Flavio Sanson Fogliatto

• Ph.D.
• Professor (Full) at Federal University of Rio Grande do Sul

This paper proposes a method for designing choice menus for mass customization (MC). The method is based on the analysis of stated preferences (SP) on product or service attributes obtained through panel studies. The method is first presented, and then illustrated with a real world case application in a natural gas (NG) distribution company. The ca...

In some industries, such as food processing, product performance is assessed with multiple criteria including both quantitative measurements and subjective characteristics evaluated by a sensory panel. A sensory panel consists of trained individuals who compare products yielding data often in the form of matrices of paired comparisons. This paper p...

The implementation of lean production systems is deemed essential for companies that wish to obtain high levels of competitiveness. There are several examples in the literature discussing the adoption of lean roadmaps; however, since such maps emphasise technical factors of lean change, the organisational learning (OL) process and human resources m...

The massive amount of data collected from industrial processes has challenged researchers and practitioners, turning variable selection into a research topic of interest both in academia and in industry. The use of redundant, irrelevant, and noisy variables tends to compromise the performance of many statistical tools, leading to unreliable inferen...

This paper aims at examining the trends, challenges and theoretical gaps in the implementation of Healthcare 4.0 (H4.0) based on a scoping review of the literature. For that, we searched journal articles in four widely known databases and screened the retrieved articles to obtain a publications’ portfolio. Our findings indicate that, despite the re...

Purpose Smart farming (SF) holds immense potential in making farming viable and improving farmers' livelihoods. However, its adoption is still in the early stages, and the resulting impacts are underexplored. This study investigates the information systems/policy and implementation barriers to the adoption of SF and its implications for various soc...

This research examines the mediating role of resilience abilities development on the effect of Lean Production (LP) implementation on manufacturers' operational performance during the COVID-19 pandemic. A survey with 216 practitioners from different Australian companies was conducted, assessing their level of LP implementation, resilience developme...

Background Emergency department (ED) overcrowding is an important problem in many countries. Accurate predictions of ED patient arrivals can help management to better allocate staff and medical resources. In this study, we investigate the use of calendar and meteorological predictors, as well as feature-engineered variables, to predict daily patien...

We propose a method to assess companies' ability to cope with different types of disruptive events by developing resilience capabilities through Lean Production (LP) implementation. We use direct and reverse mathematical operations with two expert opinion-based matrices mapping relationships between LP practices and resilience capabilities, and res...

This study aims to investigate the relationship between resilience development and digital transformation (DT) and its effect on food supply chain (FSC) performance. A survey of 208 practitioners in the Australian FSC was conducted, and the collected data was analyzed using multivariate data analysis techniques. Findings suggest a positive impact o...

To present the social network analysis-based approach used to create a new workspace layout for three hospital services as part of a campus expansion at a large tertiary care public hospital. To analyze the relationships among service members across four healthcare resilience abilities (monitor, anticipate, respond, and learn) and utilize network m...

BACKGROUND Studies reveal healthcare disparities for people with disabilities (PwD) due to various barriers. Digital health offers promise but raises concerns about the digital divide. To address that, health Information and Communication Technologies (ICTs) should follow inclusive design principles for accessibility to all, including PwD. OBJECTI...

Purpose This study aims to explore the relationship between digital transformation and resilience development in the Australian food supply chain (FSC), and identify the contribution of digital technologies to it using the dynamic capabilities theory as theoretical lens. Design/methodology/approach For that, a mixed-method approach was used. It co...

Background Emergency department (ED) overcrowding is an important problem in many countries. Accurate predictions of patient arrivals in EDs can serve as a management baseline for better allocation of staff and medical resources. In this article, we investigate the use of calendar and meteorological predictors, as well as feature engineered variabl...

Background No-show to medical appointments has significant adverse effects on healthcare systems and their clients. Using machine learning to predict no-shows allows managers to implement strategies such as overbooking and reminders targeting patients most likely to miss appointments, optimizing the use of resources. Methods In this study, we prop...

Help Chain (HC) is a problem-solving practice underpinned by lean manufacturing principles and also adopted for health services, which have different complexity characteristics in relation to manufacturing. This study is based on the premise that Social Network Analysis (SNA) might be an effective analytical approach to account for the complexity o...

The Brazilian electricity market is in the liberalization phase, and residential consumers are not yet allowed to access the free energy grid, having only the option of buying energy from the regulated market at government-regulated tariffs. This study investigates the barriers that hinder the liberalization of the free energy market in Brazil, the...

