ASSESSMENT OF THE POSSIBILITY OF USING BAYESIAN NETS AND PETRI NETS IN THE PROCESS OF SELECTING ADDITIVE MANUFACTURING TECHNOLOGY IN A MANUFACTURING COMPANY

The changes caused by Industry 4.0 determine the decisions taken by manufacturing companies. Their activities are aimed at adapting processes and products to dynamic market requirements. Additive manufacturing technologies (AM) are the answer to the needs of enterprises. The implementation of AM technology brings many benefits, although for most 3D printing techniques it is also relatively expensive. Therefore, the implementation process should be preceded by an appropriate analysis, in order, finally, to assess the solution. This article presents the concept of using the Bayesian network when planning the implementation of AM technology. The use of the presented model allows the level of the success of the implementation of selected AM technology, to be estimated under given environmental conditions

Modeling and control of operator functional state in a unified framework of fuzzy inference petri nets

Background and objective: In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Methods: Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Results: Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). Conclusion: The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller

A new paradigm for uncertain knowledge representation by Plausible Petri nets

This paper presents a new model for Petri nets (PNs) which combines PN principles with the foundations of information theory for uncertain knowledge representation. The resulting framework has been named Plausible Petri nets (PPNs). The main feature of PPNs resides in their efficiency to jointly consider the evolution of a discrete event system together with uncertain information about the system state using states of information. The paper overviews relevant concepts of information theory and uncertainty representation, and presents an algebraic method to formally consider the evolution of uncertain state variables within the PN dynamics. To illustrate some of the real-world challenges relating to uncertainty that can be handled using a PPN, an example of an expert system is provided, demonstrating how condition monitoring data and expert opinion can be modelled

Esquema metodológico para el control del sistema de tráfico vehicular con atributos de cooperación, flexibilidad y autonomía, usando redes de Petri Coloreadas Difusas Adaptativas

Para el modelado de un sistema de tráfico vehicular controlado por semaforización, se preestablecen, a través de un experto, varios parámetros: geometría, tiempos óptimos para el cambio semafórico y características físicas para obtener finalmente un controlador a la medida de cada intersección. Puesto que estos parámetros son fijos, y el cambio en el flujo vehicular es constante, el embotellamiento se hace inminente en una u ambas vías de la intersección. Debido a esto, se han generado investigaciones en controles que aprenden y adaptan su comportamiento dependiendo de la demanda, pero no consideran el tiempo de espera de los usuarios mientras los controles actúan; ni una metodología de manera gráfica que pueda modelar parámetros para diferentes geometrías de manera modular. Esta tesis establece un método aplicado para modelar el sistema de tráfico vehicular, como un sistema de eventos discretos, por medio de las Redes de Petri Continuas y controlado por una Red de Petri Coloreada Difusa Adaptativa, que le da características de flexibilidad de programación, dada su estructura modular; cooperación entre vías de la intersección; y autonomía de las vías, sin importar la geometría y aprendizaje, por medio de la implementación de un modelo Mamdani, basado en un Sistema Adaptativo de Inferencia Neuro-Difuso (M-ANFIS) con conjuntos gaussianos. Este nuevo enfoque entrega resultados de estabilidad de flujo vehicular, considerando el tiempo de espera para todas las vías de la intersección, comparada con un sistema tradicional controlado por parámetros, y obteniendo aumentos de flujo del 58% en la vía más congestionada con solo dos intervenciones del controladorIn order to model a traffic system that is controlled by traffic lights, several parameters are predefined with the help of an expert, such as geometry, optimal timing of traffic light switching and physical characteristics to obtain a controller adapted to each crossroads. Due to the fact that these parameters are fixed and that the flow of traffic changes constantly, traffic jams are imminent in one or both roads of the intersectionMagister en Automatización y Contro

Enterprise Resource Planning Implementation Strategies in Small- and Medium-sized Manufacturing Enterprises

The difficulty SME leaders of manufacturing firms experience in the executing of enterprise resource planning (ERP) systems threatens the longevity of innovative change within firms seeking to adopt ERP systems. Grounded in the diffusion of innovation theory, the purpose of this multiple case study was to examine critical success factors used to successfully implement ERP systems. The participants were four ERP business leaders of small to medium size manufacturing firms based on the east and west coasts of the United States. Data were collected using semistructured online interviews and a review of company documents. Through thematic analysis, five themes were identified: company culture and business process strategy; diffusion of innovation theory and digital transformation strategies in ERP; planning, managing, and leading strategies; change management strategies in ERP; and methods of implementation lessons learned. A key recommendation is for business leaders to identify causes of resistance to the organization-wide buy-in of new ERP systems. The implications for positive social change include the potential for successful change initiatives that impacts employment and economic health within their respective organizations and surrounding communities