# Transformation towards a Smart Maintenance Factory: The Case of a Vessel Maintenance Depot
## 2 Literature Review  
This study reviewed previous studies and categorized them into a practical application and research extension from ship building phase to ship servicing phase. Research of the building phase could be divided into smart manufacturing for the production process, smart management by information, and smart maintenance for 5M + 1E (Man, Machine, Material, Method, Measurement, and Environment), which supports production, as shown Figure 2.  
Among numerous studies conducted in each area, the concept, the recent direction, and research on the implementation will mainly be analyzed. Smart manufacturing is a term coined by several agencies such as the Department of Energy (DoE) and the National Institute of Standards and Technology (NIST) in the United States. It highlights the use of information and communication technology (ICT) and advanced data analytics to improve manufacturing operations on the shop floor [4; 5], factory [6], and supply chain [7; 8]. Smart manufacturing incorporates various technologies, including cyber-physical production systems (CPPS), IoT, robotics/automation, big data analytics, and cloud computing to realize a data-driven, connected supply network [9]. Intelligent manufacturing has often been used synonymously with smart manufacturing. Technologies and enabling factors associated with smart manufacturing were reviewed to compare the differences between smart manufacturing and intelligent manufacturing [4; 10; 11]. Studies on the features and availability of smart manufacturing and intelligent related technologies were carried out [12]. Compared to smart manufacturing, intelligent manufacturing focuses more on the technological aspect and less on the organizational aspect. The opportunities and organizational issues to be considered during smart transformation were analyzed for SMEs [13]. A smart manufacturing performance measurement system was introduced based on exploratory and empirical research [14]. According to these studies, a guide for investment in smart manufacturing was presented to ensure the validity of investment. This study used a top-down approach to introduce the specific implementation scheme from top-level planning for industrial practice in smart manufacturing [15]. By referring to the studies of smart maintenance in the build phase, the applicability and implications for the service phase were examined. We analyzed the latest research on a smart maintenance concept, the changing trend of the existing IT system, recent intensive predictive maintenance studies, and maintenance architecture. Smart maintenance was  
Figure 2: Research on smart factory and expansion. defined as based on four main components through expert interviews and preliminary research on manufacturing plants. The four main elements are data-driven decision-making, human capital resources, internal integration, and external integration [16]  
The Enterprise Resource Planning (ERP) system, which manages materials, budget, and planning, and the Manufacturing Execution System (MES), which manages field data, are the two representative factory management systems to support production. When a traditional factory is transformed into a smart factory, the existing ERP and MES systems would be advanced by applying cloud technology, big data-based data diagnostic, and AI technology. The existing information management systems of smart factory processes require more flexibility and a larger volume of data, which needs to connect to related systems, to analyze, and to visualize the activities inside the organization [14; 17; 18]. The introduction of AI systems that support decision making by making knowledge of the production process between each system and data collected from various smart devices is spreading [15; 19]. In addition to academic research, the technology trends suggested by the operators in the maintenance industry were analyzed and reflected in this study.