# Analysis and Visualization of Production Bottlenecks as Part of a Digital Twin in Industrial IoT
## 1 Introduction  
Over the past years, the areas of more efficient production, smart manufacturing and Internet of Things (IoT) have been emerging faster and faster. The well known term IoT describes a vast array of entities with sensing and actuating capabilities that collect, analyze and share data across other entities, programs and platforms and influence the state of other entities [1]. A common definition of industrial IoT is proposed by [PERSON] et al. [2]: \"Internet of Things is a network of physical objects that are digitally connected to sense, monitor and interact within a company and between the company and its supply chain enabling agility, visibility, tracking and information sharing to facilitate timely planning, control and coordination of the supply chain processes\". Integration of IoT in manufacturing is known as Industrial IoT (IIoT). In the scope of IIoT, the application of digital twins (DTs) is receiving enormous attention. Many researchers consider DTs as the most promising current trend in the scope of product development, production design and operations management [3, 4]. By means of the application of DTs, engineers in product development may benefit from the vast amount of information gathered in production processes and in product operation [5]. The main elements of DTs are integrated multi-physics, multi-scale, deterministic and probabilistic simulations of a complex technical system; they use the best available analytical models in combination with continuously updated sensor readings to mirror the state of its corresponding physical twin [4]. Meanwhile, a general consensus can be observed that a DT consists of three parts: physical product or system, virtual representation and connected data that tie these products or systems together [4]. [PERSON] et al. [6] list three key characteristics of DTs:* DTs are dynamic virtual representations of real technical systems;
* DTs are connected to the real technical system over the entire life-cycle;
* Data are exchanged bidirectionally between DTs and the real technical system. The main characteristics of DTs are summarized in Figure 1.  
Whereas the first characteristic is obvious, the second requires closer examination. A life-cycle of a product and its production system is shown in Figure 2.  
Both the development cycle of the product itself and of the production system are shown in form of a V-model, which is the common process description model in model-based systems engineering (MBSE) and is, for instance, proposed in the VDI guideline 2206 [7; 8; 9]. This process continues with the production operation and leads to product delivery, product operation and product recycling; this also highlights the potential and necessity of a circular economy. A large amount of research covers the production operation stage and international standards such as the ISO 23247 [10] are already established. Other areas of the product and production life-cycle are not as intensively researched, but they may be very important and are thus also depicted in Figure 2. It is important to note that this kind of holistic view on the product life-cycle is necessary to explore all connection possibilities between a DT and the real technical system (product and production system). It is important to note that early application possibilities of DTs already cover the development of the functional and logical architecture of a product. Engineers need to define the main functions of the new product and are required to deal with various kinds of data (e.g., customer satisfaction surveys, product sales and product competitiveness analyses, etc.) [4]. The amount of data exchanged between the real system and the DT is both huge and scattered. By means of applying a DT that integrates all kinds of data in the  
Figure 1: Characteristics of Digital Twins. Figure 2: Life-cycle of a product and its production system. physical space of the product, the engineers can gain an understanding of possible product improvements [11].