Increased mechanization in lumber mills is resulting in large data capture. This data is not being utilized to improve the profitability of the lumber mill. The main reason for not utilizing this data is lack of staff time to evaluate, analyze and develop action plans. One additional factor is that the complexity of data streams in many manufacturing industries, especially the lumber industry, will elude most data analysts. A technique in use by a number of manufacturing industries to capture the information in their data bases is data mining.
Data mining is actually the application of several statistical methodologies.
These include correlation analysis, artificial neural networks, and data clustering. Lumber mills consist of a number of unit operations and the performance of each of these operations determine the profitability of a mill. However, if care is not taken to make decisions based on overall mill profitability, sub-optimization will occur and profit opportunity will be lost. The data collected from operations can be used to optimize the overall success of the lumber mill. By applying data mining techniques, models of each operational step are developed.