Análise de indicadores da gestão de produção em obras corporativas

• Ano de defesa: 2019
• Autor(a) principal: Leiza Silva Mergh
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Planejamento e controle da produção; Last planner; Desvio de prazo; Desvio de custo; Desvio de ritmo; Planejamento; Indicadores; Construção civil; Construção civil Custos
• Link de acesso: http://hdl.handle.net/1843/RAOA-BEKRNF

The improvement in the civil construction field has been the object of studies and efforts in the last 20 years, and the role of the Production Planning and Control Process (PCP) system is to provide information and models for efficient resource management, focusing on strategies for improvement of productivity and generating value through competitive priorities such as cost, quality, flexibility, executive sequencing and security. One of the most important tools of the PCP is the Last Planner System (LPS), commonly used in manufacturing industries, and its main indicator is the Percent Plan Complete (PPC). Another planning indicator is the Rhythm Deviation (RD) that identifies possible delays of the activities in relation to the planned. In addition, it is common to measure performance to control outcomes and the most commonly used indicators are Time Deviation (TD) and Cost Deviation (CD). The present study analyzes the correlations between the planning indicators, PPC and RD and the indicators of performance, TD and CD, in two projects with 22 and 21 months of cycle. Analyzes of the characteristics of each construction were performed, in addition to the statistical analysis of correlation, simple linear regression, quadratic and cubic regression and multiple regression, in order to obtain practical equations between the indicators and statistical proof of the relations between the variables. It was verified that there is a correlation between the variables involved and it was verified the influence that each indicator exerts on the performance of the other, being able to prove that TD is very influenced by the RD and that the PPC exerts influence in the results of the CD, TD and RD. In the multiple regression tests the most significant results were found in the equations where all the variables appeared. As a main conclusion, it is pointed out that the values obtained in the regression tests suggest that other variables besides PPC and RD, not considered in this analysis, influence the values of the indicators CD and TD.