Formal DEVS modelling and simulation of a Flow-Shop relocation method without interrupting the production

International audienceThis paper presents an organisational method to keep the production going during the removal of a flow-shop. Assume a flow-shop system is to be moved on a new site and its production has to continue, our method can be applied to follow requests for the removal period. The method works as follows: we segment the removals in groups of machines and move them ones after the others. This method can be successfully executed provided that a prime condition is met: envisaging sufficient stocks’ plug between each group. The role of the latter stocks is to ensure operations’ production continuity between the old and the new site, when the non-operational group is being removed. Removal is then renewed until the whole line is moved and is operational on the new site. To validate this approach, we have used simulation and developed a model of the flow-shop according to coupled DEVS formalism. Our model enables to segment a production line. As a consequence, we can simulate the sequential displacement of machines’ groups towards the new site. Among the solutions suggested, those starting with the final group (finished products) and while finishing with the first group are much more effective. In this paper, we present and discuss some simulation results of an industrial case study. The results demonstrate the compared effectiveness of various strategies of removal, and make possible for the industrialist to envisage a good estimated project management

A modular hybrid simulation framework for complex manufacturing system design

For complex manufacturing systems, the current hybrid Agent-Based Modelling and Discrete Event Simulation (ABM–DES) frameworks are limited to component and system levels of representation and present a degree of static complexity to study optimal resource planning. To address these limitations, a modular hybrid simulation framework for complex manufacturing system design is presented. A manufacturing system with highly regulated and manual handling processes, composed of multiple repeating modules, is considered. In this framework, the concept of modular hybrid ABM–DES technique is introduced to demonstrate a novel simulation method using a dynamic system of parallel multi-agent discrete events. In this context, to create a modular model, the stochastic finite dynamical system is extended to allow the description of discrete event states inside the agent for manufacturing repeating modules (meso level). Moreover, dynamic complexity regarding uncertain processing time and resources is considered. This framework guides the user step-by-step through the system design and modular hybrid model. A real case study in the cell and gene therapy industry is conducted to test the validity of the framework. The simulation results are compared against the data from the studied case; excellent agreement with 1.038% error margin is found in terms of the company performance. The optimal resource planning and the uncertainty of the processing time for manufacturing phases (exo level), in the presence of dynamic complexity is calculated

A State-of-the-art Integrated Transportation Simulation Platform

Nowadays, universities and companies have a huge need for simulation and modelling methodologies. In the particular case of traffic and transportation, making physical modifications to the real traffic networks could be highly expensive, dependent on political decisions and could be highly disruptive to the environment. However, while studying a specific domain or problem, analysing a problem through simulation may not be trivial and may need several simulation tools, hence raising interoperability issues. To overcome these problems, we propose an agent-directed transportation simulation platform, through the cloud, by means of services. We intend to use the IEEE standard HLA (High Level Architecture) for simulators interoperability and agents for controlling and coordination. Our motivations are to allow multiresolution analysis of complex domains, to allow experts to collaborate on the analysis of a common problem and to allow co-simulation and synergy of different application domains. This paper will start by presenting some preliminary background concepts to help better understand the scope of this work. After that, the results of a literature review is shown. Finally, the general architecture of a transportation simulation platform is proposed

Discrete Event Modeling and Simulation for IoT Efficient Design Combining WComp and DEVSimPy Framework

International audienceOne of today's challenges in the framework of ubiquitous computing concerns the design of ambient systems including sensors, smart-phones, interconnected objects, computers, etc. The major difficulty is to propose a compositional adaptation which aims to integrate new features that were not foreseen in the design, remove or exchange entities that are no longer available in a given context. In order to provide help to overcome this difficulty, a new approach based on the definition of strategies validated using discrete-event simulation is proposed. Such strategies make it possible to take into account conflicts and compositional adaptation of components in ambient systems. These are defined and validate using a discrete-event formalism to be integrated into a prototyping and dynamic execution environment for ambient intelligence applications. The proposed solution allows the designers of ambient systems to define the optimum matching of all components to each other. One pedagogical example is presented (switch-lamp system) as a proof of the proposed approach

PROSIS: An isoarchic structure for HMS control

International audienceThis paper presents a holonic and isoarchic approach to the Flexible Manufacturing System (FMS) control. This approach is based on a flat holonic form, where each holon is a model for each entity of the FMS, with a unifying level of communication between holons. After description of this model, called PROSIS, the interaction protocol and decision rules are presented. The objective is to increase the FMS productivity and flexibility, particularly on responsiveness aspects. This responsiveness is achieved through decentralized generation of the production tasks. The reactive behaviour of the FMS control is illustrated by the example of a flexible turning cell, upon occurrence of a failure or of an urgent batch order, and the resulting Gantt charts are shown

