What is the Talumis simulation approach to your problem
Manufacturing, distribution and information systems are getting more and more complex. In most cases the interaction between parts of the system is not visible and certainly not easy quantify. In order to optimize these systems you must understand the dynamics of the system.
The TALUMIS approach to optimize is to focus on the dynamic interaction between parts of the system. We call this approach the “Queuing & Bottleneck analyses”. Every system, whether it is business processes, manufacturing or distribution logistics, has a dynamic behavior over time that cannot be described with averages. In general the bottleneck will shift over time, so the solution is not straightforward to obtain.
The “Queuing & Bottleneck analyses”consist of the following steps to optimize a system:
• describe the behavior of system parts or processes
• analyze the relations between the parts or processes of the total system
• retrieve relevant process data (process times, arrival rates, failure rates etc.)
• create a dynamic model of the complete system
• analyze the behavior of the total model
• create optimization scenarios based on the gathered insight
• quantify the scenarios to obtain the optimal solution
The key issue in the “Queuing & Bottleneck analyses”is to obtain results over time. To visualize and understand the results we mainly use queuing graphs, Gantt charts and utilization pies. We also support the analyses by visualizing what happens in reality; either in full 3D animation or in schematic results. The insight gathered from these results is 90% of solving the problem.
In some cases customers want to perform the analysis of a specific simulation model themselves. It might also be the case that a simulation model is used for operational planning analysis. In such cases we can provide a working model environment. The model will be controlled by simple parameter and database use alone. This enables users to work with a model without in-depth knowledge of the model or the simulation package it has been built in.
The following steps can be distinguished in a model-building project
1. Define the concept model (the blue-print of a model)
2. Model building (the translation of the concept in a computer model)
3. Verifying and validating (extensive testing)
The defining and testing phases are done in close relationship with the customer to ensure that the customer’s expectations are met in detail.
Flexsim® is object oriented and customizable. This allows defining and creating re-usable objects that can be combined into a new branch- or company specific library. If customers use simulation in a specific environment and cannot work satisfactory with the standard simulation package library we can create a library with special functionality for them.
The advantages of a company- or branch-specific library are the following:
1. It will take less time to create models (up to 200 times faster).
2. No simulation specialist is needed to create the models.
3. Automation of model building is possible
1. Define the overall concept
2. Design the individual objects
3. Building phase
4. Verifying and validating (extensive testing)
Apart from the actual building phase, each step in the project is conducted in close relationship with the customer. We build our applications using an agile approach, which means that we build piece for piece and discuss with the client the functionality of every piece before we deliver it.
We use modern tools like UML, Visual Studio, C++ & C#
If you need a simulation model for operational use, or if you have personnel that have to work with the software, but are not a simulation specialist, you need a complete application.
An application can include:
1. Easy user interface
2. Automatic model generation
3. Help file
4. Data interfaces
5. Specialized libraries
If you want to know more about how an simulation application can make your work easier, please contact us for more details.
We are specialized in analyzing and improving complex and dynamic systems. Every system that has a multitude of interactions and complex time- dependencies (like production sites, sorting systems, etc…) is suitable for improvement by using simulation.
Our project approach consists of the following steps:
1. preliminary investigation (data analysis, interviews)
2. create simulation models
3. analyze simulation results
4. define new scenario’s (designs, control rules,…)
5. report and present results
Steps 2,3, and 4 in the project are iterative: with every step you get better insight and better results. The projects are always conducted in close relationship with the customer in order to ensure results that can be implemented.