The management of hospitals' resource capacity has a strong impact on the quality of care, and the length-of-stay (LOS) of patients is an indicator that reflects its efficiency and effectiveness. This study aims at predicting the LOS of pediatric patients (LOS-P) in hospitals to assist in decision-making regarding resource utilization. LOS-P foreca...

The extra effort of healthcare professionals to provide care is a manifestation of resilient performance (RP), usually going unnoticed due to successful outcomes. However, it is not clear how the human cost of RP can be assessed. This study addresses this gap by investigating the relationships between proxies of RP and its human cost. The proposed...

This research investigates the mediation of resilience abilities on the relationship between Industry 4.0 technologies adoption and healthcare supply chain performance during the COVID-19 outbreak in Brazil and India. We surveyed 179 practitioners from organizations at different tiers of the healthcare supply chain (e.g., manufacturers, distributor...

This study examines how Industrial Engineering postgraduate programs intend to develop the competencies required for Industry 4.0 in their students. An exploratory and descriptive approach was adopted. Multiple sources of evidence were collected in four of Brazil's best-ranked and most traditional Industrial Engineering postgraduate programs, invol...

Wavelength selection is an important step in NIR data analysis as it yields more robust and accurate models for predicting products’ properties. This paper proposes a novel framework for wavelength selection in Partial Least Squares (PLS) models based on the absorbance interquartile range. The framework first divides samples into quartiles accordin...

This study aimed at identifying applications of learning curve (LC) modeling at individual, group, and organizational levels in Industry 4.0 (I4.0) environments. For that, a scoping review on four databases was conducted using the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guideline...

This study examines the effect of Industry 4.0 (I4.0) technologies adoption on the learning process of operators modeled by learning curves. We collected data from the training of new operators in a quality inspection workstation of an auto parts manufacturer. Two distinct scenarios were considered: before and after the adoption of I4.0 technologie...

In this paper, we examine the impact of adopting Industry 4.0 (I4.0) base technologies on the development of seven learning dimensions used as proxies for organization learning capabilities. We conducted a grounded theory approach in which 129 practitioners from different manufacturing companies were surveyed, and their responses analyzed through m...

Purpose This paper aims to examine the moderating effect of Industry 4.0 (I4.0) technologies on the relationship between socio-technical (ST) practices and workers' health, quality and productivity performance. Design/methodology/approach In this paper, 192 practitioners from different manufacturing firms adopting I4.0 technologies were surveyed,...

Improved flexibility, digitalization and informatization introduced by the he Fourth Industrial Revolution (or I4.0) has induced changes in the arrangement and execution of production scheduling (PS) activities. Prior research in this field is in the form of computational experiments specific to PS problem, while little is known about how digital c...

Despite the increasing utilization of lean practices and digital technologies (DTs) related to Industry 4.0, the impact of such dual interventions on healthcare services remains unclear. This study aims to assess the effects of those interventions and provide a comprehensive under-standing of their dynamics in healthcare settings. The methodology c...

Background: Patients' no-shows negatively impact healthcare systems, leading to resources' underutilisation, efficiency loss, and cost increase. Predicting no-shows is key to developing strategies that counteract their effects. In this paper, we propose a model to predict the no-show of ambulatory patients to exam appointments of computed tomograp...

This paper aims to identify bundles of Healthcare 4.0 (H4.0) digital applications and measure the impacts of their adoption on patient-centered performance. We conducted an empirical-exploratory study based on a survey with 119 middle/senior managers from different hospitals. Multivariate data techniques were applied to identify the H4.0 bundles, c...

This paper examines the impact of Industry 4.0 (I4.0) technologies on employees workload in contact centers. For that, we adopted the NASA task load index (TLX) questionnaire to assess the workload of 100 employees from different contact centers in India that have been adopting I4.0 technologies. The collected data is analyzed through multivariate...

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, obtai...

Although resilience benefits from social interactions, there is a gap regarding the identification of key players that contribute to it. This study uses social network analysis (SNA) to identify those players based on the modeling of interactions associated with four abilities of resilient systems: monitor, anticipate, respond, and learn. Networks...

Purpose Healthcare supply chains (HSCs) have been adopting Industry 4.0 (I4.0) as a means to boost their resilience. The first objective of this study is to identify the effect of contextual variables of HSCs on resilience development and I4.0 adoption. Second, the paper examines the pervasiveness of the relationship between resilience and I4.0 acr...

Health organizations have adopted technologies since the 1960s, but only after the Industry 4.0 were such technologies systematized and organized under the H4.0 acronym. The pace at which digital information and communication applications have been developed in recent years challenge healthcare managers to choose assertively those with the largest...

