Optimizing a Cutting Work Center: Multi-Criteria Approach to Pattern and Single Cut Sequencing
Abstract
Data di Pubblicazione:
2025
Abstract:
This work presents a multi-criteria optimization framework developed in collaboration with a leading company in the production of automatic machines for iron manufacturing. The study focuses on optimizing the workflow of a cutting machine and its unloading system, aiming to enhance efficiency and minimize idle times.
The manufacturing process involves several sequential steps. Initially, iron bars are cut according to pre-computed cutting stock patterns and transported via a conveyor belt to two temporary buffers. From there, a portal equipped with pliers relocates the bars through lengthwise movements into a depot consisting of identical parallel buffers, where they are consolidated by order. The finalized orders are then transferred to unloading tracks upon request from downstream processing steps. The first step essentially resembles a single-machine batch scheduling problem, whereas portal management incorporates features from several classical problems, such as dynamic berth allocation, virtual machine packing, and dynamic bin packing.
A key challenge arises from potential idle periods of the sequential cutter when the unloading stations reach capacity, leading to machine blocking. To address this, a three-step optimization approach, combining local search techniques and enumeration, is proposed. First, a local search minimizes order spread by optimizing the sequencing of cutting patterns. Second, a branch-and-bound procedure determines the optimal dispatching of parts to the unloading stations, reducing
cutter breaks and portal movements. Finally, a sequential value correction heuristic dynamically allocates consolidated lots into the depot, balancing the minimization of portal translations with the reduction of fragmented orders.
Computational experiments on real-world industrial instances validate the effectiveness of the
proposed methodology, demonstrating improvements in cutter utilization, order consolidation, and
overall workflow efficiency.
The manufacturing process involves several sequential steps. Initially, iron bars are cut according to pre-computed cutting stock patterns and transported via a conveyor belt to two temporary buffers. From there, a portal equipped with pliers relocates the bars through lengthwise movements into a depot consisting of identical parallel buffers, where they are consolidated by order. The finalized orders are then transferred to unloading tracks upon request from downstream processing steps. The first step essentially resembles a single-machine batch scheduling problem, whereas portal management incorporates features from several classical problems, such as dynamic berth allocation, virtual machine packing, and dynamic bin packing.
A key challenge arises from potential idle periods of the sequential cutter when the unloading stations reach capacity, leading to machine blocking. To address this, a three-step optimization approach, combining local search techniques and enumeration, is proposed. First, a local search minimizes order spread by optimizing the sequencing of cutting patterns. Second, a branch-and-bound procedure determines the optimal dispatching of parts to the unloading stations, reducing
cutter breaks and portal movements. Finally, a sequential value correction heuristic dynamically allocates consolidated lots into the depot, balancing the minimization of portal translations with the reduction of fragmented orders.
Computational experiments on real-world industrial instances validate the effectiveness of the
proposed methodology, demonstrating improvements in cutter utilization, order consolidation, and
overall workflow efficiency.
Tipologia CRIS:
4.2 Abstract in Atti di convegno
Elenco autori:
Arbib, Claudio; Marinelli, Fabrizio; Pizzuti, Andrea
Link alla scheda completa:
Titolo del libro:
Book of Abstracts of the International Conference on Optimization and Decision Science 2025