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A control chart is a widely used Six Sigma DMAIC process measure and control phase tool. The purpose of this paper is to contribute to the body of knowledge on applying statistical process control (SPC) methods in a pulp mill production organization and the special issues that need to be considered in this context.

The method for obtaining the results was action research, where the researcher actively participated in implementing changes in organization. Procedures to detect and further handle the deviations in a pulp mill organization were created and implemented. A cause and effect diagram used in finding causes and storing the accumulated knowledge was modified to make it applicable to this environment.

Factors for successful SPC implementation were found to be in line with earlier findings in other industries. SPC can act as a means of organizational learning in the pulp and paper industry. Specific problems in the pulp and paper industry concerning the use of SPC were the autocorrelation of data, excessive measurement variation, and limited process knowledge. The effectiveness of SPC in a pulp mill was shown both in the decreasing amount of deviations and in the positive opinions of the employees.

Findings are generated from a single case, so general applicability is limited.

This case study can be used as a benchmark by other practitioners in the industry.

This article provides new knowledge in the context of implementing SPC in a pulp and paper manufacturing organization.