The main concept of the authors is to place Reinforcement Learning (RL) into various fields manufacturing. As one first implementations, RL for Statistical Process Control (SPC) in production introduced paper; it a promising approach owing its adaptability and continuous ability perform. widely used Q-Table method was applied get more stable, predictable, easy overview results. Therefore, quant...

Complex processes in modern manufacturing and business environments can generate hundreds and even thousands of process measurements that vary over time. Early detection of process instability is critical for avoiding costly failures and minimizing risk. When the process measurements are correlated, multivariate statistical process monitoring methods are appropriate. Three new procedures in SAS...

Statistical process control charts have been widely used for monitoring the quality characteristics of manufacturing processes. Analysis of unnatural patterns is an important aspect of control charting. The occurrence of unnatural patterns implies that a process is influenced by assignable causes, and corrective actions should be taken. In practice, there are many situations in which the simult...

A system-theoretic basis for process control is developed using statistical mechanics as our point of departure. Specifically we show that a thermodynamic system can be discussed within the framework passive systems theory. Using Boltzmann's definition entropy S = kB ln(Ω) and assuming distribution states uniformly distributed close to equilibrium manifold demonstrate existence Lyapunov functio...