Framework and deployment of a cloud-based advanced planning and scheduling system. (August 2021) - Wang, Li-Chih; Chen, Chun-Chih; Liu, Jen-Li; Chu, Pei-Chun
Highlights: This paper presented a cloud-based and advanced planning and scheduling (C-APS) system framework, it can be used as a reference for system developers to develop a cloud-based and object-oriented APS with simulation-based scheduling engine that can be applied in practice. This paper proposed the service structure and approach of deploying the C-APS system in the public cloud infrastructure, platform, and service provider (e.g., AWS TM ) and hybrid cloud platforms. Readers may reference this approach to deploy a server-based enterprise information application system to a cloud-based system. This paper presented the package diagram to collect the necessary data for building the case company's virtual factory model required by the C-APS system; this feature can significantly improve modeling efficiency and data stability. Besides, the C-APS's objected-oriented, simulation-based scheduling engine has the characteristics of quickly expanding and adjusting to the virtual plant model. The C-APS system's application in a leading automotive part assembly company's printed circuit board production scheduling shows that the input planning data model is easy to maintain; the scheduling quality is high; the computing time is short and acceptable for practical application. Abstract: Many small and medium-sized manufacturing enterprises (SMEs) have already implemented enterprise resource planning (ERP) and manufacturing execution system (MES) and began to start the journey of cloud manufacturing; however, the high cost of hardware and software investment, implementation, and maintenance usually hinder SMEs from adopting an advanced planning and scheduling (APS) system. This paper aims to develop a cloud-based APS (C-APS) system framework, the service structure, and approach of deploying the C-APS system in a public cloud infrastructure platform and service provider or hybrid cloud platform. The package diagram is proposed for building the C-APS system's virtual factory model to improve modeling efficiency and data stability. The C-APS system is a cloud-based and object-oriented software; its simulation-based scheduling engine can generate the significant production and operations schedule, and has the characteristics of on-demand self-service, quickly expanding and adjusting to the virtual plant model. The C-APS system's application in a leading automotive part assembly company's printed circuit board production scheduling shows that the input planning data model is easy to maintain. The scheduling quality is high; the computing time is short and acceptable for practical application.