Autostore Warehouse in Simio
Project
This project showcases the Autostore type warehouse. By analyzing key components and their interactions, the initiative aims to improve overall performance, boost productivity, and enhance operational efficiency.
Solution
We have developed a state-of-the-art simulation model using Simio to accurately replicate warehouse operations. This dynamic model provides detailed visualizations of trolley movements and all associated processes, including picking, digging, moving and dropping.
Features
- Antideadlock logic: in case the cars are too near they use the anti deadlock logic not to block each other and move safely to the destination
- Integration with Warehouse Management System (WMS): Seamless data integration regarding pallet management, picking, and deliveries. The model animates these processes to reflect real-world behaviors effectively.
- Experimentation and Optimization: Facilitates scenario analysis and testing to uncover the most efficient assembly configurations and workflows, enabling data-driven decisions.
- Advanced Visualization: the warehouse operations well visualized in the 3d simulation software Simio.
This project provides an immersive and dynamic visualization of the autostore, bridging the gap between design and performance analysis. It empowers stakeholders with actionable insights, minimizes inefficiencies, and optimizes built-in processes, fostering smarter, data-driven decision-making.
Automated Warehouse Simulation by SimulateFirst
Project
This project showcases an innovative automated warehouse system featuring storage positions, lifts, and conveyors. By analyzing key components and their interactions, the initiative aims to improve overall performance, boost productivity, and enhance operational efficiency.
Solution
A state-of-the-art simulation model developed with Visual Components to accurately replicate warehouse operations. This dynamic model provides detailed visualizations of pallet movements and all associated processes, including the actions of lifts and shuttles.
Features
- Integration with Warehouse Management System (WMS): Seamless data integration regarding pallet management, picking, and deliveries. The model animates these processes to reflect real-world behaviors effectively.
- Experimentation and Optimization: Facilitates scenario analysis and testing to uncover the most efficient assembly configurations and workflows, enabling data-driven decisions.
- Advanced Visualization: Captures the intricate kinematics of robots and handling systems, delivering a realistic representation of warehouse operations.
This project provides an immersive and dynamic visualization of an automated warehouse, bridging the gap between design and performance analysis. It empowers stakeholders with actionable insights, minimizes inefficiencies, and optimizes assembly processes, fostering smarter, data-driven decision-making.
Dynamic Simulation and Optimization of Automated Wall Assembly Systems
Project
This project focuses on revolutionizing wall assembly production lines. It addresses the limitations of traditional static CAD models. These models fail to give meaningful insights into the dynamic behavior of complex systems. By examining key elements and their interactions, the project aims to enhance performance, productivity, and operational efficiency.
Solution
A cutting-edge simulation model is developed using Visual Components to replicate the operations within the work cell. This dynamic model offers precise visualizations of part movements and robotic processes, including those performed by Cartesian and six-axis robots.
Features
- Experimentation and Optimization: Enables scenario analysis and testing to identify the most efficient assembly configurations and workflows.
- Advanced Visualization: Captures the kinematics of robots and handling systems in detail, offering a realistic representation of operations.
- Seamless CAD Integration: Imports static CAD designs, segments them into components, and animates them to demonstrate real-world behavior.
- Enhanced Laser Cutting Simulation: Models are virtually cut, split, and handled to improve simulation accuracy and reliability.
This project offers an immersive, dynamic visualization of automated workcell operations, bridging the gap between design and performance analysis. It empowers stakeholders with actionable insights, reduces inefficiencies, and optimizes assembly processes, ensuring smarter, data-driven decision-making.
Enhancing Automated Assembly Performance with Simulation: A Dynamic Visualization Approach
Project
This project addresses the challenges of understanding and optimizing assembly efficiency within an automated work cell. Traditional static CAD models couldn’t offer enough insights into the system’s dynamic behavior. By analyzing key elements and their interactions, this project aims to improve overall performance and productivity.
Solution
A sophisticated simulation model is developed using Visual Components to emulate the operations within the work cell. The model provides a precise and dynamic visualization of part movements. It also shows robotic operations, including Cartesian and six-axis robots. The model illustrates the handling of rejected parts, which are dropped onto a conveyor for removal.
Features
- Advanced Visualization: Captures the kinematics of robots and handling systems in detail, offering a realistic representation of operations.