Peaks in patients’ demand for inward hospitalization usually lead to disruptions in the provision of healthcare, having negative effects on patient and staff satisfaction. The two main sources of ward bed demand are the emergency department and the surgical center; while the former is random by nature, the latter may be managed through proper alloc...

Purpose We investigate the experience of pediatric oncology patients with objects and equipment involved in laboratory and image exams during hospitalization for cancer treatment while generating guidelines for playful interventions to improve their subjective wellbeing. Method The study was carried out at a public tertiary referral teaching hospi...

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 locate...

We propose a method to collect data on user requirements of medical equipment shared by different users and services, relate those requirements with the equipment's technical features, and rank the most important features to be considered when procuring the equipment, leading to more effective procurement decision making. Our method is structured i...

Background We propose a mathematical model formulated as a finite-horizon Markov Decision Process (MDP) to allocate capacity in a radiology department that serves different types of patients. To the best of our knowledge, this is the first attempt at considering radiology resources with different capacities and individual no-show probabilities of a...

Forecasting of attendance demand to sports events is a common topic of study in the sports economics literature, being traditionally addressed through the use of multivariate regression analysis or structural equation modeling. In recent years, a restricted number of authors have approached the problem using machine learning methods, with promising...

Background Healthcare management faces complex challenges in allocating hospital resources, and predicting patients’ length-of-stay (LOS) is critical in effectively managing those resources. This work aims to map approaches used to forecast the LOS of Pediatric Patients in Hospitals (LOS–P) and patients’ populations and environments used to develop...

Near Infrared (NIR) is a type of vibrational spectroscopy widely used in different areas to characterize substances. NIR datasets are comprised of absorbance measures on a range of wavelengths (λ). Typically noisy and correlated, the use of such datasets tend to compromise the performance of several statistical techniques; one way to overcome that...

In this paper, we examine the contributions of digital applications to the resilience of healthcare organizations during the COVID-19 outbreak. The studied applications are framed as Healthcare 4.0 (H4.0), comprising bundles of information and communication technologies used to improve operations in the health value chain. Data collection was carri...

Purpose This study aims at identifying the contribution of Industry 4.0 (I4.0) integration into supply chains (SCs) to the enhancement of SC resilience. Design/methodology/approach A scoping review was conducted so that the relevant literature on SC resilience, and I4.0 integrated into SC management was examined. Findings The authors summarize th...

Information and communication technologies (ICTs) are known for supporting healthcare services in dealing with adverse situations. However, little is known on the contribution of ICTs in a prolonged catastrophic crisis involving a new disease, such as the COVID-19 pandemic. In this study, we carry out an exploratory investigation of which ICTs cont...

Background: Alternative approaches to analyzing and evaluating health care investments in state-of-the-art technologies are being increasingly discussed in the literature, especially with the advent of Healthcare 4.0 (H4.0) technologies or eHealth. Such investments generally involve computer hardware and software that deal with the storage, retriev...

Total Productive Maintenance (TPM), an important maintenance management approach grounded on lean principles, has found widespread applicability in the manufacturing sector since the 1950's. More recently, Industry 4.0 (I4.0) has promoted the digitalization of several functional areas bringing disruptive innovation to manufacturing environments. Th...

Descriptions of resilient performance in healthcare services usually emphasize the role of skills and knowledge of caregivers. At the same time, the human factors discipline often frames digital technologies as sources of brittleness. In this paper, we explore the upside of digital technologies derived from Healthcare 4.0 (H4.0) in terms of their c...

Resilient performance is influenced by social interactions of several types, which may be analysed as layers of interwoven networks. The combination of these layers gives rise to a “network of networks”, also known as a multilayer network. This study presents an approach to develop and interpret multilayer networks in light of resilience engineerin...

This study proposes a problem-oriented methodology, using the algebraic operations proposed in the Quality Function Deployment’s house-of-quality, to prioritize the integration of Industry 4.0 (I4.0) technologies in hospitals, allowing us to account for both the importance of healthcare value chain problems and the current level of adoption of I4.0...

In some projects, professionals face problems in designing a product that force them to deal with uncertainties in a creative way; in others, they follow structured guidelines and rely on preexisting knowledge. In this paper, we map thinking styles (conditional, creative, exploring, independent, inquiring) used by professionals with different acade...

Radiology service managers search for efficient ways to monitor productivity and improve capacity. One way to assess radiologists' productivity is by measuring their time to complete reports. Radiology reporting times (RRTs) may be monitored using statistical tools, such as process control charts (CCs). This study was carried out in the radiology s...

