Skip to content

Production Scheduling Tool for Metal Meshes Factory

Operative 
tool

The client has a metal meshes factory composed of many
machines spanning different processes: cold-rolling, bending and welding.
 

Objetives

Maximize service level and fulfillment of the delivery schedule, while considering resource efficiency.

Case Presentation

Challanges

Multiple machines
Múltiples máquinas

A production plant of metal meshes composed of multiple machines working, some sequentially and others in parallel.

Difficulties
Dificultades

Low levels of productivity are recorded, difficulties in projecting stocks, events such as warehouse saturation, as well as a lack of coordination between supply and demand.

Optimized program
Programa optimizado

The objective is to develop a tool that, based on information provided by the client, generates an optimized program. Additionally, it should be able to provide information on the projected performance of the system to allow for analysis of improvement opportunities.

Programación manual
Manual Scheduling

Manual scheduling did not consider relevant factors such as resource availability and workload.

Methodology

Inputs
Inputs / palancas
  • Working Calendar
  • Maintenance Calendar
  • Forecasted Demand
  • Initial stock, initial configuration of each machine 
  • Bill of materials 
  • Transportation resources by product type
  • Products
  • Roadmap
  • Productivities
  • Setups
  • Required workforce
  • Other parameters
Process
Proceso

An optimization engine was developed, applying local search algorithms. It starts with a base solution built from predefined programming logic. Then, solutions are explored using metaheuristics such as Tabu Search in search of the global optimum.

Simulator
Simulador

To evaluate each solution, a simulator was developed. The simulator, based on a 100% agent-based model, allows for a detailed representation of the system, which is necessary given the complexity of the interaction between its components and their temporal evolution.

In addition to evaluating the solution, the same simulator informs the optimizer about the best possible “neighbor” solutions to explore next.

Results

KPIs 

  • Machine Schedule
  • Fulfilled demand
  • Estimated production
  • Machine utilization, including losses' detail
  • Warehouse utilization
  • Transport utilization
  • Required workforce
  • Projected stock evolution
  • Supply requirements

In addition to providing indicators and a program to operate the plant, the tool also allows for scenario analysis. For example:

  • Studying utilization and service level following the current operational policies.
  • Determining the best scheduling strategy.
  • Finding the policies or criteria that generate the greatest benefits in the operation.
  • Analyzing the impact of introducing a new type of product. 
  • Anticipating the level of semi-finished stock and the need for storage resources.
  • Anticipating the projected fulfillment of the program/demand. Quantifying the risk of non-compliance.
  • Studying the impact of modifying the storage capacity of the sectors.

     

  • Examining the impact of equipment shutdown and potential recovery strategies.
  • Quantifying the need for material movement (personnel and equipment).