Some improvements in taguchi's economic method allowing continued quality deterioration in production process

On-Line Process Control using Attributes with Misclassification Errors: An Economical Design for Short-Run Production

“…The example described in this section is based on Trindade et al (2007), Nandi and Sreehari (1999), and Taguchi et al (1989) and real cases related to Dasgupta (2003) and Taguchi et al (2004). This choice is motivated by simplicity and ease of adjustment to other applications.…”

Economic modelling for statistical process control subject to a general quality deterioration

“…Indeed, note that this kind of general shift mechanism is somewhat like the drift mechanism, which is another focused scenario with regard to control chart design that involves an assignable cause resulting in a linear/non-linear drifting of μ away from μ 0 (most of this stream of research study linear drifts, such as Fahmy and Elsayed (2006), Su, Shu, andTsui (2011), Xu, Wang, andReynolds (2013) and Kazemi, Bazargan, and Yaghoobi (2014), and only a few consider non-linear drifts, see Cai et al (2002), and Capizzi and Masarotto (2012)). Besides, for monitoring process for attributes with continued quality deterioration, readers may see Nandi and Sreehari (1999), and Trindade, Ho, and da Costa Quinino (2007). In general, both mechanisms consider that the assignable cause generates a progressive degradation in process mean in the early stages, but the distinctive feature is that the drift mechanism typically refers to slow and longstanding drifts that appear, such as, in tool wear, operator fatigue or material consumption, whereas the general shift mechanism generally arises from the continuity of variations and attains a new stable state after the interim period.…”

Monitoring process for attributes with quality deterioration and diagnosis errors

“…The monitoring procedure consists of inspecting a single item at every m produced items. If the inspected item is judged conforming, the production process goes on; otherwise, the process is stopped for adjustment.This type of procedure to monitor process was studied by many authors as Adams and Woodall [2], Srivastava and Wu [3][4][5][6][7][8], Box and Kramer [9], Box and Luceno [10], Chou and Wang [11], Nandi and Sreehari [12,13], and Wang and Yue [14]. Examples that put into practice this kind of procedure may include the automatic process of soldering, production of semiconductors, production of diode, production of printed circuit boards and chemical processes [15][16][17].…”

“…To this effect, they not only developed an approach that incorporates inspection errors but also evaluated the impact when those errors are not taken into account. About the effects of inspection errors on quality control, see Johnson et al [20], Ranjan et al [21], and Wang [22].Previous studies assume that the quality of process shifts from a constant high-quality level (State I) to a constant low-quality level (State II) [1,12,16,18,19] or follows a specific deterioration scheme as in [13]. In Nandi and Sreehari [13], the authors considered that the process shifts from producing conforming items to p 2 (100)% non-conforming items, and from such a level the quality deterioration is described by a linear model (this function was stated in a specific time interval), until the shift is detected by the control procedure.…”

“…Previous studies assume that the quality of process shifts from a constant high-quality level (State I) to a constant low-quality level (State II) [1,12,16,18,19] or follows a specific deterioration scheme as in [13]. In Nandi and Sreehari [13], the authors considered that the process shifts from producing conforming items to p 2 (100)% non-conforming items, and from such a level the quality deterioration is described by a linear model (this function was stated in a specific time interval), until the shift is detected by the control procedure.…”