Manufacturing Planners

Manufacturing Planners

Creating and optimizing build-to-order and lean production manufacturing systems

DELMIA Production System Simulation

Define and Simulate Manufacturing Systems

DELMIA Production Systems Simulation (PSS) lets users perform dynamic evaluation and improvement of manufacturing systems and material flow. It models and simulates the system over multiple cycles—to help make decisions under uncertain conditions.

Using the established process plan, users can define the manufacturing system, which consists of areas for processing, storing, and transferring parts. The flow of parts can be defined from area to area. Once the system is defined, users can simulate it to evaluate its capacity, its utilization, and other performance metrics. They can then evaluate alternative scenarios for product routing and system design.

  • Leveraged manufacturing planning data
  • Early validation of manufacturing process plans and systems
  • Decision-making support
  • Better collaboration between stakeholders
  • Easy adoption by the user community
  • Simulate the manufacturing system
    PSS lets process planners validate the manufacturing system dynamically. Product flow and operation time, as well as scheduled maintenance and random equipment-failure events, are simulated to help users see how they would impact the system’s capacity. Process planners can determine whether changes are needed to meet production demands.
  • Define production system boundaries
    Planners can define where parts will enter (source) and exit (sink) the manufacturing system to determine if the system will deliver its expected throughput. This makes it possible to analyze a multi-cycle production system and evaluate capacity and utilization.
  • Define product routing rules, buffer capacities, and transfer times
    PSS leverages plans authored in either DELMIA Process Planning (PRP) or DELMIA Resource Planning (RPG). The process planner adds routing rules, determines the placement and capacity of buffers, and defines transfer times to refine the definition of the manufacturing system. These steps produce accurate discrete-event simulations.
  • Define product arrival, processing and transferring time distributions
    During actual production, product arrival and operation times vary from one cycle to another. This behavior can be modeled by defining the time as a statistical distribution. Using PSS, planners can account for this variability and uncertainty, which is observed or expected in the physical system, by defining these distributions. Both pull and push manufacturing supply models are supported.
  • View the current state of a system during simulation preview
    During simulation, dynamic 3D animation of products and iconic display of the system make it easy to understand the state of the manufacturing system. The planner can view, in chart form, the number of products, waiting and operating times, time spent in various states, and utilization. The charts are dynamically updated as the simulation progresses.
  • Detect bottlenecks
    Discrete event simulation is an important decision support tool to evaluate changes in manufacturing, distribution or process facilities. The challenge arises when it comes to the integration of simulation as an effective tool to detect manufacturing constraints and to suggest improvement alternatives. PSS makes it easy to understand the behavior of the system and to identify bottlenecks.
  • Analyze performance statistics and generate and publish reports
    PSS lets users apply simulation to define and validate the manufacturing system. Specific performance aspects of the system, such as throughput, utilization, and work in process, are measured and reported. Users can experiment with system parameters and layouts to determine optimal design and operating conditions. The simulation results are available as statistics such as throughput, operating times, waiting times, and time spent by the system in different states. PSS users can compare the performance statistics of different simulations to help select the most suitable system design and operation under given conditions.
  • Multi-Model Simulation
    Operations for multiple product models can be defined on a system. A general system with operations of multiple models executes its operations depending on the inputs available at the upstream systems.
  • Automatic Sources and Sinks
    There is an option to automatically build sources and sinks during simulation based on the system and operational plan. It is dependent on the inputs and outputs, and the supply and demand information defined on the general system.