ITE Consult at The AnyLogic Conference 2019 #ALConf19

The AnyLogic’s seventh annual Conference will take place at Austin, Texas (USA) the
17th – 19th of April. This year’s conference features panels with teams from all over the
world.

This event is a great opportunity to connect with managers and engineers from
different places and see what is new in the field of simulation models. Discover
different users and watch the new features and tools available in AnyLogic.

ITE Consult will be part of the first day of the conference and we will expose a case
study and introduce the innovations and technology in our company.

Wednesday April 17th, 2019
2:00 PM – A Multi Phases Pet Food Production Process
ITE Consult Team: Elisa Elena, Engineer; Gaston Fourcade, Javier Cortes,
Computer science

Don’t miss the chance to see how AnyLogic and ITE Consult can help users from
industry-leading organizations. You can buy tickets to attend in this link.
(https://www.eventbrite.com/e/anylogic-conference-2019-tickets-52824155471)

Production Scheduling with MultiObjective Optimization (MOO)
Case Study: A Muli Phases Pet ’s Food Production Process.

The Challenge: According to a weekly changing demand of more than 140 SKU’s, the

problem to solve was how to produce the expected demand, optimizing each
of the phases (extrusion, drying, coating, kibbles storage and packaging) that
were restrictive over the others, and changing from fluid to discrete.
Individual phases capacities were large enough to make the user feel he
could produce the input demand, but there was no way to achieve this goal
without the help of this simulator.

The Concept: This optimizer has been designed to be a trade-off solution, between the optimization of the

partial components.

Why Anylogic: We have chosen Anylogic, as we needed to combine discrete and fluid

behavior. The Fluid library has been extremely useful for the multi
components SKU production, as it allowed to combine different master
formulas for a certain finish good. We also needed to develop an agent that
will put together a combination of strategies, to allow each phase to make
their own decisions, before optimizing the combination. Due to the large
number of possible combinations it was not feasible to develop a standard
optimization model, so the use of Anylogic agents, with the internal strategic
functions we have developed, allowed us to achieve the Multi Objective
Optimization, our final goal.

The use of Optquez, in the optimization experiment, was the final step to get the best

weekly detail schedule.

Other features we have used are the ability of Anylogic in choosing the excel file to be

used and compare runs features, the ability of connecting Anylogic with
Python, for previous and outputs reports and graphical interphase.

The Output: The output of this simulation/optimization is an optimized detail

schedule for each of the process phases.

As a result, we have been able to maximize the tons produced and minimize the waist

in the different stages, with big savings for the company.

Actually, the company is using the model, for their weekly detail scheduling, to be

able to fulfill their demand and avoid waist.