- Seamless CAD Integration: Imports static CAD designs, segments them into components, and animates them to show real-world behavior.
- Realistic Physical Movements: Models part interactions, including drops, collisions, and falls, to enhance the accuracy and reliability of simulations.
- Experimentation and Optimization: Enables scenario analysis and testing to find the most efficient assembly configurations and workflows.
This project delivers an advanced visualization of automated work cell operations. It bridges the gap between static design and dynamic performance analysis. By providing stakeholders with an immersive understanding of the platform, it facilitates informed decision-making, minimizes inefficiencies, and optimizes assembly processes.
Increasing Overhead Trolleys Efficiency with Simulation: A Scalable Approach
Project
This project focuses on analyzing the logistics efficiency of a production site. The aim is to enhance efficiency by evaluating critical factors. These factors include trolley speed, the number of trolleys, and daily working hours. These elements are studied to determine their impact on overall performance and productivity.
Solution
A robust simulation model is developed using Simio to replicate the track-based operations within the production site. The model accurately shows the movement of trolleys transporting products between the warehouse and production facilities. By simulating different scenarios, it identifies optimal configurations of trolley resources to improve logistics and productivity.
Features
- Modular and Scalable Design: The simulation incorporates modular track systems and rotors for flexibility and scalability.
- Data-Driven Insights: Empirical data underpins the model to simulate and test a wide array of operational configurations.
- Comprehensive Performance Evaluation: The model assesses productivity based on variables like trolley count, operational speeds, and task volume.
- Experimentation and Optimization: Supports scenario analysis and experiments to pinpoint the most efficient logistics solutions.
This project delivers actionable insights into optimizing overhead transport within a production site. The scalable simulation approach enables stakeholders to make data-informed decisions, ultimately improving resource allocation, reducing downtime, and enhancing overall efficiency.
Optimizing Forklift Operations in a Large Warehouse: A Simulation Approach
Project
We aim to find the optimal number of forklifts. This will help efficiently manage operations in a large warehouse. We use simulation modeling. It helps us analyze the impact of various factors. These include forklift speed, number of forklifts, and daily working hours on warehouse performance.
Solution
A simulation model is developed using Simio to represent forklift operations in the warehouse. Forklifts are tasked with receiving picking orders, transporting pallets to the picking area, and bringing boxes to storage. The simulation model tests and evaluates different scenarios. It provides valuable insights into how changes in forklift resources affect overall efficiency. It also impacts productivity.
Features
- Scalable simulation with multiple forklifts and over 20,000 boxes
- Data-driven modeling to test various operational configurations
- Performance evaluation based on the number of forklifts, operational speed, and daily working hours
- Support for experiments and scenario analysis to optimize warehouse logistics
This project provides a detailed solution to improve forklift fleet management in large warehouses. It ensures greatest efficiency with minimal resource waste.
Optimizing AGV Fleet Efficiency: A Simulation-Driven Approach
Project
This project explores the optimal number of Automated Guided Vehicles (AGVs). The goal is to maximize throughput and operational efficiency in a production site. Through simulation modeling, we analyze the impact of key factors. These factors include AGV fleet size, operational speed, and daily working hours. They all affect productivity.
Solution
A detailed simulation model is developed using Simio to emulate AGV operations within the production site. Products progress through various facilities before being transported by AGVs to later destinations. The simulation evaluates multiple scenarios, offering actionable insights into how adjustments to AGV resources influence overall efficiency and throughput.
Features
- Shared Network Optimization: Models AGV transportation on a common network to show real-world constraints.
- Comprehensive Performance Metrics: Evaluates productivity based on fleet size, speed, and operational hours.
- Scenario Analysis and Experimentation: Enables testing of various configurations to find the most effective logistics strategies.
- Resource Efficiency: Provides solutions for achieving optimal efficiency with minimal resource wastage.
This project delivers a scalable and data-driven approach to improving AGV fleet management in production environments. By leveraging simulation, it ensures enhanced decision-making, reduced operational bottlenecks, and increased throughput with optimized resource utilization.
Autonomous Mobile Robot (AMR) Simulation
Project
The project focuses on simulating AMR operations in a production environment. AMRs have three main tasks. They get full boxes at two loading positions. They deliver these boxes to 12 machines. Finally, they transport empty boxes back to an outbound conveyor.
