Factors affecting the optimal performance of a high-yield pulping operation

Process models based on data from close to one hundred pilot scale pulping runs are used to investigate strategies for operating a chemimechanical pulp mill. Optimal values for a total of 55 process and pulp quality variables have been calculated by applying a genetic algorithm search to a fuzzy model of the overall system. This model consists of over 90 distinct empirical relationships. Results indicate that pulp quality is maintained at minimal fibre and energy costs when the chemical pretreatment is conducted at moderately low temperature using a high SO₂ concentration producing both high sulphonation and high yield simultaneously. Subsequent refining should involve applying at least 65% of the total energy in the primary stage. The pulp quality obtained is comparable to that of a CTMP pulp but with the added benefit of higher freeness.