December 2024

This newsletter contains:



• M&S Leadership for 2024-2025
• 2025 IISE Annual Conference and Expo
• Problem Solved: The IISE Podcast on Modeling and Simulation Under the Golden Arches
• Student Spotlight: Kevin Ramos and Karen Vázquez, Tecnologico Nacional of Mexico
• Research Spotlight: Andreas Tolk, Chief Scientist for Complex System Modeling, MITRE
• Industry Spotlight: Amy Brown Greer, Principal Simulation Engineer, MOSIMTEC
• Case Study Spotlight: Planning and scheduling model for nuclear fuel assembly plant, MOSIMTEC LLC
• Call for Entries to the Division Newsletter and Social Media
• Join the M&S Division!

Best regards,

Shima Mohebbi

IISE M&S Division President

While not required, we strongly encourage all presenters to submit a paper for publication so discoveries can be permanently documented. This year, two types of papers will be considered:

• Research Papers (with a limit of six pages) contain methods and results that are significant and have archival value to the industrial and systems engineering community. They will undergo a double-blind peer review process and accepted papers will be copyrighted and indexed in the Conference Proceedings via ProQuest.

• Case Study Papers (two to six pages) describe the application of a method or technology that addresses an important industry-motivated issue. They will be reviewed to ensure that the content focuses on the value and lessons learned for the Industrial and Systems Engineering community. The case study papers should avoid significant marketing material. Accepted manuscripts will be published with access via the IISE website.

Important Deadlines

• Paper submission deadline: February 9, 2025 (Paper submission is optional but encouraged.)
• Notification on full-paper decision: March 9, 2025
• Speaker registration deadline: March 23, 2025
• Paper final revision submission deadline: March 31, 2025

Important Note

Authors/Presenters with approved abstracts must register for the Conference by March 23, 2025. Authors/Presenters that do not register by this date will have their presentations/papers withdrawn from the program and the proceedings. The presenting author must attend and present the paper at the conference.

We look forward to seeing you in Atlanta!

Modeling & Simulation Track Chairs:

Gerda Trollip (gerda@mosimtec.com) MOSIMTEC LLC

Chaitra Gopalappa (chaitrag@umass.edu) University of Massachusetts Amherst

Huaiyang Zhong (hzhong@vt.edu) Virginia Tech

Marzieh Soltanolkottabi (msoltan@newhaven.edu) University of New Haven

Similarly, Karen is pursuing a degree in Industrial and Systems Engineering at the same institution. She is recognized for her skills in public speaking, responsibility, leadership, and teamwork. Recently, she has embarked on personal projects such as teaching Algebra and exploring entrepreneurship. Karen is passionate about learning English and staying updated through LinkedIn. Her primary areas of interest include research, quality control, and Lean Manufacturing.

Could you share more about your experience with the project “SIM-PROLAND: A Proposal for Improvement for the Service Department at Toyota,” which won the discrete-event simulation model contest organized by Promodel?

Karen: The project focused on improving the service area through simulation using PROMODEL software. The original model was executed, and each service station was thoroughly analyzed. As a result of the simulation, vehicle flow in the service area increased by 7.13%, with productivity rising to 98.38%, compared to 91.25% in the original model.

Kevin: The previous simulation identified a delay at the Final Inspection station, revealing a bottleneck. Continuous improvement techniques and administrative tools were then applied, resulting in the proposal of a new and improved model.

How can the model developed in the competition be applied to another field?

Kevin: The model developed during the competition can be applied to various fields through simulation, a vital tool in industry. Simulation enables system modeling and optimization in areas such as manufacturing, logistics, services, and material handling. By simulating different scenarios, it helps identify failures, bottlenecks, and opportunities for improvement within existing systems, facilitating informed decision-making to enhance efficiency and productivity across diverse sectors

Karen: The model can be applied across various fields, with production plants being particularly recommended, such as those in the textile, food, or aerospace industries. For instance, in the aerospace sector, it is possible to simulate the production process of companies manufacturing spacecraft components, from raw material intake to the final product, using PROMODEL software to analyze the process and detect anomalies.

What suggestions do you have for other students to join this expanding field?

Karen: In my view, simulation serves as a form of prevention. I recommend that students and professionals use PROMODEL for their projects, as it can save time and minimize financial losses. Simulation enables the visualization of a small-scale model of a real-world system. With PROMODEL's capabilities, users can experiment with these models and implement necessary changes to optimize system performance. This makes it an essential tool for effective project management and process improvement. Lastly, adapting to technological advancements is crucial, and simulation plays a key role by promoting the use of ICT (Information and Communication Technologies).