Solution
A detailed simulation model was developed using Simio. AMRs are modeled as dynamic entities that navigate within a defined area. Simulation experiments allow evaluation of performance based on the number of AMRs, providing insights for improvement.
Features
- Dynamic Positioning: AMRs autonomously select the next available position within the area.
- Collision Avoidance: Built-in logic ensures safe navigation without interference.
- Deadlock Resolution: Algorithms prevent workflow bottlenecks and keep operations smooth.
- Extensible Logic: The AMR behavior can be customized and expanded to meet specific operational needs.
This simulation approach enables comprehensive analysis, offering valuable data to improve AMR performance and enhance production efficiency.
Simulation for Inbound and Outbound Logistics
Project
The project focuses on optimizing logistics operations, including bufferdimensioning, conveyor adjustments, and portal operations for improvedefficiency.
Solution
A simulation model was developed using Simio, integrating dailyoperational data to show real-time conditions. Machines and processesare dynamically adjusted based on current orders, ensuring a realisticand flexible simulation environment.
Features
- Dynamic Buffer Management: Experimentation to improve buffer dimensions for varying operational scenario.
- Animated Portal Operations: Visualization of portals restackingboxes onto pallets for better process understanding.
- Comprehensive Pallet Logistics: Management of both full and empty pallets to streamline material flow.
- Real-Time Adjustments: Machines adapt dynamically to current orders for precise performance evaluation.
This simulation provides actionable insights into logistics operations,enabling data-driven decisions to enhance throughput and efficiency.
Production Order Scheduling in a Simulation Model
Project
This project tackles periodic order rescheduling in the face of productionvariability. It ensures optimal resource utilization. It also maintains workflow efficiency.
Solution
A simulation model was developed using Simio, designed to manageorders with complex and highly constrained routing requirements. The model incorporates constraint programming (CP) algorithms to maximize the efficiency of production facilities. These algorithms dynamically adjust scheduling based on real-time conditions.
Features
- Advanced CP Scheduling: A logic block integrates CP algorithms to recalculate and reassign all orders to available resources dynamically.
- Resource Optimization: Ensures efficient allocation of production facilities despite shifting constraints.
- Adaptive Rescheduling: Periodically adjusts orders to accommodate variability, maintaining productivity and reducing delays.
This approach provides a robust framework for managing production schedules, enabling enhanced adaptability and improved operational efficiency.
Simulation of a Complete Production Site
Project
This project focuses on optimizing machine work time to meet the demands of current production orders efficiently.
Solution
A simulation model was developed using Simio, incorporating daily operational data for realistic analysis. The model enables comparison of multiple scenarios through experiments, providing actionable insights with detailed and interactive dashboards.
Features
- Scenario Analysis: Parallel comparison of various production scenarios to evaluate performance metrics, like order delays andresource utilization.
- Interactive Dashboards: Intuitive visual tools for analyzing results, offering a clear view of key data and facilitating informed decision-making.
- Real-Time Data Integration: Daily operational data ensures the model reflects actual production conditions for precise optimization.
This simulation empowers production teams to explore and implement efficient strategies, enhancing overall site performance and reducing downtime.
Simulation of a Commissioning Center
Project
The project aims to find and resolve bottlenecks in a commissioning center. This ensures efficient daily operations. It also ensures optimal resource allocation.
Solution
A simulation model was developed using Simio to support the planning of daily operations. The model allows for proactive determination of the optimal number of employees and forklifts. It bases its calculations on the current picking load. This approach improves efficiency and minimizes delays.
Features
- 3D Visualizations: Incorporates animation objects imported from SketchUp for realistic and engaging simulations.
- Picking List Optimization: Simulates and optimizes the sorting of picking lists to streamline operations.
- Resource Planning: Utilizes experiments to calculate the precise number of employees and forklifts required for the day’s workload.
This simulation provides valuable insights into operational efficiency,enabling dynamic planning and resource optimization tailored to daily demands.
Dynamic Dimensioning of a Warehouse System
Project
This project focuses on verifying the design of a warehouse system. It also involves optimizing the dimensions to guarantee they meet operational requirements. These tasks are essential before construction begins.