Purpose There are no criteria to establish priority for bariatric surgery candidates in the public health system in several countries. The aim of this study is to identify preoperative characteristics that allow predicting the success after bariatric surgery. Materials and Methods Four hundred and sixty-one patients submitted to Roux-en-Y gastric b...

Background: Healthcare management faces complex challenges in allocating hospital resources and predicting patients' length-of-stay (LOS) is critical in effectively managing those resources. This work aims to identify approaches used to forecast the LOS of Pediatric Patients in Hospitals (LOS–P), and patients' populations and environments used to d...

Background Surgical Tray Rationalization (STR) consists of a systematic reduction in the number of surgical instruments to perform specific procedures without compromising patient safety while reducing losses in the sterilization and assembly of trays. STR is one example of initiatives to improve process performance that have been widely reported i...

Healthcare 4.0 (H4.0) adapts principles and applications from the Industry 4.0 movement to healthcare, enabling real-time customization of care to patients and professionals. As such, H4.0 can potentially support resilient performance in healthcare systems, which refers to their adaptive capacity to cope with complexity. This paper explores the imp...

UNSTRUCTURED This paper examines the trends, challenges, and theoretical gaps in Healthcare 4.0 (H4.0) technologies in hospital investment decisions. For that, we searched journal articles in four widely known databases and screened the retrieved documents to obtain a publications’ portfolio. Our findings show the multidisciplinary source of resear...

Background Surgical Tray Rationalization (STR) consists of a systematic reduction in the quantity of surgical instruments to perform specific procedures without compromising patient safety, while reducing losses in the sterilization and assembly of trays. STR is one example of initiatives to improve process performance that have been widely reporte...

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 improv...

In this study we identify bundles of technologies and associated implementation barriers that could be viewed as part of Healthcare 4.0 (H4.0) and test their impact on performance improvement in a sample of hospitals. For that, we carried out a cross-sectional study with 181 leaders from hospitals in different countries that have already started H4...

Background: No-shows of patients have negative impacts on healthcare systems, such as resources’ underutilization, efficiency loss, and cost increase. Predicting no-show is key to develop strategies that counteract its effects. In this paper, we propose a model to predict the no-show of ambulatory patients to exam appointments of computed tomograph...

Background The recent literature reports promising results from using intelligent systems to support decision making in healthcare operations. Using these systems may lead to improved diagnostic and treatment protocols and to predict hospital bed demand. Predicting hospital bed demand in emergency department (ED) attendances could help resource all...

Since high performance is essential to the functioning of emergency departments (EDs), they must constantly pursue sensible and empirically testable improvements. In light of recent advances in computer science, an increasing number of simulation-based approaches for studying and implementing ED performance optimizations have become available in th...

Background: Surgical theater (ST) operations planning is a key subject in the healthcare management literature, particularly the scheduling of procedures in operating rooms (ORs). The OR scheduling problem is usually approached using mathematical modeling and made available to ST managers through dedicated software. Regardless of the large body of...

This paper aims at identifying the combination of organizational culture profiles and leadership styles that best support companies implementing lean manufacturing practices. For that, 225 leaders from manufacturing companies at various stages of lean implementation were surveyed. The analytical approach clustered respondents and their respective f...

Background: The SARS-CoV-2 virus responsible for COVID-19 poses a significant challenge to healthcare systems worldwide. Despite governmental initiatives aimed at containing the spread of the disease, several countries are experiencing unmanageable increases in the demand for ICU beds, medical equipment, and larger testing capacity. Efficient COVID...

Studies on the influence of contingency factors on the introduction of novel digital technologies into high-complexity systems, such as hospitals, are still incipient. As the introduction of Healthcare 4.0 (H4.0) usually implies in high capital expenditures and requires a more skilled labor force, such understanding gains relevance when considering...

Introduction Human-centered approaches to eliciting requirements for medical equipment selection are recognized as improving healthcare outcomes, safety, and end-user satisfaction. Nevertheless, there are many challenges to conducting rigorous investigations to identify requirements that satisfy different hospital services and types of end users (e...

The airline industry operates in a highly competitive market, in which achieving and maintaining a high level of passenger satisfaction is seen as a key competitive advantage. This study presents a novel framework for measuring customer satisfaction in the airline industry. Using text mining methods we explore Online Customer Reviews (OCRs) to prov...

In this study we propose the use of text mining and machine learning methods to predict and detect Surgical Site Infections (SSIs) using textual descriptions of surgeries and post-operative patients’ records, mined from the database of a high complexity University hospital. SSIs are among the most common adverse events experienced by hospitalized p...

