The increasing complexity of industrial production systems is challenging employees on the shop-floor in their daily work. Specific knowledge about manufacturing processes is often not available in explicit form but mainly as tacit knowledge of experienced shop-floor workers. A systematic approach to knowledge externalization and reuse is required to make this operational knowledge available. This paper proposes a method to systematically capture and structure expert knowledge while incorporating knowledge management and social research methods. The proposed method's application and evaluation occur in a continuous manufacturing scenario, externalizing tacit knowledge about coping with manufacturing anomalies. A digital assistance system is designed and prototypically implemented to manage and reuse the externalized knowledge. The early involvement of shop-floor workers in the development phase of the prototype ensures usability and user acceptance of the assistance system. The assistance system is developed as a collaboration supporting artifact in the shop-floor's common information space. To observe the resulting productivity performance improvements in the manufacturing scenario, a KPI-based evaluation of the assistance system is presented. Finally, a discussion about the major contributions of this paper, namely the development of an approach for knowledge externalization and a human-centered design of an assistance system, takes place. To assess the novelty of these approaches, they are contrasted with the state of the art identified in the literature before a final summary of the results is presented.