Solution
A simulation model was developed using Simio, providing a highly customizable layout to show specific warehouse requirements. The model enables thorough testing of the warehouse’s performance undervarying conditions, ensuring a well-informed design process..
Features
- Scalable Design: Dynamically adjust warehouse dimensions based on pallet input quantities to find the optimal configuration.
- Performance Insights: Analyze utilization rates and stock levels through detailed and interactive charts.
- Pre-Construction Validation: Simulate and evaluate the warehouse’s functionality before construction, reducing risks and enhancing design accuracy..
This simulation ensures a data-driven approach to warehouse design,delivering a robust, efficient system tailored to operational needs.
Simulation of an Automated Storage andRetrieval System (ASRS)
Project
This project optimizes the design and operation of an ASRS. It determines the ideal number of rows and levels. Additionally, it evaluates warehouse loading and unloading strategies.
Solution
A simulation model was created using Simio. It incorporates daily stocklevels. It also uses planned orders for arrivals and deliveries as input data.This ensures the model reflects real-world operational conditions.
Features
- Customizable Framework: Design the ASRS with the desired number of shelves and rows to meet specific storage needs.
- Efficient Aisle Movements: Simulates precise and realistic movements within aisles to evaluate system effi ciency.
- Dynamic Shelf Allocation: Implements adaptive rules to find the optimal shelf for each pallet, enhancing space utilization.
This simulation empowers decision-makers to refine ASRS dimensions and strategies, ensuring a high-performing, efficient warehouse system tailored to operational demands.
Simulation of AGVs in Manufacturing Lines
Project
The project aims to find out the optimal number and usage of Automated Guided Vehicles (AGVs). These vehicles need to efficiently supply assembly lines. The findings will give critical insights for an investment decision.
Solution
A simulation model was developed using Simio to evaluate AGV performance under varying conditions. Simio experiments analyze the impact of AGV numbers and speeds on overall efficiency, ensuring data-driven investment planning.
Features
- 3D Visualization: Utilizes animation objects imported from SketchUp for realistic and engaging simulation visuals.
- Dynamic Task Assignment: Automates AGV task allocation,ensuring efficient operation without manual intervention.
- Comprehensive Workflow Simulation: Models AGVs delivering full boxes to assembly lines, collecting empty boxes, and returning to the loading area.
This simulation provides actionable insights into AGV deployment,ensuring cost-effective and efficient manufacturing line operations.
Optimizing AGV Integration for Scalable ASRS Warehouses
Project
This project focuses on optimizing the operation of Automated Guided Vehicles (AGVs). It works together with an Automated Storage and Retrieval System (ASRS). This occurs in a scalable warehouse environment. The aim is to decide the ideal number, speed, and movement patterns of AGVs to maximize efficiency and throughput.
Solution
A simulation model is developed using Simio, leveraging the SimulateFirst framework to replicate the warehouse’s ASRS layout and processes. The model includes a flexible AGV network. This network enables precise control and analysis of AGV behavior. It ensures seamless coordination with the ASRS..
Features
- AGV Navigation: Simulates AGV movements for loading and unloading at bays.
- Repacking Stations: Models interactions where pallets are retrieved, processed, and returned efficiently.
- Scalable Design: Allows adjustments to the AGV fleet size and operational factors to accommodate varying warehouse demands.
- Performance Metrics: Evaluates key performance indicators like throughput, turnaround time, and system bottlenecks.
This comprehensive simulation aims to guide the design of efficient AGV systems for modern, scalable warehouses.
Streamlining Material Supply with AGV Simulation
Project
This project focuses on ensuring a continuous and efficient material supply to various work areas using Automated Guided Vehicles (AGVs). By simulating AGV movements, the project aims to improve material flow and reduce downtime in manufacturing or warehouse environments.
Solution
A detailed simulation model is developed using Visual Components,replicating the behavior and logic of Omron mobile robots. The model integrates CAD designs and advanced AGV logic to closely resemble real-world operations.
Features
- Realistic AGV Logic: Incorporates Omron AGV behavior for precise simulation.
- Route Optimization: Records and analyzes routes for each AGV to enhance efficiency.
- Container Allocation: Simulates the dynamic allocation of containers from utility stations to work areas.
- Scalable Simulation: Adapts to different layouts and operational requirements for flexible material handling.
