Sharif Digital Repository

Nowadays, many manufacturing and service systems provide products and services to their customers in several consecutive stages of operations, in each of which one or more quality characteristics of interest are monitored. In these environments, the final quality in the last stage not only depends on the quality of the task performed in that stage but also is dependent on the quality of the products and services in intermediate stages as well as the design parameters in each stage. In this paper, a novel methodology based on the posterior preference approach is proposed to robustly optimize these multistage processes. In this methodology, a multi-response surface optimization problem is... 

While researchers have developed several approaches to attain design variable settings that simultaneously optimize multiple-quality characteristics, the multi-response optimization has become a common practice in complicated manufacturing processes. Most of these research works assume independency of responses where their variances are constant over the experimental space. However, there are many manufacturing processes in practice where the quality characteristics under consideration are correlated. In this study, an efficient approach based on principal component analysis and a conventional desirability function is proposed to optimize correlated multiple responses. This approach not only... 

In this study, a multivariate-based strategy was developed for simultaneous determination of thirteen carcinogenic polycyclic aromatic hydrocarbons (PAHs) in water samples using gold nanoparticles (AuNPs) as solid-phase extraction (SPE) sorbent combined with gas chromatography (GC). The extraction technique is based on the strong affinity between citrate-capped AuNPs and PAHs. Furthermore, characterization of AuNPs was performed by UV-vis spectroscopy and transmission electron microscopy (TEM) techniques. A rotatable central composite design (CCD) combined with multiple linear regression (MLR) was used for designing the extraction procedure and developing models using the GC peak areas of 13... 

In this study, QuEChERS combined with dispersive liquid-liquid microextraction is developed for extraction of ten pesticides in complex sample matrices of water and milk. In this regard, effective factors of proposed extraction technique combined with gas chromatography with flame ionization detector were designed, modeled, and optimized using central composite design, multiple linear regression, and Nelder–Mead simplex optimization. Later, univariate calibration model for ten pesticides was developed in concentration range of 0.5–100 ng/mL. Surprisingly, quadratic calibration behavior was observed for some of the pesticides. In this regard, Mandel's test was used for evaluating linearity...