Basics of supply chain simulation

What is a supply chain simulation?

A supply chain simulation models a supply network with suppliers, production sites, warehouses, customers and transport and shows its behaviour over time. The rules of the supply chain are defined in the model and executed at runtime, for example: production of an item starts when its stock falls below a defined reorder point. This makes it possible to examine how these rules interact and how the supply chain reacts to events such as strikes, natural disasters or fluctuations in demand.

What is the difference between simulation and network optimisation?

Network optimisation is an analytical method. It describes the supply chain using linear equations and calculates the most cost-effective network structure, such as the number and location of sites. To do this, the network has to be simplified. Dynamic simulation, on the other hand, models the processes themselves, including random events, inventory policies and time-dependent effects. It does not deliver a mathematically optimal solution, but shows how a solution behaves in operation. The two methods complement each other: optimisation delivers the plan, and simulation shows how it can be implemented.

When does it make sense to simulate a supply chain?

Analytical methods such as greenfield analysis and network optimisation are mainly suited to location decisions, for example the question of whether a centralised or decentralised network structure is more cost-effective. Simulation makes sense when you want to understand the processes in the network or need KPIs over time, such as service level, transport utilisation or stock per item. Typical applications are:

• determining safety stocks across several stages of the supply chain
• evaluating inventory policies
• identifying bottlenecks
• determining the cost of achieving a given service level
• testing the supply chain against disruptions
• answering what-if questions, for example about new production sites or transport strategies

What is a greenfield analysis?

Greenfield analysis, also known as centre of gravity analysis, is usually the first step in planning a supply network. It suggests the number and location of distribution centres or production sites without you having to specify site options. Only a small amount of data is required: customer locations, products and the demand per customer and product. The result is the location at which the costs for all inbound and outbound transport are lowest. The basic version does not take roads or geographical features into account. Its results are therefore used in a subsequent network optimisation that compares realistic site options.

Is Excel sufficient for planning a supply chain?

For small, manageable questions, it often is. As the scope grows, Excel reaches its limits: input data is difficult to check, models are time-consuming to maintain and the network cannot be seen on a map. Above all, Excel does not model processes over time. If you want to know how inventory or sourcing policies affect your supply chain, you need a simulation. Specialised tools such as anyLogistix offer data validation, a map editor, model templates and custom constraints for this purpose.

Which companies is supply chain simulation suitable for?

For companies whose costs and delivery capability depend heavily on the structure of their supply network. This applies to industry, retail, logistics service providers and consumer goods manufacturers as well as to sectors with many suppliers and global transport networks, such as the automotive industry and mechanical engineering. Simulation is used by supply chain and logistics managers, planners and executives who want to validate decisions on locations, inventory or suppliers.

Typical questions and areas of application

Which questions can a supply chain simulation answer?

Typical questions from network design projects are:

• How many warehouses do we need, where should they be located, how large should they be and which customers do they serve?
• How many production sites and production lines do we need, and which products are manufactured where?
• Which products do we manufacture ourselves, which do we source from suppliers, and from which suppliers?
• How are the number of sites, total costs and service level related, and what does a higher service level cost?
• What influence do customer demand, personnel costs and raw material prices have on the network?
• How can seasonal fluctuations in demand be covered by production planning?
• How do we ensure sufficient capacity and flexibility in the supply chain?

How does simulation help with inventory planning?

High stock levels secure delivery capability but tie up capital and incur storage costs. Low stock levels save costs but increase the risk of not supplying customers on time. Formulas for order quantity and reorder point assume constant demand and constant lead times, which is rarely the case in practice. In a simulation, safety stocks and inventory strategies can be tested under fluctuating demand and uncertain lead times, also across several stages of the supply chain. This shows how far stock levels can be reduced without jeopardising the service level.

How can risks and disruptions in the supply chain be assessed?

In the simulation model, disruptions, supply problems and fluctuations in demand can be played through in a targeted way. The simulation shows how sensitively the network reacts and how this affects stock levels, delivery capability and costs. You can also test different scenarios for changes to the network or its policies and define contingency plans before a disruption occurs. This is not possible in this form with conventional analytical tools for risk management.

