# Effective Data Utilization in the Context of Industry 4.0 Technology Integration
## 1 Introduction
### Data-Driven Smart Manufacturing  
Smart manufacturing, or smart production, is based on the effective interconnection of smart technologies with manufacturing technologies. Smart manufacturing embodies new paradigms of thinking within manufacturing technologies that are focused on automating production while taking advantage of the data provided by the information technologies of the Fourth Industrial Revolution. The key technologies of the smart manufacturing concept can include the Internet of Things (IoT), Cyber-Physical Systems (CPS), Cloud Computing and Big Data, among others [16; 17]. The utilisation of data has started to play an important role since the beginning of the Fourth Industrial Revolution. Data-driven decisions differentiate modern, intelligent manufacturing from traditional manufacturing in that decisions are made based on facts and data rather than based on theoretical models, opinions, and assumptions [17]. Data from manufacturing processes at the smart manufacturing organization level are obtained by accessing the entire product lifecycle information, from explicit data such as material properties, process temperature and vibration to implicit data, which can include supply chain resources and customer requirements. The premise of a successful product sale is to offer the customer what he both expects and needs. The volume of data that is generated during manufacturing processes in the context of the Fourth Industrial Revolution is growing exponentially [17; 18]. Smart manufacturing aims to leverage the data collected throughout the product lifecycle to achieve positive impacts on all aspects of the manufacturing process and the customers within it [16]. At present, researchers are becoming more aware of the value of data, its collection and analysis and are trying to identify ways to use it effectively within manufacturing processes. Figure 2 represents the current process of acquiring data from manufacturing processes and analysing it for the optimal decision toward the optimization of the manufacturing system. This cycle lays the foundation for a data-driven manufacturing paradigm as opposed to conventional model-based manufacturing [17]. Systematic analysis of manufacturing data has the potential to lead to decisions that can improve the efficiency of smart manufacturing [16]. The main difference between the conventional manufacturing process and the modern/smart manufacturing process can be observed in Figure 3. Conventional manufacturing processes in the context of automation can be seen as model-based manufacturing. Experts gain experience through physical observation. Based on this experience, physical models are created through experimental and numerical methods. Such models have added value but their limitation is the extent of efficiency and accuracy as a consequence of the human factor in the process. Intelligent manufacturing that is data-driven makes full use of all manufacturing processes and their real-time data to achieve system flexibility and autonomy [17]. Figure 2: Data collection process (Own processing [17]). Data have long been regarded as an important part of manufacturing and manufacturing processes that are data-driven [19]. Therefore, it can be concluded that data-driven manufacturing is a necessary prerequisite for smart manufacturing. Data are becoming a key factor for increasing competitiveness and organizations are becoming aware of its great strategic importance in the long term [16]. With the emergence of the Fourth Industrial Revolution, manufacturing systems are being transformed into digital ecosystems. Big Data and Internet of Things (IoT) technologies play an essential role in this transformation. With the advent of this revolution, industrial organizations have entered a new age of 'Big Data', where the volume, velocity and variety of data are growing exponentially.