Model fitting of laboratory-generated experimental data is a foundational task in engineering, bridging theoretical models with real-world to enhance predictive accuracy. This process particularly valuable batch dynamic experiments, where mechanistic are often used represent complex system behavior. Here, we propose systematic algorithm tailored for the model and parameter estimation from laboratory rooted Process Systems Engineering framework. The paper provides an in-depth, step-by-step...

Developing innovative cosmetics products is essential for businesses in the beauty industry, influencing their ability to grow, remain competitive, and respond rapidly shifting market trends. A structured, customer-oriented approach product design development particularly crucial cosmetics, where factors such as safety, regulatory compliance, sustainability are paramount. In this context, Conceptual Engineering offers a valuable early-phase framework design, providing foundation define...

Since they were created in 1987, the ISO 9000 standards provide a unique experience of voluntary adoption and certification entities, covering at present organizations all sizes, sectors natures across globe. In this article we will some key results that derive from statistical analysis performed over richness values compiled time for numbers certified entities world its different countries, their evolution since January 1993 way to December 2001, thus providing what believe be pioneering...

Purpose This purpose of this paper is to present an optimization‐based approach support the design attribute sampling plans for lot acceptance purposes, with fraction non‐conforming items being modeled by a Poisson probability distribution function. Design/methodology/approach The stands upon minimization error equalities in controlled points operating curve (OC) respect sample size and number. It was applied simple double plans, including several combinations quality levels required...

This paper uses semidefinite programming (SDP) to construct Bayesian optimal design for nonlinear regression models. The setup here extends the formulation of designs problem as an SDP from linear Gaussian quadrature formulas (GQF) are used compute expectation in criterion, such D-, A- or E-optimality. As illustrative example, we demonstrate approach using power-logistic model and compare results literature. Additionally, investigate how is impacted by different discretising schemes space,...

We consider a hybrid modelling approach based on the combination of prior knowledge, in form mechanistic models, with tools for extraction knowledge from operating data: first component captures first-principles system behavior features, while second one accounts differences found between predictions and real data. The empirical methods tested include backpropagation Artificial Neural Networks (ANN), Multivariate Adaptive Regressive Splines (MARS) Regression Analysis (RA). In proposed...

The systematic design of exact optimal designs experiments is typically challenging, as it results in nonconvex optimization problems. literature on the computation model-based via mathematical programming, when covariates are categorical variables, still scarce. We propose mixed-integer semidefinite programming formulations, to find D-, A- and I-optimal for linear models, locally nonlinear models domain a finite set points. strategy requires: (i) generation candidate treatments; (ii)...

Abstract A moving finite elements scheme is developed and used for solving 1‐D dynamic population balance equations (PBE). The method stands on the weighted finite‐elements based approach, local solutions are represented by cubic Hermite polynomials. weighting function gradient of residuals with respect to time derivatives solution at nodes nodal velocities. general PBE considered includes nucleation, growth, aggregation breakage terms. accuracy (MFEM) evaluated comparing results analytical...

Finding Bayesian optimal designs for nonlinear models is a difficult task because the optimality criterion typically requires us to evaluate complex integrals before we perform constrained optimization. We propose hybridized method where combine an adaptive multidimensional integration algorithm and metaheuristic called imperialist competitive find designs. apply our numerical few challenging design problems demonstrate its efficiency. They include finding D-optimal item response model...

We study optimal designs for clinical trials when the value of response and its variance depend on treatment covariates are included in model. Such generalizations Neyman allocation, commonly used personalized medicine external factors may have differing effects depending subgroups patients. develop theoretical results D-, A-, E- D A-optimal construct semidefinite programming (SDP) formulations that support their numerical computation. E-optimal appropriate efficient estimation distinct...

This paper introduces a hybrid modeling approach based on the combination of prior knowledge, under form mechanistic models, with tools devoted to extraction knowledge from operating data. The first module captures first-principles system behavior, whereas second models output residuals between real data and predictions. empirical comprises two sequential tools: one partition time domain into zones where are well-fitted by time-dependent univariate piecewise linear polynomials other fit...

Purpose – This paper seeks to present an optimization‐based approach design acceptance sampling plans by variables for controlling non‐conforming proportions in lots of items. Simple and double with s known unknown are addressed. Normal approximation distributions proposed Wallis employed handle unknown. The stands on the minimization average number (ASN) taking into account constraints arising from two point conditions operating characteristic (OC) curve. resulting optimization problems...