Contemporary production environments are undergoing dynamic transformation driven by ongoing digitalization and the implementation of Industry 4.0 technologies, as well as the concepts of Industry 5.0. The integration of Industrial Internet of Things (IIoT) systems with traditional Lean Manufacturing (LM) approaches opens new opportunities for real-time process monitoring and analysis. This paper presents a concept of supporting Lean analysis through the application of IIoT technologies in a digitally integrated production environment where a human collaborates with collaborative robots, including a mobile robot. The research was conducted in a laboratory setting that reflects real manufacturing conditions. The system architecture and its components are described, along with the methods for acquiring process data and analysing them using selected Lean tools. The aim of this paper is to demonstrate the potential of digital technologies in supporting waste identification and opportunities for continuous improvement in line with Lean principles. Motion tracking using the OptiTrack Motive system were applied to monitor the movements of the human operator and the mobile robot. A digital twin of the production system was developed, along with MIR maps, heat maps, and spaghetti charts to enable spatial and temporal visualization of flow and the identification of wastes. The collected data was analysed, and instances of waste were identified. The goal of this study is to illustrate how digital technologies can enhance the identification of improvement areas within production processes aligned with the Lean philosophy.