Simulation/optimization of production and logistics flows

Our goal is to offer to decision making managers, thanks to our competencies and a long-time experience in the domain of production management as well as in simulation/optimization techniques, the customized solutions meeting their needs.

Production flow simulation/optimization to improve the  enterprise functioning at strategic level

The simulation technique consists in reproduction of properties and behavior of a complex system such as a shop, a factory, a multi-site enterprise, in a computer running a software called simulation model. Once the model is implemented, we can use it to study the behavior of your system in various supposed scenarios without compromising the real installation. This allows one to dramatically reduce the risk of unfavorable technical or financial consequences of your project.

Thus, a simulation study includes the development and validation of the simulation model of existing (or future) system and then running this model many times changing system properties values and putting the system in different contexts. While running the model, detailed key performance indicators of the enterprise are observed, allowing us to find better (or the best) configuration and thus to improve its current or future operation.

The advantages of a simulation project:

• Comprehensive understanding of solutions and alternatives
• Comparative analysis of conceivable solutions, quantitative evaluation of ideas
• Validation of solutions prior to engage important investments
• Validation of transitional phases in business process re-engineering
• Consequences prediction, risk reduction and mitigation
• Visual dynamic presentation of your project of enterprise transformation to colleagues, clients, suppliers…

Examples of simulation model using in production management

• Analysis of financial feasibility of project of new plant construction or of important investments in production facilities to evaluate in justified manner key performance indicators of the system envisaged
• In-depth review of internal logistic, material handling system, production flow organization (kanban, work-in-process storage zones, etc.) to improve reactivity and to reduce work-in-process inventory
• Evaluation of performances of new production management rules, personnel affectation and management, algorithms of flow control, …

Scheduling/control to improve operational level performances

Enterprise Resource Planning (ERP) systems are conceived to integrate overall business process management of an enterprise. However, the ERP systems suffer from numerous limitations concerning execution (operational) level of goods or services fabrication process. Enterprise models used in ERP systems are not detailed enough on the execution level and don’t reflect the random nature of perturbing events. That’s why an ERP is not capable to schedule and to control (including reaction to unpredicted events) the execution of operations by stuff and machine tools.

To bridge the gap, complementary modules are to be developed. Since one enterprise does not resemble one other at lower than business process level (ERP level), these modules to be efficient should for sure be customized for a given enterprise. They should be connected to ERP to know the production plan and inventories and to PLCs and detectors to access the current state of the system under management, possibly through a supervision software (SCADA), a manufacturing execution system (MES) or a warehouse management system (WMS).

Recently, numerous new techniques of data acquisition about current system state appeared in the frame of Industry 4.0 concept (IoT, detectors, Big Data, …), allowing much better visibility and thus opening the door for better process management.

Here again, simulation models connected to actual state of manufacturing execution process (on-line simulation) as well as optimization software can dramatically contribute to reactive management of the operations execution.

Examples of customized applications of operation execution management

• production scheduling and re-scheduling following unpredicted events
• dynamic resources allocation
• routing, picking, shipping, cutting optimization