This paper investigates a dual-stage Gough-Stewart platform. The lower platform is responsible for simulating the oscillations of moving vehicles such as cars, ships, and airplanes. The upper platform is connected to devices that require either balance stabilization or motion stabilization according to specific requirements. The dynamic model of the robot system is derived in a general form based on the Lagrange equations of motion with Lagrange multipliers. Using these equations in a compact form, a PD controller with forces compensation in task space is designed for the robot system. Oscillation generation and balance stabilization are computed and simulated using the kinematic and dynamic parameters of two Bosch Rexroth robots. The computation and simulation results demonstrate the dynamic model's accuracy and the controller's effectiveness.

In today's rapidly evolving industrial landscape, efficient predictive maintenance solutions are essential for minimizing downtime and enhancing productivity. This research introduces an adaptive cloud-based model pipeline for predicting the Remaining Useful Life (RUL) of machine components, specifically ball screws. The pipeline integrates local preprocessing, edge computing, and cloud-based adaptive model training, ensuring data privacy and reducing data transmission volumes. The system classifies wear states using various machine learning mod-els and predicts RUL through regression analysis, incorporating uncertainty quantification for robust maintenance scheduling. The experimental setup includes accelerated degradation of ball screws, with data collected via a three-dimensional accelerometer. Feature extraction and data augmentation techniques are employed to enhance prediction accuracy. Random Forest and Gradient Boosting models demonstrate superior performance, with Random Forest selected for its robustness and uncertainty quantification capabilities. Empirical results indicate high prediction accuracy, with Random Forest achieving up to 91% accuracy in Phase 2. This cloud-ready predictive maintenance framework leverages scalable cloud infrastructure for efficient data processing and real-time updates, offering a practical solution for industrial applications. The proposed approach significantly advances the adoption of digital business models within the manufacturing industry, providing a reliable and efficient tool for predictive maintenance.

Thermal deformation is a major source of machining errors in modern machine tools. In addition to optimising the machine structure, correcting the axis position values in the numerical control is a common measure to reduce these errors. Another possibility is to directly influence the temperature field of the machine tool in the process, which requires a complex thermo-elastic modelling approach as well as appropriate thermal actuation and measurement capabilities. This paper presents a strategy for controlling the temperature field based on the eigenmodes of the thermal system. The various aspects of the concept are explained using a finite element model of an exemplary structural component. The basis is the modal analysis of the thermal system, which allows the temperature field to be described by independent discrete states. In addition to the placement of thermal sensors and actuators, this work focuses on the design of a suitable control approach. Transient simulation results are used to clearly demonstrate the performance of this method.

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Single-pass honing is used as a finishing process to meet high demands regarding form and dimensional accuracy of drilled holes.The disadvantages of single-pass honing compared to the conventional long-stroke honing are high process forces and torques as well as an increased risk of chip space clogging of the abrasive stones.Following this, the oscillation-superimposed single-pass honing without cutting fluid has been conducted in this work, which is promising when it comes to the environmentally friendly improvement of machining processes.It was shown that the omitted lubrication and flushing effect of the contact zone between the tool and the workpiece could be compensated with the aid of the superimposed oscillations.The process forces of the dry honing process are up to 37% lower compared to the conventional process, the height of the surface profile Rz decreases by 33% and the form deviations decrease up to 47%.Hence, the new method allows the saving of resources, while improving the work results.

Many potential suppliers state that they are ready to produce components according to specified requirements as they are familiar with the ISO GPS system tools for dimensional and geometrical tolerancing.Regrettably, in many instances, this is not true.This paper discusses a survey developed to assess the geometrical dimensioning and tolerancing skills and results derived from this survey executed among 15 potential suppliers.The investigation aims to preselect potential suppliers and evaluate how much support the suppliers will require while also assessing the risks associated with placing an order with a particular supplier.The survey is based on the online test comprised of 27 closed-end questions used to identify strengths, weaknesses, and knowledge of a candidate supplier's personnel.Five different answers are given for each question.The respondent shall indicate one correct answer.The inquiry is practically oriented.Most of the questions include drawings with indicated selected tolerance as well as drawings of the possible actual parts with exaggerated geometrical deviations.The associated question is whether an actual part is made according to the specification.The main conclusion is that most responders disclose a low level of understanding of the ISO GPS system.Urgent education is needed.

The hollow embossing rolling of thin-walled high precision components like metallic bipolar half plates is characterized by narrow process windows.Here, the knowledge of interaction between forming machine, roll and process is crucial for the process stability and quality of formed bipolar half plates.In this paper, the elastic machine and forming roll behaviour as a major influence parameter is described and analysed on qualitative level and verified by simulation.This investigation involves a review regarding the process sequence, forces for the hollow embossing rolling of metallic bipolar half plates.By varying the load distributions, the elastic deformations of the forming machine and their forming roll are investigated and analysed regarding process influence and potential for process monitoring.

Sawing is often the first work step in the metal cutting production chain. Especially for larger workpieces, bandsawing is used for this purpose. Nevertheless, studies on sawing have led a niche existence in the research landscape for a long time. However, as a result of the optimization of manufacturing processes in terms of economic efficiency, bandsawing is increasingly becoming the focus of research, since there are still saving potentials here. The aim of this paper is to investigate the extent to which the bandsawing process can be influenced by active, low-frequency vibration superimposition in the feed direction. First, analogue tests were carried out and parameter combinations were determined which have a positive influence on the process. Subsequently, these parameter combinations were investigated on a real sawing machine with an excitation unit, analysing the extent to which the results from the analogue tests could be transferred to the real process.

1. MALKIN S., GUO, C., 2007, Thermal Analysis of Grinding, CIRP Annals – Manufacturing Technology, 56/2, 760–782. Google Scholar