Guilherme Tortorella, Tarcisio Abreu Saurin, Flavio Sanson Fogliatto, Diego Tlapa, José Moyano-Fuentes, Paolo Gaiardelli, Zahra Seyedghorban, Roberto Vassolo, Alejandro Francisco Mac Cawley, Vijaya Sunder M, V. Raja Sreedharan, Santiago Alfredo Sena and Friedrich Franz Forstner
In this paper, the authors examine the impact of Industry 4.0 (I4.0) technologies on the relationship between total productive maintenance (TPM) practices and maintenance…
Abstract
Purpose
In this paper, the authors examine the impact of Industry 4.0 (I4.0) technologies on the relationship between total productive maintenance (TPM) practices and maintenance performance.
Design/methodology/approach
Data collection was carried out through a multinational survey with 318 respondents from different manufacturing companies located in 15 countries. Multivariate data techniques were applied to analyze the collected data. Diffusion of innovations theory (DIT) was the adopted theoretical lens for our research.
Findings
The authors’ findings indicate that I4.0 technologies that aim to process information to support decision-making and action-taking directly affect maintenance performance. Technologies oriented to sensing and communicating data among machines, people, and products seem to moderate the relationship between TPM practices and maintenance performance. However, the extent of such moderation varies according to the practices involved, sometimes leading to negative effects.
Originality/value
With the advances of I4.0, there is an expectation that several maintenance practices and performance may be affected. Our study provides empirical evidence of these relationships, unveiling the role of I4.0 for maintenance performance improvement.
Details
Keywords
Gabriel Vidor, Janine Fleith de Medeiros, Flavio Sanson Fogliatto and Mitchel M. Tseng
– This paper aims to propose a method to determine which mass customization (MC) characteristics should be prioritized in mass-customized service design.
Abstract
Purpose
This paper aims to propose a method to determine which mass customization (MC) characteristics should be prioritized in mass-customized service design.
Design/methodology/approach
Looking at manufacturing MC systems and conducting a literature review, it is not possible to observe a methodological step to define customized service design as the one we propose in this work. Results show a systematic classification of MC characteristics based on MC enablers and service enablers. These enablers are related by a quality function deployment (QFD) matrix and rewritten using a reverse QFD procedure.
Findings
In the end, it was possible to determine which characteristics should be prioritized in mass-customized services.
Research limitations/implications
Two case studies were performed: one with an electric power supplier and another one with a university.
Practical implications
It shows that despite easy customization, organization is not always interest in service features customization. The explanation in these two cases is customization cost, which compared to the benefit does not seem advantageous for the organization.
Originality/value
This paper creates a methodology to design a first phase in customized services in Latin American services and that is the original contribution.