Kevin: In student life, integrating software like PROMODEL helps in understanding the complexities and problem-solving challenges of the professional world. As aspiring professionals, PROMODEL provides opportunities to acquire new knowledge and tackle challenges that enhance our development as engineers.

If you'd like to get in touch with Kevin or Karen, you can contact them via LinkedIn: Kevin Ramos Rivera and  Karen Itzel Vázquez Hidalgo.

What do you work on?

As a member of MITRE, I work in the public interest, primarily for federal government entities. One of the most fascinating topics I engage with is using high-performance computing technology to evaluate large-scale agent-based models with hundreds of thousands of simulated entities. A particularly intriguing application of this technology is in artificial societies. In these societies, agents represent individuals with distinct attributes and abilities within a synthetic environment, such as the city they inhabit. In addition to modeling individuals, their social networks are also represented. This approach captures various value and belief systems that influence individuals' perceptions, decision-making, and sense-making. Incorporating these social components allows us to evaluate different policies for addressing challenges, from epidemic events like COVID-19 to the availability of port workers during natural or manmade disasters.

Another project of interest involves modeling the human body using hybrid approaches, such as musculoskeletal models and finite element models, to predict the effects of long-term loads experienced by truck drivers or helicopter pilots. It combines various simulation paradigms across multiple scales. This work is conducted in collaboration with a consortium of universities, forming a large cross-disciplinary team.

I am typically brought into project teams during the conceptual phase as an expert in model composition. My role involves aligning complementary models or building ensembles when models offer competitive perspectives.

How can lessons learned from one domain be applied to another domain?

My work in medical simulation exemplifies how lessons learned from one domain, such as combat modeling and distributed simulation, can be applied to another. I contributed to the introduction and application of simulation interoperability standards in this field, primarily the IEEE 1516 Standard Family for the High-Level Architecture. The insights gained from my previous experience were transferable to medical simulation, as the underlying mathematical models are applicable regardless of whether the field is defense or healthcare. We published a paper about this in the Journal for Defense Modeling: Byrne, R., et al. (2023). Developing a blast injury modeling capability: application of concepts from the Defense M&S Domain. The Journal of Defense Modeling and Simulation, https://doi.org/10.1177/15485129231184258.

How is simulation modeling applied in defense and related applications?

For decades, the defense sector was the primary sponsor of simulation applications. Recently, however, the healthcare simulation market has become the larger segment.

One of the most prominent simulation applications is in education and training. Simulation is used to create realistic training environments and scenarios that respond to trainees' decisions and immediately visualize the outcomes, whether in a tank or flight simulator or through command-and-control monitors in military headquarters. This exposure familiarizes every soldier with this category of simulation applications. This success story is repeated in the healthcare domain, where surgeons and nurses are trained using medical simulations.

Simulation also plays a crucial role in analysis and operations research. It helps answer questions about the optimal number and mix of weapon systems for a mission, evaluates new concepts and procedures on the battlefield, and determines the best use of new options like cyber operations. This support is invaluable not only for planners but also as a decision-support tool in real operations, aiding in understanding options and likely outcomes. As the battlefield becomes increasingly complex, digital support is becoming ever more essential. Similarly, in healthcare, simulation-based optimization has been widely applied to optimize procedures in large hospitals.

What suggestions do you have for other researchers to join this accelerating field of modeling and simulation?

A solid grasp of mathematics is useful for applying lessons from one field to another. However, this doesn't mean that someone skilled in simulations can create an effective simulation without the expertise of specialists in the specific field being studied. The combination of the domain expert's knowledge and the simulation expert's mathematical skills is crucial for achieving a successful outcome.

Additionally, understanding the limits of what can be learned through simulation helps prevent unrealistic expectations or pursuing solutions that aren't feasible. This later field is called epistemology of simulation and is part of the philosophy of science.

Finally, ethical principles are fundamental to every engineering profession, so also for the simulation engineer.

Only recently, I had the honor to edit the “Body of Knowledge for Modeling and Simulation” together with two other Fellows of the Society for Modeling and Simulation. This work collects and organizes the common understanding of a wide collection of professionals in this field and builds a good foundation for those who want to know more about the discipline.

Can you provide any open access resources for our readers?

The body of my work is captured under my OrcId (0000-0002-4201-8757) and not copyright protected open work can be accessed via my Research Gate account. In case you find something helpful for scholastic work, such as writing a thesis, you can also send me an email to look for alternative modes of access.

What do you work on?

