Marcelus Fabri

In this work, we consider the internal logistics processes in the car assembling company SEAT S.A (where SEAT is Sociedad Española de Automóviles de Turismo). We focus on the design of the supplying routes from the warehouse toward the workstations along a production line. The in‐house logistics routing problem (ILRP) can be seen as an extension of the classical vehicle routing problem considering special features such as long‐term fixed routes, unknown orders, backorders, and homogeneous fleet. To solve the ILRP, we propose an integer linear programming (ILP) model and a simulation‐based iterated local search (SimILS) algorithm. We conduct two computational experiments. The first experiment analyzes the methods' performance, and the second experiment compares the SimILS results with the current company's routes, considering real data provided by SEAT S.A. The results show that the SimILS provides the best overall results overcoming both the ILP approach and the current company's solution, leading to a significant improvement in the company's processes.

This work focuses on internal logistics (IL), which is defined as the flows of materials inside the same business or the same plant. We centre on the IL activities of a car-assembling company. The main objective is to propose simulation models’ concepts that evaluate assembling lines under the IL point of view. We present a real case study based on SEAT S.A., a company in the Volkswagen group. We developed a Discrete-Event Simulation model through the Plant Simulation software. The company set the main Key Performance Indicators, which are related to the logistics flows’ performance (LFP) and an assembly lines’ aisles utilisation. The results expose which aisles are overused, the disturbs among the logistics flows, and the LFP, regarding the total of backorders, the trips duration, and the routes’ length in terms of distances and time. Moreover, we offer aset of best practices for further applications in that field.

This work aims to present a methodology to support a company in the automotive business on scheduling the jobs on its final processes. These processes are: (i) checking the final product and (ii) loading the dispatch trucks. These activities are usually found in the outbound area of any manufacturing company. The problem faced is defined as the flow shop problem with precedence constraints, release dates, and delivery times. The major objective is to minimize the latest date a client receives its products. We present a time-indexed integer mathematical model to compute feasible solutions for the presented problem. Moreover, we take advantage of the Lagrangean Relaxation procedure to compute valid lower and upper bounds. The experiments were held based on the company’s premises. As a conclusion, the results showed that the methodology proposed was able to compute feasible solutions for all the instances tested. Also, the Lagrangean Relaxation approach was able to calculate better bounds in a shorter computational time than the Mathematical problem for the more complicated instances.

In today's competitive market environment, logistics has a substantial impact on companies' performance. Improving the logistics efficiency is a main goal for many industries, especially, for those involved in car manufacturing. This work considers a real logistics problem in a car-assembly factory. The problem consists in optimizing the supply of components from the internal warehouse to the production lines, determining the best delivering routes. We describe the problem in detail, propose a mathematical programming model, and solve it with CPLEX. Afterward, to evaluate the impact of implementing the optimal routes in realistic scenarios, we apply Monte Carlo simulation and present a comparison between both solutions. The manufacturer's Key Performance Indicators are considered for evaluating the obtained results. The study showed that the proposed solution outperformed the current one, pointing out that the optimized routes could deal with different levels of production in a more efficient and cost reductive manner.