Material Flow Simulation

Fraunhofer SCAI models and simulates production and logistic concepts.

We support our customers in enhancing their efficiency and in developing new production systems. With sensitivity analyses we examine the behavior of production systems in extreme situations and develop alternative and emergency strategies in collaboration with our customers. 

Our simulation and optimization services concentrate on in-house logistics.

Material Flow Simulation at a Glance

Material Flow Simulation supports you in:

  • discovering room for improvement and bottlenecks
  • maximizing efficiency and utilization
  • avoiding misinvestments
  • increasing planning reliability
  • reducing land consumption
  • minimizing inventory
  • reducing cycle times
  • increasing adherence to schedules
  • developing alternative and emergency strategies.

What effects can Material Flow Simulation achieve?

  • Increases in productivity of 15 to 20 percent are possible
  • The investment cost can be decreased by up to 20 percent
  • Inventory and cycle time can be reduced by up to 60 percent
  • Realisation of a factor from 4 to 8 between use and expenditure

Detecting and implementing potential for optimization

Find out, which principles of organization are optimal for sourcing, production, and storage in your company:

  • Flow-shop – job-shop – hybrid
  • Make to order – make to stock – assemble to order
  • Central storage – local storage
  • LIFO – FIFO – HIFO – LOFO
  • Push – pull (e.g. Kanban)

Analyzing and optimizing production and logistic concepts

 

We individually vary important parameters for the development of efficient production systems. For example:

  • Number and arrangement of work stations
  • Dimensioning of storage and buffers
  • Number of means of transport, loading aids, packaging means
  • Job scheduling
  • Storage policy
  • Lotsizes
  • Clock
  • Shift model
  • Process structure and logic
  • Decoupling point (from order-neutral to customized assembly)
  • Planning horizon

We offer taylored solutions in simulation and optimization of logistics and production:

  • Problem definition with the customer
  • Modelling and simulation
  • Analysis of the current situation and identification of bottlenecks
  • Development and realization of optimizing measures
  • Consultancy and training

Many years of experience in the field of operations research enable us to combine simulation and optimization. This makes your production and logistic processes more efficient.

Related projects, in which we developed special optimization software for our customers, are Coil Nesting, Cutting of Steel Profiles and MBOpt.

The related software product PackAssistant helps to find the best possible solution of how standard containers, e.g. skeleton boxes, should be packed with individual parts of the same type.

© Photo Fraunhofer SCAI

© Photo BPW Bergische Achsen

Optimization of industrial processes

An example of a successful material flow simulation project is a process enhancement for BPW Bergische Achsen in Wiehl, Germany. We conducted a simulation study in order to optimize the manufacturing processes in the axle plant.

The main problem was a large stock, which led to undesirable capital commitment and required a high effort for order picking. On the other hand it assured on-time delivery even during bottlenecks and breakdowns. Within this project, we aimed at reducing inventory and simultaneously maintaining a high-level adherence to delivery dates. Furthermore, we were asked to conduct sensitivity analyses for exceptional conditions, such as extreme order mix or low material availability, and to develop compensatory measures.

First of all, we modelled the current status in the simulation software Plant Simulation. Based on this simulation, we developed measures for optimizing processes and maintaining performance in collaboration with BPW, such as:

  • capacity expansion in certain divisions
  • acceleration of clocked machines
  • shortening planning intervals
  • changing the decoupling point
  • common usage of resources
  • stronger concatenation of working stations
  • globally optimal job scheduling
  • variation of the stock’s removal strategy
  • elimination of the stock and compensation by innovative concepts

The most promising ideas were implemented in the model, simulated, and evaluated. BPW began implementing selected optimization activities before the project was even finished.

What did we achieve? We managed to reduce inventory considerably without compromising on-time delivery. Furthermore, the project improved inter-divisional communication. After updating the model, it can be reused for future simulations.