Developing and implementing a lean performance indicator: overall process effectiveness to measure the effectiveness in an operation process

Ng Corrales, Lisbeth del Carmen ; Lambán, María Pilar (Universidad de Zaragoza) ; Morella, Paula (Universidad de Zaragoza) ; Royo, Jesús (Universidad de Zaragoza) ; Sánchez Catalán, Juan Carlos ; Hernández Korner, Mario Enrique

Resumen: The purpose of this paper is to build up and implement a framework of a lean performance indicator with collaborative participation. A new indicator derived from OEE is presented, overall process effectiveness (OPE), which measures the effectiveness of an operation process. The action research (AR) methodology was used; collaborative work was done between researchers and management team participation. The framework was developed with the researchers’ and practitioners’ experiences, and the data was collected and analyzed; some improvements were applied and finally, a critical reflection of the process was done. This new metric contributes to measuring the unloading process, identifying losses, and generating continuous improvement plans tailored to organizational needs, increasing their market competitiveness and reducing the non-value-add activities. The OEE framework is implemented in a new domain, opening a new line of research applied to logistic process performance. This framework contributes to recording and measuring the data of one unloading area and could be extrapolated to other domains for lean performance. It was possible to generate and validate knowledge applied in the field. This study makes collaborative participation providing an effectiveness indicator that helps the managerial team to make better decisions through AR methodology. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Idioma: Inglés

DOI: 10.3390/machines10020133

Año: 2022

Publicado en: Machines 10, 2 (2022), [18 pp.]
ISSN: 2075-1702

Factor impacto JCR: 2.6 (2022)

Categ. JCR: ENGINEERING, MECHANICAL rank: 62 / 136 = 0.456 (2022) - Q2 - T2
Categ. JCR: ENGINEERING, ELECTRICAL & ELECTRONIC rank: 145 / 274 = 0.529 (2022) - Q3 - T2

Factor impacto CITESCORE: 2.1 - Engineering (Q3) - Mathematics (Q2) - Computer Science (Q3)

Factor impacto SCIMAGO: 0.449 - Computer Science (miscellaneous) (Q2) - Control and Systems Engineering (Q2) - Mechanical Engineering (Q2) - Electrical and Electronic Engineering (Q2) - Industrial and Manufacturing Engineering (Q2) - Control and Optimization (Q3)

Tipo y forma: Article (Published version)

Área (Departamento): Área Ing. Procesos Fabricación (Dpto. Ingeniería Diseño Fabri.)