The core of the research focuses on analyzing the discharge characteristic of a lithium NMC battery in an autonomous mobile robot, which can be used as a model to predict its future states depending on the amount of missions queued. In the presented practical example, an autonomous mobile robot is used for in-house transportation, where its missions are queued or delegated to other robots in the system depending on the robots’ predicted state of charge. The system with the implemented models has been tested in three scenarios, simulating real-life use cases, and has been examined in the context of the number of missions executed in total. The main finding of the research is that the battery discharge characteristic stays consistent regardless of the mission type or length, making it usable as a model for the predictive monitoring system, which allows for detection of obstruction of the default shortest paths for the programmed missions. The model is used to aid the maintenance department with information on any anomalies detected in the robot’s path or the behavior of the battery, making the transportation process safer and more efficient by alerting the employees to take action or delegate the excessive tasks to other robots.

The commercially available battery management and mission scheduling systems for fleets of autonomous mobile robots use different algorithms to calculate the current state of charge of the robot’s battery. This information alone cannot be used to predict whether it will be possible for a single robot in the fleet to execute all of the scheduled missions. This paper provides insight into how to develop a universal battery discharge model based on key mission parameters, which allows for predicting the battery usage over the course of the scheduled missions and can, in turn, be used to determine which missions to delegate to other robots in the fleet, or if more robots are needed in the fleet to accomplish the production plan. The resulting model is, therefore, necessary for mission scheduling in a flexible production system, including autonomous mobile robot transportation networks.

The stability and repeatability of laser metal deposition is particularly important when processing multiple layers or depositing material on complex component surfaces, and requires the use of process parameter control including the stand-off distance between the laser head and the substrate. The system proposed in this paper for correcting the stand-off parameter is based on a chromatic confocal sensor integrated into a laser head. Then, the spectral signal acquired from the measurement system is processed by using the developed application to compensate for the movement of an additional axis of the kinematic system. This study used an independent verification system based on the digital image correlation method. The validation tests were carried out using the system for correcting the stand-off parameter with different control algorithms and given motion trajectories and substrate materials. The results demonstrate that the developed system can be useful for laser metal deposition.

In the article, the application potential of the dew-point cooling tower (DPCT) in selected energy-intensive applications in temperate climates was analyzed and discussed. The applications selected for analysis are power generation with natural gas turbines and chilled water air conditioning systems. The study is based on a mathematical model derived from a modified ε-NTU model. The model was validated against experimental results and showed satisfactory agreement with the experimental data. DPCT was compared with a typical cooling tower limited by the wet-bulb temperature (wet-bulb cooling tower, WBCT). The simulation results showed that DPCT is able to provide significant energy savings in energy-intensive applications; therefore, its application potential in temperate climates can be considered justified. In the case of gas turbines, DPCT was able to generate 2 to 10 percentage points more capacity than operating on outdoor air and 1.8 to 5 percentage points more than operating with WBCT. In the case of air conditioning systems, the system equipped with DPCT achieved EERs (energy efficiency ratios) higher by 1 to 7.2 compared to dry cooling and by 0.3 to 5.1 compared to systems equipped with WBCT. The annual energy savings obtained by the system with DPCT were 14.7 MWh compared to WBCT and 30 MWh compared to dry cooling.