# The Human Performance Impact on OEE in the Adoption of New Production Technologies
## 1 Introduction
The ramp-up phase can thus benefit from these technological advancements since they enable a more punctual, immediate and precise performance evaluation, which can be used to effectively drive operations. Moreover, the production systems interconnectivity and the improved man-machine interaction allow key data to be recorded, collected and analyzed to distinguish between machine and human performances. As a consequence of the previous considerations, new research works and practical applications concerning the ramp-up phase should consider opportunities to design comprehensive methods for its effective evaluation. Indeed, the growing usage of digital information and communication technologies opens new opportunities for productivity management in manufacturing companies, with an estimated average increase in productivity of 32% by 2025 due to digitalization [9]. This increase in productivity can be linked to the way digitalization changes the handling of data and information by offering new and extended ways for collecting, transferring, evaluating, and exploiting information, all of which are opportunities that allow increases in effectiveness and efficiency [10]. In addition, as a result of the exploitation of the Industry 4.0-enabling technologies, an evolution of tasks to be performed by operators is taking place. Indeed, the operator should not only perform cooperative work with robots, but also machine-assisted work by meansof CPS systems and advanced man-machine interaction technologies and adaptive automation towards human-automation symbiosis work [11; 12; 13]. Considering this background, the contribution of [PERSON] (2020) [14] discusses the knowledge and skills that operators should have in an Industry 4.0 manufacturing context and provides valuable insights for managing this technological revolution. Following the same path, [PERSON] et al. (2020) [15] propose a human-centric model to evaluate several work configurations where human activities are integrated within cyber-physical systems, along with relevant human-driven performance indicators. The role of the \"Operator 4.0\" is also analysed in the paper of [PERSON] et al. (2020) [16], which discusses its required tasks in relation to maintenance activities. Furthermore, Industry 4.0 provides an improvement in operator training operations through the usage of virtual reality-based tools by reducing the total time spent for practical training [17]. In light of the previous considerations, this paper aims to propose a comprehensive framework to evaluate the initial adoption phase of new production technologies in a digital and interconnected industrial environment. Two \"overall equipment effectiveness\" (OEE) measurement methodologies that distinguish between human performance, process configuration and technical features of the production technology are here introduced and discussed. The framework allows for the evaluation and determination of the conditions under which the transition from the ramp-up phase to the fully operational state is achieved. Hence, this contribution provides valuable insights for the reduction of the overall time required by allowing a stable production output to be achieved. In addition, it can also be adopted to perform an effective and more precise production and workforce capacity planning ahead of the conclusion of the ramp-up period. The paper also reports an application of the proposed framework to a case study related to the introduction of a semi-automatic packaging machine in a primary multinational company in the logistics industry. This allowed the methodology to be tested and validated. Furthermore, a wide literature review on research works concerning the ramp-up phase is provided to determine which relevant criteria can be applied for the assessment of the initial adoption phase of new production technologies.