This simulation provides a robust framework for evaluating and optimizing AGV-based material supply systems in various industrial settings.
Optimizing Daily Batch Production Through Data-Driven Simulation
Project
This project involves creating a data-driven simulation model to optimize the daily planning of batch production for small automotive parts. The focus is on analyzing and improving the utilization of machining stations,assembly lines, and facility occupancy. It also involves managing pallets and buffers to streamline production processes.
Solution
A 3D simulation model is developed using Simio, providing a detailed analysis of key production factors. The model evaluates buffer capacities, identifies congestion points, reduces waiting times, and improves resource utilization.
Features
- Data-Driven Initialization: Automatically integrates current production data for realistic and dynamic simulations.
- Flexible Task Allocation: Simulates different work cells for specific tasks to improve facility utilization.
- Flow-Based Representation: Shows parts using dynamic flows for precise modeling of production processes.
- Interactive Analyses: Enables real-time exploration of bottlenecks, resource allocation, and throughput.
- Comprehensive Insights: Offers detailed metrics to guide decisions on buffer sizes, facility layouts, and operational strategies.
This simulation tool provides actionable insights for optimizing daily batch production, ensuring efficiency and adaptability in a competitive manufacturing environment.
Cycle Time Optimization and Robot Simulation for Automated Production Lines
Project
This project focuses on optimizing the cycle times of an automated production line. The line handles multiple product variants. These variants have varying processing times. The aim is to enhance efficiency, reduce delays, and maximize resource utilization across the production system.
Solution
A robot simulation model is developed using Simio to analyze and enhance the production flow. The model identifies potential cycle delays caused by improper part sequencing and provides actionable insights to improve overall system performance.
Features
- Robot Simulation: Simulates robotic operations and interactions for precise cycle time evaluation.
- Turn Tables Integration: Models turn tables to enhance material handling and process transitions.
- Cycle Time Analysis: Calculates and optimizes cycle times for each work cell to ensure balanced workflows.
- Data-Driven Sequencing: Utilizes data to decide the optimal sequence of stations, reducing delays and bottlenecks.
- Quick Diagnostics: Enables rapid identification of inefficiencies and their root causes in the production line.
This project provides a robust tool for fine-tuning automated production lines. It ensures they operate at peak efficiency. This project accommodates diverse product variants.
Optimized Production Planning for Lot Size 1 with Integrated Simulation
Project
This project focuses on planning and simulating a production system designed for a lot size of 1. It enables mass customization with individual product configurations. A custom user application manages daily production data. This data is integrated with Simio for advanced simulation and result feedback. This integration ensures seamless dataflow and decision-making.
Solution
A .NET-based user application with Access is developed to manage production data and store it centrally in an SQL Server. Simio connects to this database to import production data. It carries out simulations. Then,it returns results to the application for actionable insights.
Features
- Integrated Database Connectivity: Simio seamlessly integrates with SQL Server for real-time data exchange.
- Custom User Application: A .NET application manages production data, ensuring smooth daily operations.
- Simulation for Lot Size 1: Optimizes production processes tailored to individual products in single-unit batches.
- End-to-End Workflow: Data flows dynamically between the user application and Simio, enabling continuous production planning and monitoring.
- Centralized Data Management: SQL Server provides a robust and scalable platform for storing and analyzing production data.
This system provides a comprehensive solution for achieving efficient,flexible production in a highly customized manufacturing environment.
Interactive Simulation Consulting for Automation System Decisions
Project
This project aims to support decision-makers by demonstrating the quality and feasibility of a proposed automation system through simulation. The flexible simulation model allows for real-time customization during meetings, enabling stakeholders to explore various scenarios and make informed decisions.
Solution
A high-speed simulation model is developed to run experiments, visualize production flows, and analyze key performance indicators (KPIs) within seconds. This approach ensures rapid and effective communication of system performance and potential improvements.
Features
- Interactive Analysis: Conduct real-time adjustments and scenario testing during consultations.
- Rapid Simulation: Generates visualizations and KPI analyses in seconds, ensuring quick insights.
- Engaging Visualization: Helps stakeholders understand production flows and system impacts intuitively.
- Data-Driven Decisions: Provides actionable insights to optimize the proposed automation system.
- Flexibility: Tailored to accommodate changes or modifications dynamically during discussions.
