Proposal of an activity allocation methodology considering a Scrum framework applied to multipe teams

Orientador: Robert Eduardo Cooper OrdoñezDissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia MecânicaResumo: O gerenciamento ágil de projetos é uma compilação de métodos utilizados inicialmente em projetos de desenvolvimento de softwares. Esses tipos de métodos têm ganhado destaque na última década e as aplicações se estendem para as mais diversas áreas, destancado-se dentre eles o método Scrum que é atualmente o mais disseminado. O método Scrum foi inicialmente concebido considerando cenários de equipes de projeto pequenas, porém, projetos grandes trazem a necessidade de escalar esse método considerando a sua aplicação em múltiplas equipes. Para enfrentar esse desafio, alguns métodos já foram criados, tal como o framework Less. Todavia, esses novos métodos ainda não conseguiram resolver o problema de alocação de atividades entre os times que participam de um dado projeto utilizando o método Scrum. Diante de tal cenário, o objetivo deste trabalho é propor uma metodologia de alocação de atividades entre equipes que participam de um mesmo projeto, envolvendo duas abordagens distintas buscando otimizar o tempo do projeto e respeitando as regras do método Scrum. A primeira abordagem consiste em uma proposta de algoritmo, seguido de uma heurística proposta e utilização de uma ferramenta de simulação computacional para descrever o algoritmo e implementá-lo, a qual utiliza a linguagem de programação Java e elementos de simulação de eventos discretos e agentes. A segunda abordagem trata de uma otimização, na qual se adaptou o problema clássico de alocação de máquinas de Kantorovich (1939) para alocação de equipes, considerando o conjunto de regras do Scrum. A simulação de cenários foi utilizada para validar os resultados das aplicações das duas abordagens, sendo que os mesmos se apresentaram como promissores para alocar de maneira ótima as equipes para um tempo mínimo de projetoAbstract: Agile project management is a compilation of methods used in software development projects. This type of method has gained prominence in the last decade and its application has been designed for the most diverse areas, among which the Scrum method is currently more widespread. This method was conceived considering small project team scenarios, but large projects bring the need to scale the Scrum method considering its application in several teams. To meet this challenge, some methods have already been created, such as the Less framework. However, these new methods have not yet been able to solve the activity allocation problem between teams when they participate in a given project using the Scrum method. The objective of this paper is to propose an activity allocation methodology between the teams participating in the same project, involving two different approaches, seeking to optimize the project progress and respect the rules of the Scrum method. The first approach consists of a proposed algorithm followed by a proposed heuristic and using a computational analysis tool to describe the algorithm that was implemented through Java programming language and event and agent simulation elements. The second approach was considered through optimization where the classic machine allocation problem of Kantorovich (1939) was adapted for team allocation considering the Scrum ruleset. Scenario simulations were used to validate both approaches, the results were considered as promising regarding optimal multi-team allocation in a minimum project timeMestradoMateriais e Processos de FabricaçãoMestre em Engenharia Mecânic

A manufacturing bottleneck case study trough the theory of constraints and computational simulation of the proposed bottleneck solution

In 2016, the Brazilian pet industry had revenue of R$ 18.9 billion and ranked third place worldwide. Thus, it is a sector that is always looking for enhancements in its productivity levels. Based on the previous statements, a case study was conducted in a selected company of the pet care business, with the goal to augment its monthly revenue, identify the bottleneck that impedes reaching this goal, and proposed solutions to bring the production and loading fluxes of merchandise to its optimal state, making the company’s revenue also optimal. The classical tools of the theory of constraints were used in this analysis. The first step was to obtain the undesirable effects of the process to define the bottleneck. After that, some injections were proposed as solutions to eliminate the undesirable effects and bring the production and loading model of the company to its full state. Finally, by means of a computational tool, the current situation of the company (with the bottleneck), and the situation in a virtual state (without the bottleneck) were simulated and compared, showing the potential of the found solution. 

Computational simulation applied in choosing the best solution in a product development using design for manufacturing and assembly approach

Highlights: The product development methodology aims to assist the planning and design of the product throughout its life cycle. Using selection criteria it is possible to choose a solution will be followed until the end of the development process and this process is known as optimization of product solutions. Design for Manufacturing and Assembly (DFMA) is an approach that allows selecting a product solution with better manufacturing and assembly performance. Computational modeling allows representing systems in virtual environment in order to reproduce its characteristics and to compare scenarios through simulation. Goal: The objective of this work was to apply the computer simulation to compare the productive performance, according to production times, productivity and resource utilization rate, of three solutions proposed for a raincoat for pets with thermal protection. Methodology: Initially, conceptual models representing the production systems for the three product solutions were generated. The systems were modeled in discrete event simulation software, enabling different scenarios testing, resulting in production performance indicators for each product solution. Results: The analysis of the performance indicators allow identifying that the third solution proposed for the product obtained the best productive performance in all proposed scenarios; therefore, it was chosen as the best solution for the product according to the DFMA approach. Limitations of the investigation: The application of the methodology indicated in this work was limited to the study of a single productive system of a specific product. Practical implications: This work presents a practical application of computer simulation tools applied to product development. Originality / Value: The original contribution of this work is the application of computational simulation of production systems in product development following the DFMA approach

Computational simulation applied in choosing the best solution in a product development using design for manufacturing and assembly approach

The product development methodology aims to assist the planning and design of the product throughout its life cycle. Using selection criteria it is possible to choose a solution will be followed until the end of the development process and this process is known as optimization of product solutions. Design for Manufacturing and Assembly (DFMA) is an approach that allows selecting a product solution with better manufacturing and assembly performance. Computational modeling allows representing systems in virtual environment in order to reproduce its characteristics and to compare scenarios through simulation. The objective of this work was to apply the computer simulation to compare the productive performance, according to production times, productivity and resource utilization rate, of three solutions proposed for a raincoat for pets with thermal protection. Initially, conceptual models representing the production systems for the three product solutions were generated. The systems were modeled in discrete event simulation software, enabling different scenarios testing, resulting in production performance indicators for each product solution. The analysis of the performance indicators allow identifying that the third solution proposed for the product obtained the best productive performance in all proposed scenarios; therefore, it was chosen as the best solution for the product according to the DFMA approach. The application of the methodology indicated in this work was limited to the study of a single productive system of a specific product. This work presents a practical application of computer simulation tools applied to product development. The original contribution of this work is the application of computational simulation of production systems in product development following the DFMA approach15461862