Diagrama de Ishikawa y las 3 Mu como herramientas para el diagnóstico de la productividad

[EN] The purpose of this paper is to identify the factors that affect the productivity of a plastics company in Mexico, answering the question: What are the factors that decrease the productivity of the review and adjustment area in a plastics company? To achieve this, a case study methodology was u...

Descripción completa

Detalles Bibliográficos
Autores: Reyes Juárez, Liliana, Rivera González, Gibrán, Ángeles-Tovar, Luis Canek, Canós-Darós, Lourdes|||0000-0002-9609-2880, Castello-Sirvent, Fernando|||0000-0002-2088-0039
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:español
OAI Identifier:oai:dnet:riunet______::4b604f281d6deac575e4594367f59414
Acceso en línea:https://riunet.upv.es/handle/10251/234051
Access Level:acceso abierto
Palabra clave:Diagrama de Ishikawa
Las 3 Mu
Empresas de plásticos
Administración industrial
Productividad
Descripción
Sumario:[EN] The purpose of this paper is to identify the factors that affect the productivity of a plastics company in Mexico, answering the question: What are the factors that decrease the productivity of the review and adjustment area in a plastics company? To achieve this, a case study methodology was used, supported by the collection of quantitative and qualitative data based on interviews, observations, document review and company statistics. It was found that the problems causing low productivity in the company are found within six factors: material, labor, method, environment, measurement, machinery, and equipment. The main limitation is that it is research focused on a single company, but at the same time this gives greater value to the investigation by contributing knowledge regarding the usefulness offered by the combination of the 3 Mu tools and the Ishikawa diagram, used to make a productivity diagnosis. It is concluded that the research represents an important contribution on the use of industrial engineering tools to study productivity, thanks to its systematic approach, rigorous analysis, and detailed diagnosis.