This consulting tool bridges the gap between technical details and strategic decision-making, enabling efficient evaluation and adoption of automation solutions.
Virtual Commissioning of Control Systems with Real-Time Simulation
Project
This project focuses on the early validation of a control system under realistic operational loads. A simulation model replicates production processes. It exchanges requests, replies, and status messages with the controller. This helps evaluate its performance and reliability before physical deployment.
Solution
A real-time simulation model is developed in Simio, enhanced with acustom .NET AddOn for seamless communication with the controller viaTCP/IP. This setup ensures continuous interaction between the model and the controller, enabling comprehensive testing and debugging.
Features
- Real-Time Simulation: Simio operates in synchronization with the controller for realistic validation.
- Seamless Communication: The .NET AddOn facilitates bidirectional message exchange over TCP/IP.
- Dynamic Status Updates: The simulation sends status messages after every production step, mimicking real-world behavior.
- Early Problem Detection: Identifies potential issues in the control logic before physical commissioning.
- Flexible Integration: Adaptable to various controller configurations and production scenarios.
This virtual commissioning solution reduces risks, shortens development cycles, and ensures robust control system performance in live environments.
Comprehensive Plant Simulation for Digital Twin Development
Project
This project involves the creation of a highly flexible simulation model foran entire plant. It encompasses orders, resources, and employees. It also includes warehouses and transportation systems like AGVs and Automated Material Handling Systems (AMHS). The aim is to develop a digital twin to optimize production and logistics processes.
Solution
The model is developed using Enterprise Dynamics (ED). It serves as a digital twin to simulate and analyze the production and logistics system.The design is data-driven and highly parametrized, allowing for detailed customization and scalability. Advanced animation enhances visualization, making complex systems more intuitive for stakeholders.
Features
- Data-Driven Design: Integrates real-time or static data to create a realistic and dynamic plant model.
- Parametrized Flexibility: Highly customizable to adapt to various plant configurations and operational changes.
- Comprehensive Scope: Includes orders, resource allocation,workforce, warehousing, and transport systems (AGVs/AMHS).
- Engaging Visualization: Features high-quality animations for intuitive presentation and analysis.
- Digital Twin Application: Enables in-depth scenario testing,bottleneck analysis, and system improvement.
This simulation solution provides a robust foundation for decision-making and operational improvements in large-scale production and logistics environments.
Optimizing Pick Rate and Throughput with Coordinated Delta Robots
Project
This project aims to increase the pick rate and throughput of a production line. It does this by optimizing the coordination of delta robots tasked with picking biscuits. The goal is to improve efficiency while minimizing the number of robots required, reducing costs and enhancing system performance.
Solution
A simulation model was developed using Visual Components,incorporating dynamic algorithms to allow efficient task distribution among delta robots. The robots communicate in real-time, exchanging messages to coordinate their picking tasks, ensuring no overlap and maximizing throughput.
Features
- Dynamic Task Allocation: Robots dynamically decide which biscuits to pick based on real-time communication.
- Improved Efficiency: Achieves higher pick rates while reducing the number of robots needed.
- Real-Time Coordination: Robots pass messages to avoid conflicts and guarantee smooth operations.
- Visual Simulation: Provides a detailed and realistic simulation of robot interactions and production flow.
- Cost Optimization: Reduces capital and operational expenses by minimizing unnecessary robot deployments.
This simulation demonstrates the potential of coordinated robotics to enhance productivity in high-speed production environments.
Coordinated Multi-Robot Simulation with SCARA,Delta, and 6-Axis Robots
Project
This project involves simulating the interactions and coordination between various types of industrial robots, including SCARA, Delta, and 6-axis robots. The aim is to analyze their functions, compatibility, and performance in a shared workspace, ensuring optimal collaboration and efficiency.
Solution
A simulation model was developed using Visual Components, allowing for realistic visualization of robot functions and interactions. The model supports over 1,000 predefined robot types from various manufacturers.These include Kuka, ABB, Stäubli, Fanuc, Motoman, and Kawasaki. It can be exported as a 3D PDF for enhanced visualization. This feature facilitates stakeholder communication.
Features
- Diverse Robot Integration: Supports a wide range of predefined industrial robots from leading manufacturers.
