Statistical quality control in micro-manufacturing through multivariate ?-EWMA chart
نویسندگان
چکیده
Micro-manufacturing processes are characterized by high process variability and an increased significance of measurement uncertainty in relation to tight tolerance specifications. Therefore, an approach that separates the superposition of measurement and manufacturing variation is demanded. A novel design for a quality control chart that makes it possible to monitor, control and extract measurement variation frommanufacturing variation is proposed. Thus, a definite cause diagnosis on the approval or rejection of micro-components due to errors either in the measurement or in the manufacturing process is possible. The proposed multivariate m-EWMA chart which is based on weighting each measurement data with its current measurement variation is discussed and benchmarked with traditional control charts.
منابع مشابه
A Generalized Linear Statistical Model Approach to Monitor Profiles
Statistical process control methods for monitoring processes with univariate ormultivariate measurements are used widely when the quality variables fit to known probabilitydistributions. Some processes, however, are better characterized by a profile or a function of qualityvariables. For each profile, it is assumed that a collection of data on the response variable along withthe values of the c...
متن کاملMonitoring Fuzzy Capability Index $widetilde{C}_{pk}$ by Using the EWMA Control Chart with Imprecise Data
A manufacturing process cannot be released to production until it has been proven to be stable. Also, we cannot begin to talk about process capability until we have demonstrated stability in our process. This means that the process variation is the result of random causes only and all assignable or special causes have been removed. In complicated manufacturing processes, such as drilling proces...
متن کاملA Multiobjective Optimization for the Ewma and Mewma Quality Control Charts
The Multivariate EWMA control chart, MEWMA, Lowry, Woodall, Champ and Ridgon [1] and its univariate version EWMA, may be designed to efficiently detect small shifts in the mean vector of a set of p quality characteristics of a production process. However, this work presents a method for the optimal design of MEWMA and EWMA charts parameters to control processes where it is not convenient to det...
متن کاملEWMA control chart limits for first- and second-order autoregressive processes
(Correction made here after initial online publication.) Today's manufacturing environment has changed since the time when control chart methods were originally introduced. Sequentially observed data are much more common. Serial correlation can seriously affect the performance of the traditional control charts. In this article we derive explicit easy-to-use expressions of the variance of an EWM...
متن کاملSeasonal ARMA-based SPC charts for anomaly detection: Application to emergency department systems
Monitoring complex production systems is primordial to ensure management, reliability and safety as well as maintaining the desired product quality. Early detection of emergent abnormal behaviour in monitored systems allows pre-emptive action to prevent more serious consequences, to improve system operations and to reduce manufacturing and/or service costs. This study reports the design of a ne...
متن کامل