Many research works on soft-sensors have been conducted. Although it is common practice to evaluate the estimation performance of soft-sensors by using industrial process data, few papers have reported long-term application results of process control using soft-sensors in real processes. In the present work, a practical configuration of an inferential control system was developed that integrated a commercial model predictive control (MPC) software and a just-in-time (JIT) soft-sensor. The developed system has adopted locally weighted partial least squares (LW-PLS) to build soft-sensors. LW-PLS is a kind of JIT modeling method that can cope with changes in process characteristics as well as process nonlinearity. Thus, LW-PLS helps engineers to reduce their burden of model maintenance, which has been recognized as the most serious problem in practice. The usefulness of the developed LW-PLS-based soft-sensors and inferential control systems is demonstrated through their successful industrial applications to a cracked gasoline (CGL) fractionator and a purification section for an acetyl plant. Inferential control systems have been used for more than a year at Showa Denko K.K. (SDK) in Japan. The operation cost and environmental burden have been significantly reduced. In the CGL fractionator, for example, about 0.6% of operation cost was cut successfully. In addition, the present work aims to describe challenges, revealed by the long-term applications of JIT soft-sensors: the parameter tuning, the selection of input variables, the definition of similarity in JIT modeling, the management of the database, and the assessment and enhancement of soft-sensor reliability.

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The individual growth of tree diameter at breast height (dbh) is analyzed in an even-aged plantation of Cryptomeria japonica from stand age of 45 to 94 years, to examine how the growth of individual trees has been affected by the changes in spacing resulting from thinning operations. At any age, a significant proportion (0.37-0.46) of the variation in dbh growth during a 5-11-year period was explained by dbh at the beginning of the period, probably due to greater leaf mass of larger trees. Next, either one-sided or two-sided competition was added to the model, by calculating the basal area (BA) of neighboring trees around each tree within a given radius or BA for trees having larger dbh than the focal tree within the radius. After preliminary analyses, a radius of 8 m was selected as the critical range for tree competition. Although both types of competition explained a significant proportion (0.09-0.43) of growth variation, one-sided competition was not significant at ages greater than 54 years. Based on the model at 45 years of age, the initial deviation of growth rate for each tree from the predicted rate was calculated and added to the models as a third variable. This raised the coefficient of determination up to 0.50-0.74. These findings have practical significance for forest plantation management, particularly for controlling the growth of standing trees via thinning, to produce high-quality timber in the future.

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SEKI, T. 1994. Dependency of cone production on tree dimensions in Abies mariesii. Can. J . Bot. 72: 1713-1719.Dependency of cone production on tree dimensions was examined in Abies tnariesii trees that had developed undamaged crowns. The total and maximum numbers of cones produced by a tree for the last 8 years both had allometric relationships with the square of the trunk diameter just below the lowest living branch (DB2). The estimated number of cones produced during the most recent 17 years on the main branch axes showed a positive correlation with the square of the trunk diameter just below the whorl developed in 1979, 1969, or 1959, while no such relationship was found with DB2. The number of cones produced on a branch was constrained by the square of the branch diameter. I suggest that the number of cones is regulated by the amount of dry matter accumulated in the neighboring trunk and branches where the cones are produced rather than the whole amount of dry matter in the tree.