Which KPIs does a supply chain simulation provide?

The KPIs measured are those relevant to the supply chain in question, for example costs and revenue, stock development, service level, lead time and delivery reliability, utilisation of capacities and transport, throughput times, open orders and the bullwhip effect. Because the simulation models the course of time, you see not only final values but also how a KPI changes, for example the stock level on a specific day of the simulated period. The KPI system can be based on the real system or first be designed and tested with the help of simulation.

Can CO2 emissions also be assessed?

Yes. In addition to costs and service level, CO2 emissions can be evaluated as a KPI, for example in the Supply Chain Suite. In anyLogistix, network optimisation can also use CO2 emissions as an optimisation objective: first, a minimum profit is set as a constraint, then the optimisation searches for the network configuration with the lowest emissions. This shows what a reduction in emissions costs.

Can the simulation also model processes in warehouses and plants?

Yes. In addition to the network as a whole, anyLogistix can model processes within warehouses, plants and distribution centres in detail, down to conveyor systems and means of transport. If the supply chain contains very special processes that are not covered by the anyLogistix standards, the SimChain Building Block Library based on Plant Simulation is used. It allows you, for example, to dimension machines, resources and the number of special containers required.

Digital twin and artificial intelligence

What is a digital twin of the supply chain?

A digital twin is a simulation model of the supply chain that is connected to current operating data, such as shipping schedules, vehicle locations and stock levels. It uses this data to assess the current state of the supply chain and to produce continuously updated forecasts. It can issue warnings in critical situations, for example when the service level falls below a threshold, and test action plans in advance. Unlike a simulation model for a one-off planning study, it is integrated into the existing IT environment with databases and business intelligence tools.

What is an agentic digital twin?

A digital twin connects a simulation model with real data. In an agentic digital twin, AI agents use this model themselves: they adjust scenarios, run them and evaluate alternatives. Much of this is still a concept today. The basis for it is reliable simulation models of your own supply chain.

Does AI replace supply chain simulation?

No. AI can recognise patterns, explain simulation results and translate questions in natural language into experiments. It cannot judge on its own whether a decision will work in the real network. That is still shown by simulation: it tests solutions under realistic conditions such as actual lead times, inventory policies and fluctuating demand. Anyone who wants to use AI in supply chain planning therefore needs reliable models and a clean data basis.

The SimChain toolset

Which components make up the SimChain toolset?

The SimChain toolset consists of five components:

• anyLogistix from The AnyLogic Company for the design, optimisation and simulation of supply chains
• SimChain Building Block Library, developed in-house by SimPlan on the basis of Plant Simulation, for very special processes
• Supply Chain Suite (SCS) from Siemens Digital Industries Software, which extends ERP systems with supply chain management
• KNIME for preparing and analysing supply chain data
• Python for very complex data analyses and data transformations

Which tool is used depends on the question, such as network analysis, inventory optimisation or a digital twin of the entire supply chain.

What can anyLogistix do?

anyLogistix combines analytical network optimisation and dynamic simulation in one tool. The IBM ILOG CPLEX solver works in the background for optimisation. The experiment types include greenfield analysis, network optimisation, simulation, risk analysis, inventory optimisation, transport optimisation and what-if analyses. With a data connection, a model can be operated as a digital twin, and every component of a simulation model can be adapted with AnyLogic Professional. SimPlan is the official sales partner for anyLogistix in the DACH region.

When is the SimChain Building Block Library used?

When the supply chain contains very special processes that are not covered by the anyLogistix standards. The building block library was developed in-house by SimPlan and is based on the requirements of numerous logistics and supply chain projects. It is object-oriented and based on Plant Simulation from Siemens Digital Industries Software, so models can be extended individually. Typical applications are comparing network alternatives, production and sourcing strategies, dimensioning stock coverage and resources, and selecting transport solutions with delivery cycles, minimum order quantities, delivery lot sizes and transport modes. The building block library is available as a licence and is also used in SimPlan projects.