Purpose This study aims to investigate the factors affecting daily demand in an emergency department (ED) and to provide a forecasting tool in a public hospital for horizons of up to seven days. Design/methodology/approach In this study, first, the important factors to influence the demand in EDs were extracted from literature then the relevant fa...

Purpose The purpose of this paper is to examine the mediating effect of learning organization dimensions on the relationship between the implementation of total quality management practices and companies’ operational performance improvement. Design/methodology/approach The authors carried out a cross-sector survey with 135 Brazilian manufacturing...

Several statistical-based approaches have been developed to support medical personnel in early breast cancer detection. This article presents a method for feature selection aimed at classifying cases into categories based on patients’ breast tissue measures and protein microarray. The effectiveness of this feature selection strategy was evaluated a...

In batch processing, process control is typically carried out comparing trajectories of process variables with those in an in-control set of batches that yielded products within specifications. However, one strong assumption of these schemes is that all batches have equal duration and are synchronized, which is often not satisfied in practice. To o...

Sterilization plants process all reusable materials used in hospitals during different stages of healthcare provision. Most items sterilized come from the surgical theater in the form of individual instruments, linen and surgical trays. Reducing the number of instruments in trays impacts on the performance of the sterilization process. Here, we pro...

The main purpose of fault detection in batch process monitoring is to identify batches displaying atypical behavior in comparison to normal operating data. The current growth in the number of measurable variables due to process automation yields datasets in which the number of variables is much larger than the number of batches. That may compromise...

This article aims at examining the influence of teams’ characteristics on the sustainability of Continuous Improvement (CI) initiatives. To achieve that, two identical manufacturing cells undergoing CI implementation and subordinated to the same leadership were investigated through a combination of quantitative and qualitative approaches. While one...

This research aimed to develop an affordable device for the elbow and forearm rehabilitation to be used in Brazilian hospitals, clinics, physician’s offices, and residences. The Brazilian government made investments in technology development for social change, demanding innovative rehabilitation products manufactured with lower cost, compared to th...

This study presents a systematic review of the literature on layout planning in healthcare facilities. The review includes 81 articles from journals, conferences, books, and other documents. Articles were classified in two groups according to their main contents including (i) concepts and guidelines and (ii) techniques and tools to assist in layout...

In this paper, we propose a novel framework to select the most relevant X-Ray Fluorescence (XRF) energy values (i.e., features) to enhance the clustering (grouping) of counterfeit and illicit medical tablets. The framework is based on the integration of multidimensional scaling (MDS) and Procrustes analysis (PA) multivariate techniques. MDS provide...

Mass Customization (MC) implies in large product variety and reduced production batch sizes. Tasks that rely on human ability are especially affected in this context as workers must quickly adapt to the requirements of new models. That adaptation process takes place differently in each worker, justifying the development of strategies to group worke...

Background: In this article, we propose a method that integrates systematic layout planning techniques to lean health care practices aided by multicriteria decision analysis that could be applied to reformulate the layout of health care facilities. Methods: We analyze a high-variety sterilization unit of a large public hospital located in Brazil...

This paper proposes an approach for feature selection aimed at classifying wines samples according to place of origin. The method relies on Kruskal-Wallis non-parametric test to remove non significant features, and Linear Discriminant Analysis to derive a feature importance index. The ranked features according that index are iteratively added and c...

A thinking style refers to a person’s preferred way to process and react to different situations. Since they have an impact on performance and should be viewed as fluid, some environments may benefit from specific thinking styles to optimize results and the use of resources. In this paper we present a study indicating which thinking style professio...

Objetivo: Relatar a experiência de desenvolver uma sistemática para racionalização de instrumentais em bandejas cirúrgicas. Método: Estudode desenvolvimento de sistemática para racionalização de instrumentais, realizado em 2015, a partir do método qualitativo, em um centro de materiaise esterilização (CME) de um hospital universitário federal de Po...

Street cocaine is typically altered with several compounds that increase its harmful health-related side effects, most notably depression, convulsions, and severe damages to the cardiovascular system, lungs, and brain. Thus, determining the concentration of cocaine and adulterants in seized drug samples is important from both health and forensic pe...

The objective of this study was to develop an agent based modeling (ABM) framework to simulate the behavior of patients who leave a public hospital emergency department (ED) without being seen (LWBS). In doing so, the study complements computer modeling and cellular automata (CA) techniques to simulate the behavior of patients in an ED. After verif...