- Collaborative Simulation: Visualizes and analyzes how SCARA,Delta, and 6-axis robots coordinate tasks in a shared environment.
- Exportable Visuals: Generates 3D PDF exports for easy sharing and presentation.
- Task Transparency: Clearly demonstrates each robot’s functionality and role in the workflow.
- Versatile Applications: Adaptable for testing layouts, improving processes, and training personnel.
This project delivers a powerful tool for evaluating and optimizing multi-robot systems in industrial settings.
Dynamic Validation of Optimized Operation Plans with Simulation
Project
This project combines mathematical process optimization with 3D simulation to create robust and efficient operation plans. The near-optimal process flows generated by optimization algorithms are dynamically tested against potential disturbances in a simulation model.This approach ensures the plans stay resilient and adaptable under real-world conditions.
Solution
A simulation model is developed to integrate and check optimization outputs. This system dynamically simulates disturbances and “what-if”scenarios. This approach allows fine-tuning of algorithms and production plans. These adjustments are made before implementation in real systems. This ensures both efficiency and adaptability in automated workflows.
Features
- Seamless Optimization-Simulation Integration: Combines precise mathematical optimization with realistic 3D simulation for comprehensive process analysis.
- Dynamic Scenario Testing: Simulates disturbances to confirm plans and answer “what-if” questions, ensuring real-world robustness.
- Balanced Objectives: Maintains short time tolerances at stations while increasing throughput by maximizing parts in process.
This project provides a reliable framework for developing and validating operational plans. It minimizes risks and optimizes performance inautomated production systems.
Optimizing Traffic Flow in Freiburg Through Simulation
Project
This project aims to address traffic congestion at specific junctions in Freiburg. It does so by analyzing traffic light cycle times and exploring different redirection routes. The aim is to reduce waiting times and improve overall traffic flow efficiency.
Solution
A detailed simulation model of Freiburg’s traffic network was developed,incorporating relevant traffic volumes, vehicle movements, and signal timings. The model allows for the dynamic adjustment of cycle times and provides rapid feedback on the effects of changes.
Features
- Immediate Impact Analysis: Quickly assesses the effects of changes on waiting times and congestion.
- Dynamic Traffic Light Control: Enables real-time adjustments to cycle times for optimized traffic flow.
- Comprehensive Visualization: Displays traffic lights and vehicle movements for intuitive analysis.
- Integrated Dashboards: Provides clear metrics for evaluating waiting times and flow efficiency.
This simulation tool offers a robust solution for planning traffic management in Freiburg. It improves traffic systems, ensuring smoother and more efficient road use.
Optimizing Train Cycle Times and Stop Operations in Railway Networks
Project
This project aims to find optimal train cycle times to maximize networkutilization based on demand. The project evaluates scenarios withdifferent numbers of trains. It also considers shorter cycle times and safestop operations. This ensures efficient, high-capacity rail transport whilemaintaining safety.
Solution
A simulation model of the railway network is created based on the actual layout. Trains are modeled with detailed passenger capacities, including seating and standing areas. The model allows for flexibility in adjusting thenumber of trains and operational distances to evaluate different scenarios dynamically.
Features
- Dynamic Train Scheduling: Adjusts train numbers and cycle times for optimal utilization.
- Safety Compliance: Ensures no collisions and maintains safe stopping distances at all times.
- Realistic Turnaround Operations: Simulates efficient turnarounds to reduce delays.
- Flexible Passenger Modeling: Incorporates seated and standing capacities for demand-based analysis.
This simulation tool provides valuable insights into improving rail network efficiency, balancing capacity, and safety while meeting fluctuating demand.
Optimizing AGV Coordination in Manufacturing Lines
Project
This project focuses on simulating and optimizing the coordination of Automated Guided Vehicles (AGVs) within a manufacturing line. The aim is to guarantee prompt delivery and pickup of boxes. It also seeks to prevent double order reservations. Additionally, it aims to reduce wasted time and movements.
Solution
A simulation model is developed in Simio to analyze AGV operations. The analysis includes the number of AGVs required and their optimal speeds.Simio Experiments are used to evaluate scenarios, ensuring continuous box availability and efficient task execution without unnecessary delays or movements.
Features
- Dynamic Task Assignment: Automatically assigns AGVs to tasks,ensuring seamless operations.
