New Predictive Models for COD from All Stages in Full ECF Bleaching Sequences
This paper proposes new mathematical models for the prediction of chemical oxygen demand (COD) from different stages in full ECF bleaching sequences and discusses several important issues related to model development and interpretation. The effects of different process conditions, like pH, chemical charge, initial Kappa number, carryover, temperature etc., on the formation of COD from the different chlorine dioxide stages (Do, D1, D2) and extraction stages (E, EO, EP, EOP) were studied and corresponding models were developed for softwood and hardwood pulps. The models, based on results obtained from the extensive studies of the kinetics, stoichiometry, and effluent properties of the chlorine dioxide stages and extraction stages in the ECF bleaching of pulp, were tested for accuracy on a vast range of data both from literature and laboratory experiments. The kinetics, stoichiometry and effluent properties have not previously been considered together for optimization and would be of considerable use in bleach plant optimization as well as in process control of different stages. This study will also help in understanding the need for modifications of the conventional conditions in both the chlorine dioxide and the extraction stages to obtain the best mix between a low formation of COD and high bleaching efficiency.
Equipment performance analysis of a Canadian Kraft mill. Part I: Development of new key performance indicators (KPI)
Abstract Most process integration techniques and optimization procedures are based on the implicit assumption that the unit operations and equipment are working efficiently, which is not always the case. Equipment performance analysis by means of key performance indicators is a prerequisite step before undertaking any optimization or improvement measure. However, there are no key performance indicators specifically tailored for the Kraft process equipment, and that take into account both the governing operating conditions and the design parameters. In this paper, new key performance indicators (KPIs) have been developed based on an in depth characterization and dimensional analysis of the Kraft process equipment using the Buckingham Pi (Π) theorem. These KPIs were used to identify process inefficiencies, diagnose causes of inefficiencies and propose remedial actions through a systematic approach. Once adopted, the KPIs proposed could serve to monitor systems performances and allow a tighter process control as they incorporate the design characteristics of the unit operations and their influencing operating conditions.
Traceability strategy for gear-pitch-measuring instruments: development and calibration of a multiball artifact
There is a strong demand to ensure the traceability of gear-measuring instruments (GMIs). We propose a multiball artifact (MBA) for the evaluation of pitch-measuring accuracy. The aim of the MBA is to transfer the minimum uncertainty from a calibrated value at the National Metrology Institute of Japan (NMIJ) to a measured value of GMIs at a shop floor. The MBA is composed of equally spaced high-accuracy balls around an axis. The pitch-measuring accuracy of GMIs is evaluated by measuring the angular pitch deviation of the balls instead of the angular pitch deviation of a gear. We calibrated the angular pitch deviation using a coordinate measuring instrument (CMM) at the NMIJ and adapting a multiple-orientation technique. We proposed a calibration strategy of the angular pitch deviation. The calibration value of the pitch deviation for the MBA at the NMIJ was obtained with a measurement uncertainty (U95) of 0.2 µm. We evaluated the pitch-measuring accuracy of a GMI using the calibrated MBA. Each value of U95 for the cumulative and single pitch deviations for the left and right flanks was less than or equal to 0.5 µm. The small uncertainty was transferred from the NMIJ to the GMI.