Browsing by Author "Zanella, Fernando"
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- Modeling an aggregate production planningPublication . Zanella, Fernando; Vaz, Clara B.Production planning is an essential and complex activity inside any company which requires simultaneous cooperation between everyone responsible for the decision-making process. Most of the time, small companies cannot afford to customize, implement and train people to use an Advanced Planning and Scheduling (APS) software that is available in the market. Thus, one feasible soluion for these companies is to develop their own simplified tools to support the decision-making process. When solving problems involving medium-term planning, more specifically aggregate production planning, it is possible to create an integer linear programming (LP) mathematical model and use it to find the optimal solution.
- Modeling an aggregate production planningPublication . Zanella, Fernando; Vaz, Clara B.This paper aims to present and discuss the benefits that small- and medium-sized companies can get when using mathematical programming to help in the decision-making process regarding aggregate production planning. The aggregate plan is concerned with determining the quantity of a good or a family of goods to be produced and also scheduling its production for the medium-range period, in which the main objective is to meet forecast demand while minimizing costs. To exemplify an aggregate production planning problem, a simplified model of a real company, considering four months, was proposed. Future developments should improve the model to consider other data such as inventory management and costs; raw material storage and logistics; employee costs, contracting and subcontracting and overtime.
- Sustainable production planning optimization using integer programmingPublication . Zanella, Fernando; Vaz, Clara B.This paper presents how integer linear programming can be used to optimize and develop a sustainable production plan for a medium-sized cold stamping company. The objective is to develop a model to minimize the total production cost, which includes the manufacturing process cost, inventory holding cost, and unproductive machine cost. The model takes into account weekly demands, inventory levels, and idle machine time during a planning horizon of one month. The output is a plan containing all products that have to be manufactured, their weekly optimal quantities, and a prediction of the final inventory level. By minimizing the total production cost, the model ensures that the company is consuming only the necessary amount of resources. The mathematical model is related to the real-world constraints that are part of the company’s production scenario, reflecting both direct and indirect impacts of resource usage. This model enables to simulate three scenarios, and their results indicate that the total production cost is minimum when a company produces in volumes slightly greater than the demand. By better allocating resources, the company can contribute to sustainability in the context of responsible production.
- Sustainable short-term production planning optimizationPublication . Zanella, Fernando; Vaz, Clara B.This study proposes a framework for short-term production planning of a Portuguese company operating as a tier 2 supplier in the automotive sector. The framework is intended to support the decision-making process regarding a single progressive hydraulic press, which is used to manufacture cold-stamped parts for exhaust systems. The framework consists of two sequential levels: (1) a Mixed-Integer Linear Programming (MILP) model to determine the optimal production quantities per week while minimizing the total cost; (2) a dynamic production sequencing rule for scheduling operations on the hydraulic press. The two levels are combined and implemented in Excel, where the MILP model is solved using the Solver add-in, and the second level uses the optimal production quantities as inputs to determine the production sequence using a dynamic priority rule. To validate the framework, a proposed optimal plan was compared to a real plan executed by the company, and it was found that the framework could save up to 22.1% of the total cost observed in reality while still satisfying demand. To address uncertainties, the framework requires a rolling weekly planning horizon.
- Two-level hierarchical framework for short-term production planning and schedulingPublication . Zanella, Fernando; Vaz, Clara B.; Trentin, Robson GonçalvesThis study aims to develop a two-level hierarchical production planning framework for a medium-sized Portuguese company that operates as a tier 2 supplier within the automotive production supply chain. The framework is designed to assist the decision-making process during the short-term planning of four progressive hydraulic presses used to produce cold-stamped parts for exhaust systems. The two hierarchical levels of the framework are: (i) a Mixed-Integer Linear Programming (MILP) model to determine the optimal quantities to be produced in a single machine while minimizing the total costs; and (ii) a dynamic production sequencing rule that defines the machine schedule based on three criteria that are relevant for the company. Both framework levels have been combined and implemented in Excel; in the first level, the MILP model is solved using the add-in Solver; then, the second level uses the optimal quantities to be produced as inputs to determine the production sequence through a mathematical procedure. The spreadsheet features a dashboard for intuitive use and presentation of results. The framework was validated by comparing it to a real plan executed by the company, and it was found that the plan proposed by the framework could save up to 20,6% of the total cost observed in reality. The framework requires a week-to-week rolling planning horizon in order to absorb uncertainties.