Automated process planning and dynamic scheduling for smart manufacturing: A systematic literature review

Process planning and scheduling (PPS) are two key functions of Smart Manufacturing (SM) that need to be explored under the influence of Industry 4.0 (I4.0) operationalization. Although these two functions are connected, their objectives usually do not agree. As a result, Process Planning (PP) solutions often cannot cope with dynamic production requirements. Over the years, researchers have realized the potential of SM for the automation of several aspects of manufacturing, leading to the next industrial revolution. This study aims to identify the opportunities and challenges of Automated Process Planning and Scheduling (APPS), paying particular attention to Digital Twin (DT) and Artificial Intelligent (AI) technologies of I4.0. These technologies offer a new paradigm by creating an intelligent digital representation of the physical production system to explore the influence of uncertain events predictively. A systematic literature review methodology is obtained o achieve this goal. The survey is conducted in two stages. In the first stage, a Keyword Co-occurrence Network (KCN) analysis is undertaken to highlight current research trends. In the second stage, an in-depth review is conducted to identify specific applications and limitations. This study contributes towards identifying the most promising research direction within I4.0 for the holistic APPS problems to address shop floor uncertainties and disruptions.