- Integrated Workflow: AGVs deliver full boxes, pick up empty ones,and move to the loading area in a synchronized manner.
- Detailed Animation: Incorporates SketchUp objects for realistic visualizations of AGV movements.
- Efficiency Analysis: Includes waiting times and optimizes routes to reduce waste.
- Scalable Parameters: Allows flexible adjustments to AGV numbers and speeds for different production scenarios.
This simulation provides a robust framework for improving AGV coordination in manufacturing lines, enhancing productivity and operational efficiency.
Optimizing Automated Work Cells with Multi-Robot Simulation
Project
This project focuses on simulating work cells with multiple robots. The aimis to recognize and resolve errors, deadlocks, collisions, and inefficiencies in automated systems. The goal is to improve process flowand test enhancements before implementation.
Solution
A simulation model is developed using Visual Components, enabling offline programming and collision testing for multiple robots. The model evaluates and optimizes robot sequences to reduce cycle times and guarantee safe, efficient operations..
Features
- Offline Robot Programming: Enables programming and testing of robot tasks without disrupting production.
- Collision Detection: Identifies potential collisions and deadlocks to guarantee safe operation sequences.
- Cycle Time Optimization: Analyzes and reduces tact times to improve throughput and efficiency.
- Error and Process Validation: Detects inefficiencies and validates process improvements early in development.
- Flexible Scenario Testing: Allows for rapid testing of different configurations and workflows..
This simulation tool provides a comprehensive solution for enhancing the performance and reliability of robotic work cells in automated systems.
Optimizing Production Flow with a Digital Twin for Automotive Assembly
Project
This project involves creating a digital twin of the assembly area for a car manufacturer. The purpose is to continuously improve production flow. It also aims to increase throughput. The goal is to find and tackle inefficiencies early in the process, reducing costs and enhancing operational performance
Solution
A digital twin is developed using Simio, incorporating data imports for product requirements, routing, work-in-progress (WIP), and production plans. This tool enables in-depth analysis of key performance indicators(KPIs) and provides actionable insights to balance and streamline production.
Features
- Data Integration: Utilizes relational data structures and imports for seamless updates on product requirements, routing, and WIP.
- Dynamic Model Updates: Automatically updates the simulation model with the latest data at the start of each session.
- KPI Analysis: Tracks and evaluates production metrics to find bottlenecks and optimize flow.
- Visual Insights: Outputs results as Gantt charts and interactive dashboards for intuitive decision-making.
- Continuous Improvement: Supports iterative testing and refinement of production plans for sustained throughput gains.
This digital twin solution offers a robust platform to improve assembly line efficiency. It ensures the car manufacturer meets production targets while minimizing costs.
Integrated Simulation of Assembly Processes with ASRS and Robotics
Project
This project involves simulating a comprehensive assembly system. It includes machining stations, Automated Storage and Retrieval Systems(ASRS), employees, buffers, and robotics. The goal is to illustrate the process steps, evaluate the project environment, and guarantee safe,efficient operations.
Solution
A detailed 3D simulation model is developed using Visual Components. It enables the analysis of critical aspects like danger zones, congestion points, and potential collisions. The model integrates various robotic systems and assembly components for a thorough visualization of workflows.
Features
- Comprehensive System Modeling: Simulates machining stations,ASRS, employees, buffers, and robots to replicate real-world assembly processes.
- Multi-Robot Integration: Supports multiple robot brands,enabling analysis of collaborative and independent tasks.
- Safety and Efficiency Analysis: Identifies danger zones,congestion points, and collision risks for proactive mitigation.
- 3D Visualization: Provides an intuitive representation of assembly workflows and robot interactions.
- Process Optimization: Highlights areas for improvement inthroughput, workflow efficiency, and resource utilization.
This simulation solution delivers a powerful tool for planning, validating,and optimizing assembly systems with ASRS and robotics.
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+49 351 30906020dresden@simulatefirst.comPARTNERS:
SimulateFirst Poland
ul. Powstańców Śląskich 5
PL 53-332 Wrocław
polska@simulatefirst.com
+48 75 6406434
SimulateFirst Germany
Anton-Graff-Str. 24
D-01309 Dresden
dresden@simulatefirst.com
+49 (0) 351 30906020