A Modeling and Analysis Framework To Support Monitoring, Assessment, and Control of Manufacturing Systems Using Hybrid Models

The manufacturing industry has constantly been challenged to improve productivity, adapt to continuous changes in demand, and reduce cost. The need for a competitive advantage has motivated research for new modeling and control strategies able to support reconfiguration considering the coupling between different aspects of plant floor operations. However, models of manufacturing systems usually capture the process flow and machine capabilities while neglecting the machine dynamics. The disjoint analysis of system-level interactions and machine-level dynamics limits the effectiveness of performance assessment and control strategies. This dissertation addresses the enhancement of productivity and adaptability of manufacturing systems by monitoring and controlling both the behavior of independent machines and their interactions. A novel control framework is introduced to support performance monitoring and decision making using real-time simulation, anomaly detection, and multi-objective optimization. The intellectual merit of this dissertation lies in (1) the development a mathematical framework to create hybrid models of both machines and systems capable of running in real-time, (2) the algorithms to improve anomaly detection and diagnosis using context-sensitive adaptive threshold limits combined with context-specific classification models, and (3) the construction of a simulation-based optimization strategy to support decision making considering the inherent trade-offs between productivity, quality, reliability, and energy usage. The result is a framework that transforms the state-of-the-art of manufacturing by enabling real-time performance monitoring, assessment, and control of plant floor operations. The control strategy aims to improve the productivity and sustainability of manufacturing systems using multi-objective optimization. The outcomes of this dissertation were implemented in an experimental testbed. Results demonstrate the potential to support maintenance actions, productivity analysis, and decision making in manufacturing systems. Furthermore, the proposed framework lays the foundation for a seamless integration of real systems and virtual models. The broader impact of this dissertation is the advancement of manufacturing science that is crucial to support economic growth. The implementation of the framework proposed in this dissertation can result in higher productivity, lower downtime, and energy savings. Although the project focuses on discrete manufacturing with a flow shop configuration, the control framework, modeling strategy, and optimization approach can be translated to job shop configurations or batch processes. Moreover, the algorithms and infrastructure implemented in the testbed at the University of Michigan can be integrated into automation and control products for wide availability.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147657/1/migsae_1.pd

Process software simulation model of Lean-Kanban Approach

Software process simulation is important for reducing errors, helping analysis of the risks and for improving software quality. In recent years, the Lean-Kanban approach has been widely applied in software practice including software development and maintenance. The Lean-Kanban approach minimizes the Work-In-Progress (WIP), which is the number of items that are worked on by the team at any given time. It has been demonstrated that such approach can help to improve software maintenance and development processes in industrial environments. The goal of the simulation model itself is to increase the understanding and to support decisions for planning such kind of projects. Considering the threats to validity of the study, the accuracy and reliability of the simulation model could be shown and the simulation model implementation allows for deriving hypothesis on the impact of distribution on parameters such as throughput. In this thesis, we describe our simulation studies, which show that the Lean-Kanban approach can indeed help to reduce the average time needed to complete maintenance or development issues. This simulation model can simulate existing maintenance and development processes that does not use a WIP limit, as well as a maintenance and development processes that adopt a WIP limit. We performed some case studies using real data collected from different projects. The results confirmthat the WIP-limited process as advocated by the Lean- Kanban approach could be useful to increase the efficiency of software maintenance and development, as reported in previous industrial practices

Process software simulation model of Lean-Kanban Approach

Software process simulation is important for reducing errors, helping analysis of the risks and for improving software quality. In recent years, the Lean-Kanban approach has been widely applied in software practice including software development and maintenance. The Lean-Kanban approach minimizes the Work-In-Progress (WIP), which is the number of items that are worked on by the team at any given time. It has been demonstrated that such approach can help to improve software maintenance and development processes in industrial environments. The goal of the simulation model itself is to increase the understanding and to support decisions for planning such kind of projects. Considering the threats to validity of the study, the accuracy and reliability of the simulation model could be shown and the simulation model implementation allows for deriving hypothesis on the impact of distribution on parameters such as throughput. In this thesis, we describe our simulation studies, which show that the Lean-Kanban approach can indeed help to reduce the average time needed to complete maintenance or development issues. This simulation model can simulate existing maintenance and development processes that does not use a WIP limit, as well as a maintenance and development processes that adopt a WIP limit. We performed some case studies using real data collected from different projects. The results confirmthat the WIP-limited process as advocated by the Lean- Kanban approach could be useful to increase the efficiency of software maintenance and development, as reported in previous industrial practices