9/9/2019 - Descreye Solutions
This is an objective comparison of discrete event simulation software packages as they are in 2019. It is meant to inform decisions on which tool is ideal for a given situation. Additionally, the best discrete event simulation software of 2019 is identified given the ranking system defined.
10/18/2018 - Descreye Solutions
Sizing buffers is a critical component of logistics, factory, and manufacturing production line design. However, the methodologies used to do buffer sizing are often inadequate or incorrectly applied. Many methodologies have assumptions that limit their applicability. Fortunately, buffer sizing simulations are easy to make and provide valuable insight in a short period of time.
2/3/2018 - Descreye Solutions
This is an objective comparison of discrete event simulation software packages. It is meant to inform decisions on which tool is ideal for a given situation. Additionally, the best discrete event simulation software of 2018 is identified given the ranking system defined.
1/14/2018 - Descreye Solutions
Simulation is an important tool in the analysis of supply chains. Simulations can provide more accurate forecasts, provide a better method for safety stock calculations, improve systems within the supply chain, and optimize logistics strategies.
1/12/2018 - Descreye Solutions
Process simulation is the act of getting the mathematical or stochastic outcome of a process with known characteristics. Process simulation can take many forms including mathematical models, monte carlo simulations, discrete-event simulations, or agent-based models.
12/05/2017 - Descreye Solutions
Business intelligence and discrete-event simulation are partners in providing insights into complex business processes and systems. It would probably be correct to say that DES is a subset of BI, but in practice that is rarely the case.
3/17/2017 - Descreye Solutions
Discrete-event simulation software can be an incredibly powerful tool for learning about the dynamic nature of complex systems. However, in many cases it is not the right tool for an analysis. The following are four instances where discrete-event simulation is unlikely to be helpful, but instead could end up being a distraction in achieving the insight that is necessary to inform the decision making process.
10/27/2016 - Descreye Solutions
Most simulation models are created manually, because their goal is to get insight into a specific problem. However, sometimes it becomes necessary to create a discrete-event simulation model programmatically. To create a simulation model automatically there are a few process steps. The image below shows the various steps in model creation that must be defined to programmatically create and run a model.
10/19/2016 - Descreye Solutions
The purpose of this guide is to give a basic overview of discrete-event simulation and model building for people who are new to the topic. While not by any means exhaustive, it gives information on why and how to use discrete-event simulation software to get insight into systems. For more information there are additional links.
10/12/2016 - Descreye Solutions
Discrete event simulation has been around for a long time. Today there are many discrete event simulation software tools that allow people to completely replicate, design, or improve a system. In simulation software like FlexSim there are advanced 3D graphics that make it easy to build, visualize, and validate simulation models. However, even with all these advances simulation still has some growing left to do. The following are some areas where discrete event simulation software must advance in order to reach further into system design and improvement.
10/6/2016 - Descreye Solutions
A lesson on using histogramic distributions to generate random variates for use in a discrete event simulation model. OPS uses a histogramic-6 distribution to convert raw observations to a samplable random number distribution.
10/4/2016 - Descreye Solutions
There are thousands of tools that can be used for process improvement. The tools range from highly analytical tools like MatLab and RStudio to a simple pad of paper and a pencil. The following is a list of tools that are essential to master for anyone that is concerned with process improvement.
9/27/2016 - Descreye Solutions
Value-stream mapping (VSM) is a valuable tool for improving systems. However, many people start using value-stream mapping without first recognizing the inherent limitations in the tool. They then don't see the expected result when they finish the work to decrease non-value added time, or increase resources in a bottleneck step.
9/20/2016 - Descreye Solutions
Creating simulation models can be difficult. Many people have spent hours creating models only to scrap them because they weren't getting any useful insight from them. The following 4 mistakes are common for people when they start creating simulation models. Avoiding them is an important part of becoming an experienced discrete-event simulation modeler.
9/13/2016 - Descreye Solutions
The key to successful process improvement is good data analytics. Data helps to identify problems and predict solutions. While a lot of data can be gleaned from GUIs in various programs, it is inevitable that the GUI won't provide the data as an analyzed solution. That is where these programming languages assist the user in gathering, analyzing, and summarizing the data that is necessary for successful process improvement.
9/6/2016 - Descreye Solutions
At the rate of current progress in technology it is almost impossible to predict the state of a technology 50 years from the present. If we simply look into the past 20 years we can see the past developments in simulation. 20 years ago most simulations were done using a programming language or very rudimentary GUIs. Now simulation packages do full 3d representations of real-life systems and can include all the ancillary processes of the system to increase accuracy and insight.
8/30/2016 - Descreye Solutions
Queueing theory has been used for over 100 years to analyze system dynamics. Queueing theory uses a series of mathematical equations to estimate wait time in queues. It has been an important part of system analysis because it simplifies complex systems into a series of equations. However, the problem remains that with increased system complexity, queueing theory becomes inadequate for estimating the effects of changes on the system.
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