A Risk Management Framework for Industry 4.0 Environment

In past decades, manufacturing companies have paid considerable attention to using their available resources in the most efficient way satisfy customer demands. This endeavor is supported by many Industry 4.0 methods. One of these called MES (Manufacturing Execution System), which applied for monitoring and controlling recording processing production-related data. article presents a possible method implementation risk-adjusted production schedule data-rich environment. The framework based on datasets multiple workshops, followed statistical analysis, its results are used stochastic network models. outcome simulation implemented scheduling model determine how assign among workshops. After collecting necessary data, reliability indicator-based critical path was case study. Two cases were presented importance inventory cost two different created presented. With objective least cost, postponed latest time possible, means that workshops had more finish previous work first day due small quantity. When not relevant, started each workshop, completed before deadline. These optimal solutions, but alternative solutions can also be performed decision maker results. use modified analysis shed light deficiency production, merit continuous improvement process estimation total project time.