José Arnaldo Barra Montevechi

Application of design of experiments on the simulation of a process in an automotive industry

The objective of this article is to apply the Design of experiments technique along with the Discrete Events Simulation technique in an automotive process. The benefits of the design of experiments in simulation include the possibility to improve the performance in the simulation process, avoiding trial and error to seek solutions. The methodology of the conjoint use of Design of Experiments and Computer Simulation is presented to assess the effects of the variables and its interactions involved in the process. In this paper, the efficacy of the use of process mapping and design of experiments on the phases of conception and analysis are confirmed.

Conceptual modeling in simulation projects by mean adapted idef: an application in a brazilian tech company

Several process modeling techniques have been used in simulation projects. However, most of these techniques provide little specific support to the programming. The main cause of this is the fact that these techniques were not developed with the same logic used in simulation models. From this issue, this paper presents an industrial application of a new conceptual modeling technique, named IDEF-SIM (Integrated Definition Methods - Simulation) currently under development by the authors. This adapted IDEF uses logic elements present in techniques such as IDEF0 and IDEF3, but in a way that is similar to the process interpretation logic usually used in simulation projects. This way, it can be noticed an increase in the conceptual models utility, which might facilitate the simulation model programming, verification and validation and the scenarios creation. Additionally, the paper presents the benefits of using IDEF-SIM to create the conceptual model of a Brazilian tech company manufacturing cell.

Perspectives and relationships in Supply Chain Simulation: A systematic literature review

Abstract The main purpose of this article is to develop a meta-analysis about the relationships and potential perspectives of modeling and simulation in supply chains. The research methodology used in this paper was a systematic literature review, exploring the state of the art in Supply Chain Simulation. The methodological procedures were based on a systematic literature review and statistical analysis of a sample of papers. The results indicated that modeling and simulation in supply chains can be better integrated. The models could be more sophisticated to capture the dynamics and behavior of these networks. The combination of optimization methods with agent-based simulation is an observed trend. Hybrid simulations involving normative models and empirical applications can be useful to represent the reality of supply chains, generating alternative solutions that improve supply chain performance. The relevance of this article is to analyze the interfaces related to this field of research, in order to establish a theoretical framework that improves the process of modeling, simulation and decision-making in supply chains.

Combined use of modeling techniques for the development of the conceptual model in simulation projects

The objective of this paper is to utilize the SIPOC, flow-chart and IDEF0 modeling techniques combined to elaborate the conceptual model of a simulation project. It is intended to identify the contribution of these techniques in the elaboration of the computational model. To illustrate such application, a practical case of a high-end technology enterprise is presented. The paper concludes that the proposed approach eases the elaboration of the computational model.

A practical guide for operational validation of discrete simulation models

As the number of simulation experiments increases, the necessity for validation and verification of these models demands special attention on the part of the simulation practitioners. By analyzing the current scientific literature, it is observed that the operational validation description presented in many papers does not agree on the importance designated to this process and about its applied techniques, subjective or objective. With the expectation of orienting professionals, researchers and students in simulation, this article aims to elaborate a practical guide through the compilation of statistical techniques in the operational validation of discrete simulation models. Finally, the guides applicability was evaluated by using two study objects, which represent two manufacturing cells, one from the automobile industry and the other from a Brazilian tech company. For each application, the guide identified distinct steps, due to the different aspects that characterize the analyzed distributions

A New Approach to Reducing Search Space and Increasing Efficiency in Simulation Optimization Problems via the Fuzzy-DEA-BCC

The development of discrete-event simulation software was one of the most successful interfaces in operational research with computation. As a result, research has been focused on the development of new methods and algorithms with the purpose of increasing simulation optimization efficiency and reliability. This study aims to define optimum variation intervals for each decision variable through a proposed approach which combines the data envelopment analysis with the Fuzzy logic (Fuzzy-DEA-BCC), seeking to improve the decision-making units’ distinction in the face of uncertainty. In this study, Taguchi’s orthogonal arrays were used to generate the necessary quantity of DMUs, and the output variables were generated by the simulation. Two study objects were utilized as examples of mono- and multiobjective problems. Results confirmed the reliability and applicability of the proposed method, as it enabled a significant reduction in search space and computational demand when compared to conventional simulation optimization techniques.

Integrating soft systems methodology to aid simulation conceptual modeling

Discrete-event simulation is considered an increasingly common support tool for decision making, especially in manufacturing. Most simulation projects are divided into three distinct phases: conception, implementation, and analysis. Some authors believe the conception phase is the most important, as the simulation study objectives are defined and the projects foundation is laid at this point. Many researchers do not spend the necessary amount of time on this important initial phase. Thus, this article presents an integration method that makes use of soft systems methodology (SSM), a complex problem-solving approach, during the conceptual phase of simulation studies. SSM was used throughout the conceptual modeling phase for a real manufacturing simulation case study. Through the analysis of this study, it can be concluded that the use of SSM to develop the conceptual model enabled identification of the study objectives, thus avoiding errors and reworks. The studys results are presented and the methods application is justified by presenting a valid model capable of analyzing the systems key input variables.

Sensitivity analysis in discrete-event simulation using fractional factorial designs

This paper presents a sensitivity analysis of discrete-event simulation models based on a twofold approach formed by Design of Experiments (DOE) factorial designs and simulation routines. This sensitivity analysis aim is to reduce the number of factors used as optimization input via simulation. The advantage of reducing the input factors is that optimum search can become very time-consuming as the number of factors increases. Two cases were used to illustrate the proposal: the first one, formed only by discrete variable, and the second presenting both discrete and continuous variables. The paper also shows the use of the Johnsons transformation to experiments with non-normal response variables. The specific case of the sensitivity analysis with a Poisson distribution response was studied. Generally, discrete probability distributions lead to violation of constant variance assumption, which is an important principle in DOE. Finally, a comparison between optimization conducted without planning and optimization based on sensitivity analysis results was carried out. The main conclusion of this work is that it is possible to reduce the number of runs needed to find optimum values, while generating a system knowledge capable to improve resource allocation.

Interactive learning of modeling and discrete-events simulation through Lego® parts

A discrete-events simulation course should develop in its students not only the abilities related to the programming language and statistical analysis, but also the ability to create an abstract of a real system into a model system. Thus, this paper has the objective to develop and evaluate an educational dynamic project for discrete event simulation courses, which are capable of developing the students ability to perform abstraction and representation of real systems in a conceptual and computational model. To meet this objective, Lego® was used in the educational dynamic. For the evaluation of the motivation presented by the students in the dynamic, the ARCS (Attention, Relevance, Confidence, Satisfaction) technique was used together with an Instructional Materials Motivational Survey (IMMS) questionnaire. An indicator was established to measure the students utilization and/or knowledge gained. The results demonstrate that the dynamic reached its objective, presenting a high utilization in the motivational criteria analyzed.

Aplicação de programação por metas binária: mista em uma empresa do setor sucroenergético

The Goal Programming (GP) is an important analytical approach that has been successfully applied in relevant real-world decision making problems. This paper proposes a Mixed-Binary Goal Programming (MBGP) model to optimize production and distribution planning of a energy cogeneration sugar and ethanol milling company. Therefore, the MBGP model integrates the production process of sugar, alcohol, molasses, and energy cogeneration, and it enables decision-making in the agricultural, industrial, and distribution phases on a weekly-basis planning horizon including the harvest season and the periods between harvests. The model was applied in a Brazilian sugar and ethanol milling company, and it contributed to the formulation of production and distribution optimum policies yielding good financial and operational results in addition to raising energy export in conformity with the reality of the plant.