Festo (Germany)

Efficient Fault Diagnosis and Correction (FDC) is crucial for maintaining high availability in manufacturing systems. This paper presents a novel ontology-driven approach for creating Bayesian Networks (BNs) to support decision-making in FDC. An ontology is developed to represent fault knowledge from domain-specific data sources, including Failure Mode, Effects, and Criticality Analysis (FMECA) data. This ontology is used as a template for creating the BN structure. The probability parameters of the BN are identified heuristically via FMECA criticality information, deterministic relationships, and expert knowledge. A case-based evaluation using an assembly line for solenoid valves demonstrates the BN’s accurate FDC prediction performance.

This paper demonstrates the critical role of the Asset Administration Shell (AAS) as a standardized framework for data exchange within the industrial automation domain, particularly considering the discrete manufacturing roots of automation projects. To address the lack of integration and collaboration in the supply chain of automation projects, we propose a digitally assisted and efficient solution using the Factory-X project as a case study. This approach connects various tools from manufacturers and integrates them into the toolchains used by system integrators, mechanical engineers, and operators. We demonstrate how the proposed method significantly enhances productivity and the solution-finding process in automation engineering by facilitating the exchange and integration of automation component information between customers and suppliers through AAS.

with details of the nature of the infringement. We will investigate the claim and if justified, we will take the appropriate steps.

Traditional post-secondary education models are designed for students looking to enter the skilled labour market rather than up-skilling or re-skilling the existing labour market. Micro-credentials, which are short-duration courses available outside of credited degree programs, are a promising mechanism for post-secondary institutions to engage in these continuing education opportunities. In this paper, we present a micro-credential program that is complementary to the existing engineering degree program while also relevant and accessible to industry. The program contributes to a larger micro-credential movement within the province of British Columbia and provides a model for other institutions looking to enter and collaborate within the micro-credential ecosystem.

Eye-in-hand camera calibration is an essential step in robotic vision systems. Traditional methods perform the calibration via geometry computation methods where the calibration points are acquired by moving the robot arm while capturing images of a static object (often a checkerboard) of known geometry. Our work aims to explore deep reinforcement learning (DRL) techniques for solving common calibration optimization problems. Inspired by the actor-critic mechanism of DRL, we propose a novel approach to perform eye-in-hand camera calibration on the robot arm. Numerical and real-world experiments prove the feasibility of the proposed method as such here we show the potential of the reinforcement learning method to solve the camera calibration problem.

Zusammenfassung Die physikalischen Eigenschaften pneumatischer Antriebe ermöglichen den Bau von sicheren, leichten und intuitiv bedienbaren Robotern, deren Regelung jedoch herausfordernd ist. Gründe dafür sind die Dynamik der Pneumatik und nichtlineare Reibung mit Unsicherheiten, die ohne abtriebsseitige Momentensensorik unbekannt ist. In dieser Arbeit wird die nichtlineare modellbasierte Trajektorienfolgeregelung eines Roboters mit sechs pneumatischen Drehgelenken vorgestellt. Sie umfasst die Mechanik und Pneumatik sowie, im Gegensatz zum Stand der Technik, deren Verkopplung in einem zentralen Regler. Ausgehend vom dynamischen Modell des Gesamtsystems wird der Regler mittels Feedback-Linearisierung, einem Sonderfall der differentiellen Flachheit, hergeleitet. Die Regelung wird experimentell validiert und anhand der Messungen werden praktische Auswirkungen ihrer Struktur aufgezeigt.

Die Veröffentlichung der NE 177 - und damit des Security-Konzepts der NAMUR Open Architecture (NOA) – liegt nun über ein Jahr zurück. Grund genug, auf dem Markt befindliche Lösungen im Hinblick auf ihre Sicherheit zu untersuchen. Dazu wurden beispielhaft drei verschiedene Umsetzungen des NOA-Security-Konzepts in der IDEA-Anlage in Frankfurt Höchst installiert und einem professionellen Penetrationstest unterzogen. In diesem Artikel geht es neben einer Rekapitulation des NOA-Security-Konzeptes um eben diese Beispielimplementierungen sowie das Vorgehen und die Ergebnisse der Sicherheitstests.

Purpose This study aims to investigate the suitability of a multi-step prototyping strategy for producing pneumatic rotary vane actuators (RVAs) for the development of lightweight robots and actuation systems. Design/methodology/approach RVAs typically have cast aluminum housings and injection-molded seals that consist of hard thermoplastic cores and soft elastomeric overmolds. Using a combination of additive manufacturing (AM), computer numerical control (CNC) machining and elastomer molding, a conventionally manufactured standard RVA was replicated. The standard housing design was modified, and polymeric replicas were obtained by selective laser sintering (SLS) or PolyJet (PJ) printing and subsequent CNC milling. Using laser-sintered molds, actuator seals were replicated by overmolding laser-sintered polyamide cores with silicone (SIL) and polyurethane (PU) elastomers. The replica RVAs were subjected to a series of leakage, friction and durability experiments. Findings The AM-based prototyping strategy described is suitable for producing functional and reliable RVAs for research and product development. In a representative durability experiment, the RVAs in this study endured between 40,000 and 1,000,000 load cycles. Frictional torques were around 0.5 Nm, which is 10% of the theoretical torque at 6 bar and comparable to that of the standard RVA. Models and parameters are provided for describing the velocity-dependent frictional torque. Leakage experiments at 10,000 load cycles and 6 bar differential pressure showed that PJ housings exhibit lower leakage values (6.8 L/min) than laser-sintered housings (15.2 L/min), and PU seals exhibit lower values (8.0 l/min) than SIL seals (14.0 L/min). Combining PU seals with PJ housings led to an initial leakage of 0.4 L/min, which increased to only 1.2 L/min after 10,000 load cycles. Overall, the PU material used was more difficult to process but also more abrasion- and tear-resistant than the SIL elastomer. Research limitations/implications More work is needed to understand individual cause–effect relationships between specific design features and system behavior. Originality/value To date, pneumatic RVAs have been manufactured by large-scale production technologies. The absence of suitable prototyping strategies has limited the available range to fixed sizes and has thus complicated the use of RVAs in research and product development. This paper proves that functional pneumatic RVAs can be produced by using more accessible manufacturing technologies and provides the tools for prototyping of application-specific RVAs.