Production Planning in Marine Industry

Production Planning in Marine Industry

Italy is historically known for being one of the most exclusive countries to produce yachts and super yachts across the globe. In order to gain market penetration amongst the numerous prestigious brands, cost control and rightsizing are as important as product and process innovation. The manufacturing process of luxury yachts is complex, and the quality of the final product and craftsmanship cannot be compromised. The manufacturing process requires a huge amount of time and labor for each yacht.

Each yacht uses a multitude of different highly skilled trades, performing a large number of manufacturing tasks, some of which can be completed in sequence, and others that are mutually exclusive. To add to the complexity, the process is constrained by space, both in terms of how many yachts can be in the factory at any one time (at over 60 feet, the logistics associated with moving a yacht around the factory isn’t easy), and in terms of how many people can be working on the yacht at once (it is impossible to have a horde of people working within the same hull at the same time).

Problem

The managers of one of the most important Italian manufacturers, Monte Carlo Yachts, needed a new, intelligent approach that would make the planning process simpler. Fair Dynamics and DSE Consulting (now SimulAi) were approached to develop a radical new tool for simulation support planning. The objective was to give the real production planner exceptionally rich planning information, which would allow the person to test and refine a plan before its implementation. The concept of the tool was guided decision making, which means that the individual can easily refine ideas and test a plan’s feasibility over multiple simulations before rolling it out to the factory.

Solution

The solution was a simulation based decision support tool developed through AnyLogic, using its unique hybrid approach. Discrete events were used to model the physical layout and the manufacturing process, and Agent Based were used to model the production planner’s complex and adaptive “day-by-day” decision making. This tool could easily simulate both automatic (Agent Based decision making) and human guided planning solutions as an integral part of a 3 step aggregate plan process:

  1. Automatic, unconstrained scheduling.
  2. Human guided review of both the master plan and the resource plan, adjusting parameters.
  3. Constrained production planning, using the updated data from stage 2, to tests its feasibility.

Thanks to the efficient Anylogic Java engine, the entire simulation process of a production season only took a few seconds!

Yacht Production Simulation

Outcome

Watch Luigi Manca from Fair Dynamics and Dave Buxton from DSE presenting this project at the AnyLogic Conference 2012:

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