Browsing by Author "Tortorella, Guilherme Luz"

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    Digitalization of maintenance: exploratory study on the adoption of Industry 4.0 technologies and total productive maintenance practices
    (TAYLOR & FRANCIS LTD, 2022) Tortorella, Guilherme Luz; Saurin, Tarcisio Abreu; Fogliatto, Flavio Sanson; Mendoza, Diego Tlapa; Moyano-Fuentes, Jose; Gaiardelli, Paolo; Seyedghorban, Zahra; Vassolo, Roberto; Vergara, Alejandro F. Mac Cawley; Sunder, Vijaya M.; Sreedharan, V. Raja; Sena, Santiago A.; Forstner, Friedrich Franz; de Anda, Enrique Macias
    This paper analyzes the joint adoption of Industry 4.0 (I4.0) technologies and Total Productive Maintenance (TPM) practices in manufacturing firms. For that, we surveyed 335 practitioners from firms currently implementing TPM and I4.0, located in sixteen countries. The collected dataset was analyzed using sets of partial correlation analyses, obtained when controlling the effect of three contextual variables, all assessed at the firm level: (i) socio-economic context, (ii) technological intensity, and (iii) size. Pairs of TPM practices and I4.0 technologies with significant positive correlations in all partial correlation sets indicate positive trends in the adoption of elements in the pairs, regardless of context, and may be viewed as indicators of TPM practices and I4.0 technologies more prone to be integrated. Our results identified 67 pairs of I4.0 technologies and TPM practices meeting the significance criterion. Four TPM practices (fostering operator ownership, standardization of AM checks, setting 3M-machine/man/material-conditions, and constant search for the next generation of technology) and two I4.0 technologies (Internet-of-Things, and big data) appeared in 26 of the 67 pairs. The study unveiled trends in the integration of I4.0 and TPM, pointing to pairs whose joint adoption is predominant and indicating pathways to the digitalization of maintenance.
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    Healthcare costs' reduction through the integration of Healthcare 4.0 technologies in developing economies
    (ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2020) Tortorella, Guilherme Luz; Fogliatto, Flavio Sanson; Esposto, Kleber Francisco; Mac Cawley, Alejandro Francisco; Vassolo, Roberto; Tlapa, Diego; Narayanamurthy, Gopalakrishnan
    This study aims at examining the effect of Healthcare 4.0 (H4.0) implementation on healthcare costs' reduction in hospitals located in developing economies. For that, 159 middle and senior leaders from hospitals located in Brazil, India, Mexico and Argentina were surveyed regarding their adoption level of H4.0 technologies and cost reduction improvements. Responses were analysed using multivariate data analysis techniques. Our findings indicate that the adoption of H4.0 technologies, empirically grouped into two different bundles (Sensing-Communication and Processing-Actuation), is positively related to healthcare costs' reduction and that the extent of such relationship may vary according to the bundle under analysis. Our results elucidate the impact of digital integration on healthcare costs, suggesting a cost-effective path based on H4.0 implementation. The identification of this relationship in hospitals located in developing economies evidences the benefits of healthcare digital transformation despite the challenging socioeconomic conditions, which has been contradictorily reported in previous studies.
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    How does artificial intelligence impact employees' engagement in lean organisations?
    (Taylor & Francis Ltd., 2024) Tortorella, Guilherme Luz; Powell, Daryl; Hines, Peter; Mac Cawley Vergara, Alejandro Francisco; Tlapa-Mendoza, Diego; Vassolo, Roberto
    Driven by the digital transformation currently pursued by organisations, artificial intelligence (AI) applications have become more frequent. Nevertheless, its impact on employees' behaviors and attitudes is still poorly known. As employees' engagement (EE) is a key element for a successful Lean Production (LP) implementation, there is the need to understand such AI's implications on EE in this scenario. This paper aims to investigate the impact of AI on EE in lean organisations. We performed a qualitative-empirical approach in which we first interviewed twelve academic experts to grasp the investigated problem. Then, we conducted a multi-case study in manufacturing organisations undergoing a LP implementation to refine such understanding based on the observation of real-world evidence. Identifying commonalities between these stages allowed the formulation of propositions for future theory testing and validation. Findings indicate that AI may positively impact EE dimensions (physical, cognitive, and emotional) in human-centred work environments, such as lean organisations, although not at the same extent. Results also suggest that employees' psychological conditions (safety, meaningfulness, and availability) are positively affected by the relationship between AI and EE. The demystification of AI's effect on EE helps practitioners anticipate potential issues that can impair the LP implementation in the Fourth Industrial Revolution era.
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    Implementing a material planning and control method for special nutrition in a Brazilian public hospital
    (WILEY, 2021) Alemsan, Najla; Tortorella, Guilherme Luz; Mac Cawley Vergara, Alejandro Francisco; Taboada Rodriguez, Carlos Manuel; Staudacher, Alberto Portioli
    This study aims to (i) propose a demand forecast model for special nutrition materials in the context of health services, and (ii) comparatively evaluate three inventory management and control systems (periodic review, continuous review and mixed) for special nutrition materials. For that, we carried out a case study in a Brazilian public teaching hospital where data and information collection were conducted over a span of 22 months (from January 2018 and were consolidated until October 2019). A six-step approach was followed to propose the demand forecasting models and, later, evaluate the inventory control systems for special nutrition materials. Results indicate that if the organization implements the proposed inventory management method, there could be savings of up to 33% in the stock values managed by the healthcare organization. This research shows the planning and control of special nutrition materials in an integrated manner. Demand forecasting methods have been combined with inventory management to promote systemic improvements to healthcare organization.