Abstract
This article considers the challenging problem of production lot sizing and scheduling that arises in the glass container industry. In such manufacturing environment, a furnace operates continuously feeding its attendant container forming machines with melted glass. Setups in the aforementioned machines interrupt the melted glass flow and, hence, the glass paste undergoes a heat loss. Consequently, a warm-up process is needed after each setup changeover. In addition, setups can affect the furnace output (total amount of glass extracted from the furnace) resulting in extraction variation losses. Both warm-ups and furnace extraction variations prevent the capacity of machines from being fully used and incur in additional costs. This study addresses such specificities for the first time in lot sizing and scheduling literature by introducing a novel integer programming model, which represents the problem appropriately, and a variable neighborhood search (VNS) solution method. A relevant case study conducted in an amber glass bottle plant shows that the model is able to comprise the problem requirements, and the VNS produces good-quality solutions in reasonable computational times. The reproducibility of the results is ensured by additional experiments involving artificial instances.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: The International Journal of Advanced Manufacturing Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
