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In our rapidly globalizing and digitizing world, small and medium-sized manufacturing enterprises (SMEs) face significant challenges that compel them to adopt a co-opetition strategy—a blend of competition and collaboration. Despite their potential benefits, the high failure rates and unmet expectations of co-opetition networks highlight a significant gap in the empirical frameworks for establishing and maintaining these networks. This research seeks to address these gaps by developing a framework that enhances value cocreation in the Portuguese ornamental stone sector, integrating the latest developments in the Industrial Internet of Things (IIoT), Service-Dominant Logic (S-D Logic), and service science. Question: How can a framework integrating IIoT, S-D Logic, and service science enhance value cocreation and manage co-opetition among SMEs in the Portuguese ornamental stone sector? Methods: Theoretical insights and practical applications were synthesized to develop and validate a comprehensive co-opetition framework. This framework was tested through an experimental pilot project in the Portuguese ornamental stone sector, leveraging IIoT. Results: The implementation of the framework demonstrated significant operational efficiency, including enhanced performance, reduced production variance, and better resource utilization, indicating that integrating IIoT within co-opetition networks can effectively support SMEs. Conclusions: This study confirms the transformative impact of embedding IIoT in co-opetition networks, offering a replicable and scalable framework for other sectors. This framework addresses the empirical gap and aligns with broader socio-economic goals, setting the stage for further research into its applicability and potential across diverse industrial environments. [ABSTRACT FROM AUTHOR]

The complexity of Fuel Cell (FC) systems demands a profound and sustained understanding of the various phenomena occurring inside of it. Thus far, FCs, especially Proton Exchange Membrane Fuel Cells (PEMFCs), have been recognized as being among the most promising technologies for reducing Green House Gas (GHG) emissions because they can convert the chemical energy bonded to hydrogen and oxygen into electricity and heat. However, their efficiency remains limited. To enhance their efficiency, two distinct factors are suggested. First, the quality of materials plays a significant role in the development of more robust and efficient FCs. Second, the ability to identify, mitigate, and reduce the occurrence of faults through the use of robust control algorithms is crucial. Therefore, more focused on the second point, this paper compiles, distinguishes, and analyzes several publications from the past 25 years related to faults and their diagnostic techniques in FCs. Furthermore, the paper presents various schemes outlining different symptoms, their causes, and corresponding fault algorithms. [ABSTRACT FROM AUTHOR]

This paper investigates an optimal model-free control design for a synchronous reluctance motor (Syn-RM) with unknown nonlinear dynamic functions, parameter variations, and disturbances. The idea is to combine a predictive control with a time-delay estimation technique (TDE) in order to successfully deal with the system's uncertainties and make the Syn-RM control scheme easy to implement in real-time. This model-free control strategy comprises two cascade control loops namely outer and inner loops. The outer loop is designed for the mechanical part of Syn-RM to ensure the convergence of the speed dynamics by using a proportional-integral controller while the inner loop is developed to control the uncertain dynamics of currents via an optimal robust controller. In the proposed current loop, the predictive control is enhanced by the inclusion of ultra-local model theory where dynamic functions and disturbances are estimated by instantaneous input-output measurements of the Syn-RM using the TDE approach. Moreover, a particle swarm optimization (PSO) algorithm is also proposed to find the optimal design parameters to improve the dynamic performances of the closed-loop control system. Numerical validation tests of the proposed TDE-based model-free predictive current control (TDE-MFPCC) method are performed in the simulation environment of the Syn-RM system, and the results show the robustness and the effectiveness of the proposed TDE-MFPCC compared to the conventional model-based PCC. [ABSTRACT FROM AUTHOR]

This paper addresses the diagnostics of stator faults in three-phase line-start permanent magnet synchronous motors. More traditional fault diagnostic methodologies are unable to properly diagnose stator inter-turn short-circuit faults in three-phase motors under unbalanced supply voltage conditions, since both conditions impact the fault indicators used for inter-turn short-circuit fault diagnostics in a similar way. In this paper, the relation between the symmetrical components of the three-phase quantities and the harmonic components of the Extended Park's Vector Approach (EPVA) is established. It is proved that the negative component and the EPVA harmonic component at a frequency twice the supply frequency are directly related to the fault occurrence. It is also proved that the healthy motor negative impedance is constant and not load-dependent. Based on this, the negative impedance/admittance is indirectly analyzed, through the combined use of the Extended Park´s Vector Approach of both voltage and current, and is explored for the fault diagnostics. Experimental results, obtained for different load torques, unbalanced supply voltage values, and fault severity levels, show that inter-turn short-circuit fault diagnostics can be achieved even under unbalanced supply voltage conditions based on the analysis of the motor admittance, at a frequency twice the supply frequency, that is the negative sequence admittance. [ABSTRACT FROM AUTHOR]