Sensitivity analysis–based dynamic process capability evaluation for small batch production runs

Abstract

Quantifying the current and expected future performance of a machining process no doubt is essential for continuous improvement of product quality and productivity. However, process capability evaluation for small batch production runs is a challenging work, because the assumptions required by traditional evaluation approaches based on statistical process control techniques are commonly not satisfied in real world. In this article, a sensitivity analysis–based process capability evaluation method for small batch production runs is proposed, and a new capability index is also presented correspondingly. In this method, an error propagation model between machining errors and input errors is first established using weighted least squares support vector machine. Then, the sensitivity distribution of machining errors versus input errors is characterized by a set of eigenvalues and eigenvectors in the variation space of input errors. Third, the safe variation space of input errors is solved according to the specification limits of quality characteristics. Finally, the process capability is evaluated by comparing the fitness between the safe variation space and the tolerance space of input errors. A practical case is addressed to validate the feasibility and effectiveness of the proposed method, and the results demonstrate that the method can measure a real small batch machining process effectively and get rid of the common assumption of independent and identical distribution, which is needed by traditional methods.

A fuzzy approach to determine process quality for one-sided specification with imprecise data

“…Otsuka and Nagata 25 proposed a novel approach to process capability which controls part dimensions based on product performance. Zhou et al 26 proposed a sensitivity analysis of process capability evaluation for small-batch production runs. Chang et al 27 developed a process quality analysis chart based on an accuracy index and a precision index, which analyzes process quality determined by multiple quality characteristics.…”

An Enhanced DMAIC Method for Feature-Driven Continuous Quality Improvement for Multi-Stage Machining Processes in One-of-a-Kind and Small-Batch Production

“…And its value can be calculated by comparing the positional relation and volume relation between S rf and S sf . The specific calculation process can be seen in the literature [44] and this article will not repeat them. According to the recommended minimum process stability, some controlling approaches must be done as Figure 8 shows.…”

Modified weighted standard deviation index for adequately interpreting a supplier’s lognormal process capability

“…Wu et al 15 discussed the relationships of quality assurance and some major PCIs in relation to four aspects, namely, process consistency, process relative departures, process yield, and expected relative loss. In addition to the review paper above, see literature [16][17][18][19][20][21][22] for more discussion of PCIs.…”