As a preliminary, in the first half of the session, background of some process factors which can cause problems will be reviewed. Thin film growth properties such as nucleation and percolation/coalescence are reviewed along with conductivity in metallic films. Examples of thin film growth with columns and/or dendrites will be shown. The process factors which may cause stress and delamination will be presented. The importance of the quality of the vacuum and the control of process temperature and particle energy and flux level will be demonstrated.

Stability and reproducibility are critical to any production process. We want to get the same product today as we did yesterday and get the same result tomorrow. Setting control parameters optimally is one key to these results, but often found to be done less desirably in practice. This is addressed first for thickness and temperature control before more complex things. Design of Experiments Methodology (DOE) will then be addressed with history, principles, and examples.

Vacuum coating processes typically have many variables which influence the properties of the results. Although there may be dozens of variables which have some influence on the results, it is frequently possible to determine which three or four variables are most influential and ignore the rest as being only noise factors. It is desirable to find the optimal values for each influential variable where the results of the overall process meet the best compromise between all of the process goals.

One general methodology to accomplish this efficiently evolved approximately one century ago in the agricultural industry for developing new strains of plants and animals. The experimental/evolutional cycle times for these developments are typically long. Therefore, it is highly desirable to minimize the number of experiments needed, and to maximize the amount of data acquired from those experiments. This is generally referred to as DOE.

This course will show how the set up and carry out a DOE for various simple and complex example processes. The user should be able to become well acquainted with using DOE to debug ailing processes and/or optimize new processes.