The problem of too much power in detecting biases for a real chemical process

Statistical hypothesis testing in a strategic fashion is often used to loca te biased process variables and nodes (interconnecting points) with materia l leaks. Power, which increases with the number of measurements used in a h ypothesis test, represents the ability of the test to correctly conclude th e existence of bias or a leak. As computer technology continues to improve, so does the ability to store large quantities of data. Measurement bias oc curs from miscalibrated instruments and equipment failures. To some degree, most instruments will have some amount of bias at any given time. Thus, wi th huge data sets, statistical hypothesis testing strategies will flag near ly all instruments as being biased, which is not a practical result when on e is only interested in a bias above a certain threshold (i.e., control of power). This work demonstrates the dilemma of too much power and stresses t he control of power by using power functions and a controlled number of mea surements. This study was conducted using real plant data provided by the S hell Development Company. (C) 1998 Elsevier Science Ltd.. All rights reserv ed.