Iterative Improvement of Process Planning Within Individual and Small Batch Production
Present challenges of small batch production are represented by the need to improve time-to-market and the reduction of costs. A promising approach to take up these challenges is the use of highly iterative development processes such as Scrum known from software development. A transfer of these principles to process planning enables the prediction of producibility of customer orders by iteratively learning from manufacturing data of similar jobs from the past. Based on the required data structures described in this paper, work plans for new orders can be generated automatically. The potential of the approach is validated by an industrial example.
KeywordsComputer automated process planning (CAPP) Production planning Producibility prediction
The authors would like to thank the German Research Foundation DFG for the kind support within the Cluster of Excellence “Integrative Production Technology for High-Wage Countries”.