| dc.description.abstract | Most companies typically find a way to meet customer demands for high-quality items
at a minimal cost while maintaining overall quality. Higher quality standards are
required now more than ever, especially when a startup is going against a
manufacturing-focused firm (the Tobacco industry in our case) and has limited funding
for development. Furthermore, because of artificial intelligence's growing capabilities,
experts and researchers can now apply these tactics to a variety of commodities, such as
labor- and time-optimized manufacturing schedules and cost-of-living optimization, to
develop sensitive product attributes. To achieve optimal production planning on a single
manufacturing line, this research proposes a Mixed Integer Linear Programming (MILP)
model. All typical production planning constraints are included in this model, including
labor shifts, machine capacity, inventory limits, materials balance, and manpower
constraints. It also considers certain aspects of the production of Tobacco. Products vary,
and setup costs and times are impacted by the order. All of the main sources of variable
costs—labor, inventory, and conversion costs—that depend on the production schedule
are taken into consideration while the target function is minimized.
The current study suggests an optimization schedule for the factory's Tobacco
manufacturing process in order to meet these research objectives. In this study, Tobacco
Company, a newly founded dairy company, is the subject of the production solution
application. The manufacturing industry is trying to figure out how to win in this market. | en_US |
