specifications) output can be measured. Key tools used in SPC include run charts, control charts, a focus on continuous improvement, and the design of experiments. An example of a process where SPC is applied is manufacturing lines. SPC must be practiced in two phases: The first phase is the initial establishment of the process, and the second phase is the regular production use of the process. In the second phase, a decision of the period to be examined must be made, depending upon the change in 5M&E conditions (Man, Machine, Material, Method, Movement, Environment) and wear rate of parts used in the manufacturing process (machine parts, jigs, and fixtures). An advantage of SPC over other methods of quality control, such as "inspection," is that it emphasizes early detection and prevention of problems, rather than the correction of problems after they have occurred. In addition to reducing waste, SPC can lead to a reduction in the time required to produce the product. SPC makes it less likely the finished product will need to be reworked or scrapped. Statistical process control was pioneered by Walter A. Shewhart at Bell Laboratories in the early 1920s. Shewhart developed the control chart in 1924 and the concept of a state of statistical control. Statistical control is equivalent to the concept of exchangeability. Statistical process control is appropriate to support any repetitive process, and has been implemented in many settings where for example ISO 9000 quality management systems are used, including financial auditing and accounting, IT operations, health care processes, and clerical processes such as loan arrangement and administration, customer billing etc. Despite criticism of its use in design and development, it is well-placed to manage semi-automated data governance of high-volume data processing operations, for example in an enterprise data warehouse, or an enterprise data quality management system.In manufacturing, quality is defined as conformance to specification. However, no two products or characteristics are ever exactly the same.
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![Quality ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Er.Sartaj Singh Bajwa](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)