Yves Ducq

Enterprises today face an increasing need for seamless data exchange across various information systems, both internally and with their partners. Addressing challenges in information system and data interoperability is essential. Unfortunately, this issue is often underrecognized by many stakeholders, leading to time wasted on non-value-added tasks and a significant decline in data quality. Our contribution comprises two essential components. Firstly, we introduce and implement extensions to BPMN 2.0 to visually represent data exchanges that encounter interoperability issues as well as those successfully resolved. These extensions also provide performance metrics such as cost, duration, quality, and data availability for tasks affected by these exchanges. By doing so, they gauge the extent of the interoperability challenge and underscore the need to address it for all stakeholders within the enterprise. Secondly, we propose a method derived from FMECA, enabling users to meticulously examine each exchanged piece of data and compute its criticality. This approach empowers the prioritization of corrective actions to enhance data quality, establishing a continuous improvement process that ensures optimal data quality over time.

The world faces nowadays serious health problems caused by the spread of the SARS-CoV-2 (COVID-19). This last was reported by officials in Wuhan City China, in December 2019, and led to a pandemic as of March 2020.Subsequently world economy plunged into an unprecedented paralysis. Despite the threat of COVID-19 on the populations health, many countries, including Algeria, have begun the process of opening up to boost industrial activities. While significant efforts are being put to manage the recovery process of industrial activities within Algerian companies, this work contributes to: the assessment of the pandemic risks and workers resilience mechanism to allow the continuity of companies activities and to improve their response to this pandemic. Keywords- COVID19, human health, occupational risk assessment, resilience, opening up.

Nowadays, industries are implementing heterogeneous systems from different domains, backgrounds, and operating systems. Manufacturing systems are becoming more and more complex, which forces engineers to manage the complexity in several aspects. Technical complexities bring interoperability, risk management, and hazards issues that must be taken into consideration, from the business model design to the technical implementation. To solve the complexities and the incompatibilities between heterogeneous components, several distributed and cosimulation standards and tools can be used for data exchange and interconnection. High-level architecture (HLA) and functional mockup interface (FMI) are the main international standards used for distributed and cosimulation. HLA is mainly used in academic and defense domains while FMI is mostly used in industry. In this article, we propose an HLA/FMI implementation with a connection to an external business process-modeling tool called Papyrus. Papyrus is configured as a master federate that orchestrates the subsimulations based on the above standards. The developed framework is integrated with external heterogeneous components through an FMI interface. This framework is developed with the aim of bringing interoperability to a system used in a power generation company.

In order to control manufacturing systems, managers need risk and performance evaluation methods and simulation tools. However, these simulation techniques must evolve towards being multiperformance, multiactor, and multisimulation tools, and this requires interoperability between those distributed components. This paper presents an integrated platform that brings interoperability to several simulation components. This work expands the process modeling tool Papyrus to allow it to communicate with external components through both distributed simulation and cosimulation standards. The distributed modeling and simulation framework (DMSF) platform takes its environment into consideration in order to evaluate the sustainability of the system while integrating external heterogeneous components. For instance, a DMSF connection with external IoT devices has been implemented. Moreover, the orchestration of different smart manufacturing components and services is achieved through configurable business models. As a result, an automotive industry case study has successfully been tested to demonstrate the sustainability of smart supply chains and manufacturing factories, allowing better connectivity with their real environments.

With the emergence of big data and cloud technologies, companies now evolve in complex IT environments. This situation requires good practices for data process automation to be adopted to ensure system interoperability. Visual computing helps companies to describe and organize the ways in which information systems, devices, and people must interact. It incorporates a number of fields including modeling and simulation (M&S). This paper focused on M&S of data workflow processes that are key steps to bridging the gap between business views and goals on the one side, and operational implementations on the other side. Simulation adds a dynamic view to static modeling; it increases understanding of the behavior of process mechanisms and the identification of weak areas in data flow. Several research projects have been focused on control flow and data flow, but less attention has been paid to resource characteristics. This work is based on the MDSEA approach and the eBPMN language, and proposes an approach that aims to distinguish the types of resources carrying out process tasks. Furthermore, it introduces a new composite resource made from the relationship between a user (human resource) and a task form (IT resource). Moreover, it proposes a resource aggregation based on process performance combination in order to run and display a global performance measurement of a process path.