In this presentation, new process quality indices are proposed. The current world-wide used process capability indices are zero-defects indices for the purpose of meeting the specification requirements, while the process quality indices are zero-loss indices for the purpose of approaching the target value.
In fundamentally, the process quality indices focus not on the defect rate of the process, but on the average quality loss of the process. In other words, the ideal goal of the process quality is zero-loss based on the target value, not merely on the zero-defects based on the specification limits. Using process quality indices to evaluate process quality capability is a great change of quality management philosophy. As a producer, the ideal goal of quality management should be zero-loss.
Compared with process capability indices, process quality indices have the following four significant advantages:
1. The process capability indices need to be evaluated based on the probability distribution of the process, which is very troublesome for the case of non-normal distributed process. The process quality indices have no requirements for process distribution, and do not need to make any assumptions or make great efforts to find the probability model of a process. As Deming and Wheeler pointed out, in practice, exactly stable processes never exist. Real processes are never entirely free of perturbations. The process quality indices do not need to consider the probability model of the process at all. If the samples which collected for the process capability analysis can well represent the process, the evaluated result of the process quality capability will be unique. Neither the process quality indices nor the Shewhart control charts approach require probability model, used them in combination, can ensure the process to be improved and controlled in the most economical, simple and effective way, to bring the process truly maintained in a stable and capable expected state.
2. The process capability indices based on the delivery specification limits only concern the product conforming rate or defect rate, the deviation from the target value of the product within the delivery specification limits is not evaluated. The process quality indices based on Taguchi quality loss function can include all products within the functional limits into the evaluation, and the evaluation baseline is the deviation of each characteristic value from the target value. In other words, the evaluation scope of the process quality capability indices not only cover the non-conforming products beyond the delivery specification limits, but also include the products which within the specification limits. In the actual production process, even if there is a case that the products beyond the functional limits are shipped to the customer, it will be a rare accident. So, in order to evaluate the process quality capability, it is perfectly possible only to consider the case that all product characteristic values are within functional limits.
3. The new process quality indices used combined with Shewhart control charts approach will make the statistical process control completely bypass the attention to the probability distribution of the process, this will greatly simplify the statistical process control, which is more suitable for engineers and even operators to use on the manufacturing site.
4.No matter how many numbers of the data, the process quality indices can be evaluated. An individual characteristic value can be evaluated, one subgroup can be evaluated, a big data process with full automation inspection can also be evaluated. Obviously, it is do necessary to use process quality indices instead of process capability indices. Process quality indices are the true metrics for evaluating the process quality level. Except for the assumption based on Taguchi quality loss function, process quality indices do not care about the actual probability distribution of the process at all. For three types of quality characteristics, standard and easy understood calculation Equations were given respectively. In the process improvement, by comparing the quality indices before and after the improvement, we can easily evaluate the improvement effects and calculate the average loss rate reduced by the process improvement. The Zone which the process quality indices located can direct the producer the continuous improvement potential. Process quality indices approach is more suitable for quality management in the Era of big data.
Because the formula can not be shown here, the formula of process quality indices can not be shown. If needed, please contact me.
Understand the new proposed process quality indices for process capability evaluation.
Understand how to calculate the process quality indices for three types of characteristics (nominal-the-best, smaller-the-best and larger-the-best) respectively.
Understand how to use the process quality indice to evaluate process capability and direct the continuous improvement.