I work on a wide variety of projects in transportation, healthcare, distribution, manufacturing, and service industries. I don’t think there is such a thing as a “normal” day or “typical” project. One day, I may get to help design scheduling algorithms for a blood analyzer, and the next day, I am looking at pedestrian flow dynamics in a retail environment.

Our deliverables range from web-apps that run simulation models for a sales team to very detailed models that are run on engineers desktop. Sometimes we deliver recommendations for system design, as opposed to a model for ongoing use. At other times, we may facilitate a training and mentoring engagement to help a client bring simulation in house.

I would say my favorite projects involve scheduling problems / control logic. I also really love when I get to deliver a model to a really smart, engaged engineer that runs it independently. It is always a thrill when I get an email months or years after delivering a model and find out they have been able to be widely successful with the tools we gave them. 

How can your research be applied to another field? 

As a practitioner, I do not consider my work research in the academic sense. Our solutions often pull from several areas, such as queuing theory, facilities layout design, and computer science. Taken holistically, the solutions we develop for clients are often unique. Our customers are much more interested in solving problems effectively, with little regard for if it novel or not. 

There are some universal truths I have seen in simulation consulting over the past 20 years, regardless of the industry. A few of them include:

1. There needs to be clear objectives.
2. “Modeling the world” almost always results in a project that never adds value. In general, a successful projects are smaller scoped with greater depth or larger scope with less depth. This is not always true, but it is something to screen for when scoping a project.
3. Good programming skills and computer science techniques are not appreciated enough in simulation.

What suggestions do you have for other researchers to join this accelerating field of machine learning? 

We heard a lot of questions similar to this a lot at IISE Annual 2024. I would argue it is the wrong question. If you asked the question, “What can universities do to accelerate digital twins in industry?” I would say we need more undergraduate Industrial Engineers prepared to execute good modeling projects. We need this far more than additional academic research related to digital twin techniques. There is already so much out there that is being underutilized because there is a shortage of people that can apply what is already possible.

At its core, most simulation digital twins we see are simulation models, with a more real time feed of inputs into the model and outputs out of the model. This is not new, but it is certainly accelerated with increased data availability and awareness. The need to use good, disciplined software development practices has never been higher. Good model architecture, development processes, testing procedures, and approaches to model change management have never been more important. We need Industrial Engineers comfortable with this discipline, as well as being able to manage up to ensure reasonable scope and timelines. Besides the software development and project management components, the IE that understands the fundamental problem they are trying to solve (a layout problem, a scheduling problem, a staffing problem) is priceless.

How do you use your Industrial and Systems engineering in your day-to-day career?

I use my Industrial and Systems Engineering background almost every day. This includes statistics, facility design, operations research, time study techniques. I believe the breadth of what can be learned in a technically rigorous IE program is the perfect preparation for a career in simulation consulting.

Can you provide any open access resources for our readers?

Our website, https://mosimtec.com, contains several case studies and videos. Due to non-disclosure agreements, we cannot always publish our work in detail. However, if an IISE member has a question about good applications for simulation modeling, I would encourage you to reach out to MOSIMTEC via our contact form on our website or my email address (amy.greer@mosimtec.com).  

Challenge

The planning and scheduling of tasks and activities in a fuel fabrication site requires alignment and coordination across multiple departments with disparate equipment and resources. Furthermore, fuel assembly specifications, specifically the required enrichment level or so-called core loading plan, may only be issued shortly before desired delivery dates and are unique to each customer. These dynamic requirements contribute to significant system demand variability and planning complexity.

Solution

A process digital twin of the system was implemented to capture the inherent system complexities and logical dependencies in a virtual representation of the system. The simulation-based digital twin can then be used to generate a feasible schedule of the future operations that would fulfill customer demand.

• In order to deploy the digital twin of the fuel fabrication facility, there were three key areas of focus:
• Specification formation, model development, and output validation of the simulation model to accurately represent the system and processes at a sufficient level of abstraction.
• Accurate and timely data integration of the following items: demand, bill of materials, materials and parts, work in process, resource status, and related information from relevant enterprise resource planning (ERP) and manufacturing execution systems (MES).
• Organizational change management to maintain the relevant data and follow the plan as generated.

Benefits

• Developing a feasible new plan for a complex system now takes a few hours instead of a few weeks.
• In addition to generating short term production plans, the tool allows for long term capacity planning.
• The simulation based planning and scheduling solution provides the fuel fabrication facility with an environment to perform what-if analysis.
• The model creates Gantt charts to assist planners in understanding system behavior.

For more information please feel free to reach out to Gerda Trollip at gerda@mosimtec.com.