Supply Chain & Logistics Simulation - Engineering Industries eXcellence

Navigating Increasing Supply Chain Complexity

In the dynamic landscape of the modern business world, the supply chain has undergone a profound transformation since the start of the digital age, and at the heart of this evolution lies the omnipresence of data. Unlike its form 100 years ago when the term ‘supply chain’ was first conceived, today's network of resources is intricately woven with the threads of information and technology. As a result of globalization, industrial machinery advancements and ever-fluctuating market conditions, businesses now find themselves in a data-rich environment with an unprecedented volume of information at their fingertips. While this influx of data presents unparalleled opportunities, it also poses a unique challenge – the need to navigate through the vast sea of information and harness its power for effective analysis and optimization.

Applying Technology for Supply Chain Optimization

Even in the digital age, many computerized methods of supply chain management fall short in utilizing data and addressing the intricacies of supply chain dynamics, which often results in suboptimal performance, increased costs and vulnerability to disruptions. Supply Chain Simulation models have emerged to bridge this gap. Industrial enterprises, recognizing that addressing these challenges requires more than mere digitalization, are turning to Supply Chain Simulation to leverage their data comprehensively.

In addition to acting as a proactive tool to optimize supply chain processes, Supply Chain Simulation technologies are being implemented by industrial organizations today to solve some of their most common and complex supply chain challenges. Supply Chain Simulation helps industrial enterprises proactively answer questions such as:

Where to locate new facilities?
How would the supply chain change if a new product was introduced?
How would the supply chain withstand a strike or the loss of a supplier?
What service level can we provide customers with?
What inventory policies should we use to balance costs and service levels?
What should the capacity of the new manufacturing plant be?
How many products do we have to ship each month?
Should we use our own or rented vehicles for transportation?

What is Supply Chain Simulation?

Applying Supply Chain Simulation technologies enables organizations to create a digital representation, or Digital Twin, of a supply chain system, which businesses can then utilize to model, analyze and optimize their end-to-end processes in a risk-free virtual environment. It mirrors real-world scenarios, enabling organizations to experiment with different strategies, assess the impact of changes and make informed decisions before implementation. Whether your organization is trying to study and optimize your entire supply chain workflow, or if you have a very specific supply chain problem that you are trying to solve, the process to create a Digital Twin is the same:

1. Data Collection for Supply Chain Model

This process begins with data collection. Relevant information such as transportation costs, lead times, inventory levels, resource availability and other factors is collected and used to build the foundation of the virtual model. With broad technical expertise, an innovative solution portfolio and a breadth of experience across industrial sectors, Engineering Industries eXcellence’s global Simulation & Decision Science team collaborates with stakeholders and third-party logistics (3PLs) along the supply chain to make sure that the right data is collected and utilized to build a comprehensive model that accurately represents their real-life supply chain. After identifying the critical variables and parameters that will be modeled, our team leverages the most advanced simulation software on the market today to build the 3D model.

2. Supply Chain Model Development

Next, the model is developed. Upon implementing the chosen solution, Engineering IndX experts begin developing mathematical models and algorithms that represent the relationships and interactions between different elements of our customer’s supply chain, including equations, logic statements and decision rules to simulate real-world dynamics. These equations are validated by comparing the model’s output with historical data or real-world observations and calibrated to ensure that it accurately reflects the behavior of the actual supply chain.

3. Supply Chain Simulation Studies & Decision Science

Once the model is ready, it is time to define scenarios and run simulations. First, our team will specify the scenarios to be simulated, including variations in demand, changes in production schedules, disruptions and random factors. During execution, we analyze the results to identify performance metrics and assess the impact of different decisions, which enables us to optimize the customer’s supply chain processes, identify bottlenecks and refine decision-making strategies. By adjusting parameters and running tests frequently, the Supply Chain Simulation model can be continuously improved and utilized by the customer long after the project is over. Documenting results and communicating findings to key stakeholders facilitates informed decision-making along the supply chain.

Building a Supply Chain Simulation model is an iterative process that involves continuous refinement and validation to ensure its effectiveness in providing valuable insights and support for decision-making. By embracing Supply Chain Simulation, organizations gain the ability to see their supply chains holistically and analyze alterations in a risk-free virtual environment, tackling challenges such as demand variability, inventory management intricacies, lead time uncertainties and overall operational inefficiencies with a more informed and strategic approach.

Features of Our Supply Chain Simulation Solutions

Create agent-based simulation models focused on individual active components of supply chain and their behavior(e.g., people, equipment, products)
Create discrete event simulation models focused on separate business processes of a supply chain (e.g., logistical or warehouse operations)
Create system dynamics simulation models as general representations of complex supply chains for long-term, high-level studies
Model the layout of production facilities, warehouses and distribution channels
Run, evaluate and manage “what-if” scenario analysis
Identify and analyze supply chain bottlenecks, improvements and/or changes
Access 2D and 3D visualization of supply chain layout, resources and processes
Define and monitor supply chain Key Performance Indicators (KPIs)
Visualize data and analytics (energy usage, throughput, resource utilization, etc.)
Apply optimization algorithms, AI and machine learning methodoligies for intelligent supply chain model insights
Predict the impact of new product introductions
Study distribution channels or logistics to implement changes
Assess the performance of suppliers and other partners

Benefits of Our Supply Chain Simulation Solutions

Drive more intelligent decision-making
Leverage a risk-free environment to test and explore
Save money and time in the real world
Deliver concepts and ideas in a more effective way
Provide insight into complex system dynamics
Increase accuracy and visibility into data and processes
Better handle uncertainty and minimize risks
Improve planning processes and results
Ensure quality of processes, product and services
Reduce inefficiencies and time-to-market

Engineering’s Expertise

Engineering Industries eXcellence has broad technical expertise, deep regulation knowledge and an innovative solution portfolio that makes us a power player in the arena of supply chain management. Our global team of Simulation & Decision Science experts has helped businesses across industrial sectors worldwide to optimize their supply chains for over a decade. By understanding and leveraging the potential of data, our Supply Chain Simulation solutions play a pivotal role in unlocking the true efficiency and resilience of the modern supply chain.