Multi-Variable Mathematical Optimization

LineLab uses a powerful optimizer to do two things simultaneously: determine dynamic factory behavior, and optimize the system configuration as a whole - minimizing production costs overall. To do that, it combines detailed financial models and nonlinear models of factory behavior in a powerful optimization.

Input Flexibility: Any System Parameter can be an Input, or Optimized by LineLab

As a result, LineLab can be used in different ways, and it is up to the user - and their use case - to decide, which parameters are known, and which parameters LineLab should determine. That's the beauty of a purely mathematical optimization: as long as you can assign a cost to every variable - like the purchase cost of machines or a maximum total floor space - it does not matter how many variables are unknown, LineLab is able determine the optimal value for all of them simultaneously, to minimize unit costs.

From target rate: A popular use case is to set a target rate, and let LineLab optimize how many machines and part carriers should be obtained. LineLab will automatically determine the optimal "capacity buffer" and "inventory buffer" that would minimize unit costs overall.

From existing equipment: Likewise, for an existing production system, LineLab can determine the optimal rate the system can handle. It can also find favorable production rates given certain equipment constraints - and will always tell you, where the bottleneck will be.

Automated & Seamless: Minimal User Input for Maximum Results

Starting points are not needed - LineLab will automatically optimize any parameter for which an input is not provided. At the same time, you can always constrain parameters, such as maximum queueing time between any two stations, utilization, etc. You can provide arbitrary costs for LineLab to consider, such as carbon credits for machine usage. As long as your system is feasible, LineLab will find the best way to realize it.

LineLab automatically optimizes a great number of variables, unless provided as an input - commonly any of the following:

  • Workstation count
  • Max. rate
  • WIP inventory
  • Buffer sizes
  • Utilization
  • Best use of $x investment
  • Critical path + margins
  • Bottleneck placement
  • Kanban / tool count
  • Favorable production rates
  • Economic production quantities
  • Flow times
  • Waiting times
  • Any variable that can be parametrically expressed: Geometries, sustainability KPIs, lifecycle parameters …

Thus, alongside its detailed models of complex production flow and extensive financial models, LineLab's powerful optimization solver makes it particularly suitable for early-stage projects with numerous unknowns, and for optimizing highly complex systems with thousands of interrelated performance parameters.