This paper proposes a method to improve the process model estimation based on limited experimental data by making use of abundant production data and to achieve the optimal process adjustment based on the improved process model. The proposed method is called an Estimation-adjustment (EA) method. Furthermore, this paper proves three properties associated with the EA, which guarantee the feasibil...

This paper presents a framework for the optimal design of experiments for medical sensors calibration. A new software program, G-optimal, is developed to demonstrate the optimal design of experiment. This program has been used to find G-optimal design for amperometric enzyme glucose sensor, silicon capacitive absolute pressure sensors and electrochemical oxygen and carbon dioxide partial pressu...

In this paper‎, ‎we model and solve the problem of optimal shaping and placing to put sensors for a 3-D wave equation with constant damping in a bounded open connected subset‎ ‎of 3-dimensional space‎. ‎The place of sensor is modeled by a subdomain‎ ‎of this region of a given measure‎. ‎By using an approach based on the embedding process‎, ‎first‎, ‎the system is formulated in variational form;...

When the number of data used for an identification experiment is small, the data contain transient effects and these effects contribute to the accuracy of the identified model. Consequently, when designing the optimal input signal for an identification experiment in the case of small data set, these transient effects have to be taken into account. In this paper, we present a methodology for opt...

The problem with computer model calibration by tuning the parameters associated models is significant in many engineering and scientific applications. Although several methods have been established to estimate parameters, research focusing on design of remains limited. Therefore, this paper proposes a sequential experiment based D-optimal criterion, which can efficiently tune while improving pr...