What are KNIME and Python used for?

Most supply chain simulation tools offer hardly any functions for data preparation. The KNIME Analytics Platform, free software for data processing and data analysis (ETL: extraction, transformation, loading), closes this gap. It converts supply chain data into a format that optimisation and simulation can read and works on a workflow basis with several hundred modules. If the analyses become too complex for KNIME, SimPlan uses a Python environment with libraries for large data volumes, for example to extrapolate goods receipt and goods issue data to future scenarios.

Can I test anyLogistix free of charge?

Yes, in two ways. The anyLogistix Personal Learning Edition (PLE) is a free version for learning purposes. The anyLogistix Sandbox runs entirely in the browser and is ready to use in a few minutes. It contains most functions but, as a demonstration environment, is restricted: no data import, only one project, limited model size, no multi-user collaboration and no access to the Open API.

Do I need programming skills?

Not for most tasks. anyLogistix and the Supply Chain Suite work mainly with graphical modelling and predefined functions, and in anyLogistix the experiments guide you step by step through typical analyses. Basic knowledge helps but is not essential. If you do not want to build models yourself, SimPlan takes care of modelling and evaluation for you.

What is the Supply Chain Suite (SCS)?

The Supply Chain Suite is modular software from Siemens Digital Industries Software for managing supply chains. It does not replace existing ERP systems but complements them: the SCS combines data from ERP systems, transport management and other sources in a uniform data model and makes it usable for analysis, simulation and optimisation. Its modules include Network Optimization, Transportation Optimization, Intralogistics Optimization and Rate Optimization. The SCS is provided as software as a service. SimPlan is a certified Siemens Smart Expert Partner.

Data, projects and support from SimPlan

Which data is required for a supply chain simulation?

That depends on the question. For a greenfield analysis, customer locations, products and the demand per customer and product are sufficient. Network optimisation and simulation need more detail, for example on manufacturing processes, resources, warehouse and distribution processes, replenishment and sourcing policies, transport and costs. This data is often spread across ERP systems and other sources. SimPlan supports data collection and prepares the data with KNIME or Python.

Can the simulation be connected to ERP and other systems?

Yes. anyLogistix processes Excel, CSV and geodata and can be connected to ERP and WMS systems via data export and import or via API. The Supply Chain Suite can be integrated with ERP, transport management and CRM systems via standardised APIs. This allows models to be supplied with current data regularly and used in ongoing operations.

How does a supply chain project with SimPlan work?

SimPlan supports simulation studies with the SimChain toolset in all phases:

1. joint process analysis and definition of the relevant KPIs
2. support with data collection
3. modelling with the SimChain toolset and visualisation of important process steps
4. definition of the experiment plan
5. analysis of the results, optimisation of parameters and recommendations on supply chain design
6. presentation and documentation
7. on request, transfer of the results to SCM planning and collaboration systems and support with implementation

You do not need any simulation or software expertise of your own.

How much does a supply chain simulation cost, and is it worth it?

The cost depends on the complexity of the supply network and the availability of data. As a general guide: the more costs and delivery capability depend on a few key decisions, such as site selection or supplier selection, the quicker a simulation pays for itself, because wrong decisions at this stage are particularly costly. Please contact us for a specific assessment.

Are there practical examples?

Yes. For a large German building materials manufacturer with 24 plants and 6,000 products, SimPlan analysed and optimised the supply chain with anyLogistix. The aim was a network that would support the forecast growth up to 2030 cost-efficiently. Among other things, a centralised versus a decentralised structure, the choice of locations for production and storage, and the effects on lead times, transport costs and stock levels were examined. You can find the case study on the anyLogistix page on simplan.de.

How can I find out more without obligation?

Our free web seminars give you an introduction to modelling, optimising and simulating supply chains. The content covers a general introduction, greenfield analysis, network optimisation, dynamic simulation, evaluations and extension options. Afterwards, we answer your questions about your specific case. Web seminars on individual tools are available on request. We are also happy to arrange an individual appointment with our supply chain experts.