Course Goal

The course aims to enhance participants' knowledge of data analytics, statistical process control (SPC), data visualisation, and techniques for reducing variation. A key highlight will be an ‘Introduction to Machine Learning Concepts’. By promoting lower operational targets and reducing costs, the course offers significant benefits to companies.

The workshop is needed because the timber industry collects vast data, which can be transformed into valuable information using statistical tools and AI to produce high-quality products. Industries not utilising their data effectively will miss optimising production and may struggle to remain competitive. 

The course is also for Forestry Specialists that analyse spatial data. Techniques related to spatial pattern analysis and spatial regression will be presented to  predict, and understand spatial patterns and relationships in forest ecosystems.

Course Structure

The course is two days with ~ 16 hours of instruction plus the option of a practical mill tour where learning could be best deployed. The concepts will be applied in Excel, JMP, Minitab, and R.

Students will enjoy hands-on exercises such as ‘Deming’s Bead Box’ (demonstrates natural variation of a system); ‘Deming’s Funnel Experiment’ (illustrates inducing variation by over-adjusting a system), and group case studies with real data.

Course History

The 'National Centre for Timber Durability & Design Life' has offered data analytics courses on three occasions in recent years, attracting over 50 industry professionals. The first highly successful course took place in Mt. Gambier, South Australia, in 2019 and we are returning there this year.

Instructor

Timothy Young is a Professor Emeritus in the School of Natural Resources and Interim Director of the ‘Data Science Institute’ at the University of Tennessee (UT). 

See more details about the UT Data Science Institute or Tim Young on LinkedIn.

Contact

If you would like to find out more about upcoming courses and training please contact us. Email your interest and if there is particular training or information you are after for yourself or your team.

Email: FRIAdmin@usc.edu.au