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A Primer on Product Risk Management
Published in Ali J Jamnia, Khaled Atua, Executing Design for Reliability within the Product Life Cycle, 2019
The process of writing a control plan begins with developing an understanding of process variations. This may come about through a short capability study to ensure that the proposed process is realistic. This requires that a knowledge of measurement systems exists and that it is appropriate. By measurement systems, we mean that the techniques and approaches used to measure the process outcome are appropriate to the process.6 Often, if a measurement system analysis (MSA) is not available, a design of experiments may be conducted (called gage repeatability and reproducibility, or gage R&R) to measure and qualify the levels of variation. A more detailed examination of gage R&R is beyond the scope of this work.
Process Capability
Published in Gisi Philip, Sustaining a Culture of Process Control and Continuous Improvement, 2018
Measurement systems analysis (MSA) is used to assess the quality of measurement data. It ensures data collection procedures and systems provide adequate resolution by understanding measurement bias and the influence of variation on specified tolerances. Bias is the difference between an average output measurement compared to a standard or reference value. It’s an assessment of gage accuracy where the smaller the difference between the actual versus reference value, the better (Figure 4.1).
Robust Quality for Analytics
Published in Rajesh Jugulum, Robust Quality, 2018
To obtain accurate measures, performing a measurement system analysis (MSA) is quite important. MSA is a method for evaluating how much variation is present in the process by which we collect data. It answers the question regarding the accuracy and reliability of data as well as the process of data collection. MSA also helps in evaluating the effectiveness of the data collection plan.
Managing the powder coat waste stream: an industrial experimentation approach
Published in Production Planning & Control, 2023
The purpose of this phase is to define and quantify the problem being investigated. This includes acquiring a complete understanding of the underlying process that needs improvement. The key steps involved are process mapping to outline the key process steps; determination of appropriate output measure(s) i.e. variable measure(s) for evaluating process output; monitoring the distribution of process output measures using a suitable sampling plan; creation of a baseline distribution to quantify the problem; and evaluation of the effectiveness of measurement system stability and repeatability. Some of the problem-solving tools employed in this phase are process flowcharts to illustrate the scope and nature of the problem, multi-vari charts for sampling plan (Snee 2001; De Mast, Roes, and Does 2001) and Gauge Repeatability and Reproducibility study (GR&R) (Kumar et al. 2006). A Multi-vari is a data sampling plan to graphically highlight the dominant family of causes responsible for the process variation. It categorizes the family of causes into three types – positional variation or with-in-part variation, cyclic variation or part-to-part variation, and temporal variation or time-to-time variation (De Mast, Roes, and Does 2001). A GR & R or measurement system analysis (MSA) study is conducted to quantify the inherent variation in the measurement system (Kumar et al. 2006). For instance, the measurement system is considered acceptable if GR&R value is between 10 and 30%; and it needs improvement if the value is above 30%.
Gage R&R studies in measurement system analysis: A systematic literature review
Published in Quality Engineering, 2022
Williane de Oliveira Silva Soares, Rogério Santana Peruchi, Rômulo Augusto Ventura Silva, Paulo Rotella Junior
Measurement system analysis (MSA) is a set of statistical techniques that enables statistical quality control (Peruchi et al. 2014); allows the assessment of the influence of measurement errors on variations in manufacturing processes (Al-Refaie and Bata 2010); and quantifies the accuracy (Yeh and Sun 2013), precision and stability of a measurement system (MS) (Saikaew 2018). Investigating an MS is a standardized process for extracting measurements from a mensurand; it allows statistical inference on the quality characteristics and investigation of measurement error (AIAG 2010). MSs are evaluated in virtually any type of manufacturing process (Peruchi et al. 2014) through the application of statistical techniques and control logic in the measurement process (AIAG 2010). MSA helps in quantifying the capacity of a gage or measurement device to generate data that support decision-making (Majeske 2012a). Furthermore, it ensures that the variability of an MS is not significant in relation to the variation in the manufacturing process (Pereira et al. 2016). The total variation observed in a process is caused by two sources: the process itself and MS (Al-Refaie and Bata 2010). If both variations are improperly distinguished, that is, if process variations are confused with MS variations, unnecessary adjustments may be made to the process. Therefore, it is necessary to evaluate the MS and determine the degree of variability associated with measurement errors.
A region segmentation method to measure multiple features using a tactile scanning probe
Published in International Journal of Computer Integrated Manufacturing, 2019
Feng Li, Joseph Hiley, Tauseef Mohammed Syed, Carl Hitchens, Miguel Garcia Lopez-Astilleros
As the inspection of large machined components (those being over 2 m) is a costly and difficult activity, on-machine inspection has the potential to reduce time, cost and risk associated with the manufacture of large-volume components. The logistics involved in relocating large components from the machining centre to a CMM are difficult and often account for a significant amount of the overall manufacturing time. Further work will involve the evaluation of the performance of probing systems on a multiple axis large-scale machining centres. A measurement system analysis (MSA) will be carried out to qualify measurement systems for the use on machine centres by quantifying accuracy, precision and stability. Then, the region segmentation method described in this paper will be replicated using a SP installed on a CNC machining centre. The measured results will be compared with the CMM results detailed in this study. Results of this research will greatly expand the knowledge base pertaining to on-machine inspection.