A Bin Packing Algorithm for Steel Production

Maddaloni, Alessandro; Colla, Valentina; Nastasi, Gianluca; Seppia, Marco Del; Iannino, Vincenzo

doi:10.1109/ems.2016.014

Cited by 4 publications

(3 citation statements)

References 19 publications

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“…Examples of products scheduling optimization for a cold rolling line are presented in [2,17]. Other examples of discrete optimization with different constraints such the coil-scheduling problem can be found in literature [3,[18][19].…”

Section: Process Self-optimizationmentioning

confidence: 99%

A Multi-Agent Approach for the Self-Optimization of Steel Production

Iannino

Vannocci

Vannucci

et al. 2019

International Journal of Simulation: Systems, Science &Amp; Technology

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The paper presents a distributed intelligence-based system concept for modeling and self-optimizing the production of flat steel products. The concept is implemented through a multi-agent system approach. In particular, three types of autonomous agents are modelled, each playing a different role in the steel production chain. The agents are designed in order to take autonomous decisions based on their current and target state, to adapt the production scheduling through optimization algorithms and communicating each other to react on unforeseen interruptions and disturbances. The approach is designed for the steel coil coating manufacturing but can be easily readapted to any brown-field scenario.

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Section: Process Self-optimizationmentioning

confidence: 99%

A Multi-Agent Approach for the Self-Optimization of Steel Production

Iannino

Vannocci

Vannucci

et al. 2019

International Journal of Simulation: Systems, Science &Amp; Technology

Self Cite

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“…The problem we are targeting arises from the steel-processing production process, where specific constraints must be considered. In this kind of industry even small improvements in the production operation can result in large monetary savings [24]. In our case raw materials are ordered and delivered in batches.…”

Section: Introductionmentioning

confidence: 99%

Material Requirements Planning Using Variable-Sized Bin-Packing Problem Formulation with Due Date and Grouping Constraints

Gradišar

Glavan

2020

Processes

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Correct planning is crucial for efficient production and best quality of products. The planning processes are commonly supported with computer solutions; however manual interactions are commonly needed, as sometimes the problems do not fit the general-purpose planning systems. The manual planning approach is time consuming and prone to errors. Solutions to automatize structured problems are needed. In this paper, we deal with material requirements planning for a specific problem, where a group of work orders for one product must be produced from the same batch of material. The presented problem is motivated by the steel-processing industry, where raw materials defined in a purchase order must be cut in order to satisfy the needs of the planned work order while also minimizing waste (leftover) and tardiness, if applicable. The specific requirements of the problem (i.e., restrictions of which work orders can be produced from a particular group of raw materials) does not fit the regular planning system used by the production company, therefore a case-specific solution was developed that can be generalized also to other similar cases. To solve this problem, we propose using the generalized bin-packing problem formulation which is described as an integer programming problem. An extension of the bin-packing problem formulation was developed based on: (i) variable bin sizes, (ii) consideration of time constraints and (iii) grouping of items/bins. The method presented in the article can be applied for small- to medium-sized problems as first verified by several examples of increasing complexity and later by an industrial case study.

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“…It provides a preliminary global optimal resource scheduling under static conditions, i.e., based on production orders and not considering unexpected events. MILP techniques are used to solve different types of industrial problems, including gas distribution [39], cutting and packing [40], energy and by-products management [41,42], production planning [43] and scheduling [44]. Their importance lies in both their wide application and the availability of effective general-purpose techniques for finding nearly optimal solutions.…”

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confidence: 99%

A hybrid approach for improving the flexibility of production scheduling in flat steel industry

Iannino

Colla

Maddaloni

et al. 2022

ICA

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Nowadays the steel market is becoming ever more competitive for European steelworks, especially as far as flat steel products are concerned. As such competition determines the price products, profit can be increased only by lowering production and commercial costs. Production yield can be significantly increased through an appropriate scheduling of the semi-manufactured products among the available sub-processes, to ensure that customers’ orders are timely completed, resources are optimally exploited, and delays are minimized. Therefore, an ever-increasing attention is paid toward production optimization through efficient scheduling strategies in the scientific and industrial communities. This paper proposes a hybrid approach to improve the flexibility of production scheduling in steelworks producing flat steel products. Such approach combines three methods holding different scopes and modelling different aspects: an auction-based multi-agent system is applied to face production uncertainties, multi-objective mixed-integer linear programming is used for global optimal scheduling of resources under steady conditions, while a continuous flow model copes with long-term production scheduling. According to the obtained simulation results, the integration and combination of these three approaches allow scheduling production in a flexible way by providing the capability to adapt to different production conditions.

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A Bin Packing Algorithm for Steel Production

Cited by 4 publications

References 19 publications

A Multi-Agent Approach for the Self-Optimization of Steel Production

A Multi-Agent Approach for the Self-Optimization of Steel Production

Material Requirements Planning Using Variable-Sized Bin-Packing Problem Formulation with Due Date and Grouping Constraints

A hybrid approach for improving the flexibility of production scheduling in flat steel industry

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