# Enabling Technologies for Operator 4.0: A Survey
## 1 Introduction  
The continuous innovations of Cyber-Physical Systems (CPS), the Internet of Things (IoT), the Internet of Services (IoS), robotics, big data, cloud and cognitive computing and augmented reality (AR) result in significant change in production systems [1; 2]. As these technologies revolutionize industrial production, the high-tech strategy of the German government launched to promote the computerization of manufacturing was named as the fourth industrial revolution (Industry 4.0). China developed its own initiative. Made-in-China 2025 is a strategic plan announced in 2015 to increase competitiveness in cutting-edge industries including the manufacturing sector [3; 4; 5]. The approach of China is also based on the most modern IT technologies [6] that are not only used to improve the efficiency of the production, but also to share manufacturing capacity and support cooperation [7]. The U.S. has introduced \"reindustrialization\" policies to reinvigorate its manufacturing industry. By releasing the \"New Robot Strategy,\" Japan is attempting to accelerate the development of cooperative robots and unmanned plants to revolutionize the robot industry, cope with the aggravation of Japanese social and economic issues and enhance international competitiveness. The \"New Industrial France\", the \"high-value manufacturing\" strategy of the U.K. and the \"advanced innovators' strategy\" of South Korea have similar CPS-based focus points [8]. The common goal of these developments is to integrate the supply chain. Industry 4.0 and additive manufacturing, when combined, can help enable the creation of products that are first-to-market and fully customized. Thanks to the benefits of additive manufacturing, not only the consumer can find more customized products and services, but also the manufacturer has a chance to create more efficient and scalable production flow [9]. All in all, these novel manufacturing technologies appear to herald a future in which value chains are shorter, more collaborative and offer significant sustainability benefits. Organizations should be prepared for the introduction of Industry 4.0-based complex production systems. Recently developed maturity or readiness models are mainly technology focused [10; 11] andassess the Industry 4.0 maturity of industrial enterprises in the domain of discrete manufacturing [12]. Thanks to the fast and flexible communications between CPSs, smart sensors and actuators, real-time and self-controlled operations can be realized [6; 13]. The new smart IoT devices have the potential to design mobile machines that replace human minds [14]. Researchers at Oxford University estimated that approximately 47% of all U.S. employment will be at a high risk of computerization by the early 2030s [15]. A survey conducted by PricewaterhouseCoopers (PwC) found that 37% of employees were worried about the possibility of redundancy due to automation [15; 16]. Although the increase in the degree of automation reduces costs and improves productivity [17], human operators are still essential elements of manufacturing systems [18; 19]. The increasing degree of automation also does not necessarily lead to enhanced operator performance [20]. Handling human factors is a challenging problem concerning both cellular manufacturing [21] and human-robot interaction [22]. For example, smart factories have to take into consideration operators who are aging or apprentices by using advanced technologies to help people to integrate into the modern manufacturing workforce [23]. Industry 4.0 (especially IoT devices and CPS) allows new types of interactions between operators and machines [24]. These interactions will generate a new intelligent workforce and have significant effects on the nature of work. The integration of workers into an Industry 4.0 system consisting of different skills, educational levels and cultural backgrounds is a significant challenge. The new concept of Operator 4.0 was created for the integrated analysis of these challenges.