Filipa Ferraz

Bio: Filipa Ferraz is an academic researcher from University of Minho. The author has contributed to research in topics: Dyscalculia & Decision support system. The author has an hindex of 6, co-authored 25 publications receiving 77 citations.

A Deep-Big Data Approach to Health Care in the AI Age

Abstract: The intersection of these two trends is what we call The Issue and it is helping businesses in every industry to become more efficient and productive. One's aim is to have an insight into the development and maintenance of comprehensive and integrated health information systems that enable sound policy and effective health system management in order to improve health and health care. Undeniably, different sorts of technologies have been developed, each with their own advantages and disadvantages, which will be sorted out by attending at the impact that Artificial Intelligence and Decision Support Systems have to everyone in the healthcare sector engaged to quality-of-care, i.e., making sure that doctors, nurses, and staff have the training and tools they need to do their jobs.

Entropy and Organizational Performance

Abstract: The main purpose of this article is to analyze the impact of the workers’ behavior in terms of their emotions and feelings in system’s performance, i.e., one is looking at issues concerned with Organizational Sustainability. Indeed, one’s aim is to define a process that motivates and inspires managers and personnel to act upon the limit, i.e., to achieve the organizational goals through an effective and efficient implementation of operational and behavioral strategies. The focus will be on the importance of specific psychosocial variables that may affect collective pro-organizational attitudes. Data that is increasing exponentially, and somehow being out of control, i.e., the question is to know the correct value of the information that may be behind these numbers.

A brief look into dyscalculia and supportive tools

Abstract: Mathematics has always been a crucial matter to the human being since theirs existence. Therefore, it is across their development that its importance and complexity becomes noticeable. Either counting cookies or telling the hours, for someone with dyscalculia, these simple tasks become difficult to perform. Even if they fail developing these issues, it is not because they do not have the capacity to evolve their knowledge, but because they have a dysfunction appealing to be diagnosed, followed and treated. Consequently, diagnosis tests and therapeutic tasks will be implemented and the informatics version of it can increase potentially the success and precision of the results.

Developing an ambient intelligent-based decision support system for production and control planning

Abstract: Scheduling production instructions in a manufacturing facility is key to assure a efficient process that assures the desired product quantities are produced in time, with quality and with the right resources. An efficient production avoids the creation of downstream delays, and early completion which both can be detrimental if storage space is limited and contracted quantities are important. Therefore, the production, planning and control of manufacturing is increasingly more difficult as family products increases. This paper presents an ongoing Ambient Intelligent decision support system development that aims to provide assistance on the creation on standard work procedures that assure production quantity and efficiency by means of ambient intelligence, optimization heuristics and machine learning in the context of a large organization.

Collaborative Process Mapping to Improve Work Instructions and Standardized Work

Abstract: Nowadays, companies are searching for models that are able to increase their performance, efficiency and competitiveness. Therefore, it is crucial to identify the current company status and its needs, adopting a suitable model for this. Many times, the success key consists in the adoption of tailor-made models developed by each organization. The company under study has developed a process mapping tool, called Value Stream Design in Indirect Areas (VSDiA) that has been used to map and improve its business processes, in this case, applied to Work Instructions and Standard Work creation. The adoption of this model has allowed the identification of weaknesses, strengths and improvement opportunities in the abovementioned processes, through a collaborative process team work. Furthermore, this tool has provided an overview about the whole process by all involved, as well as, increased transparency and accuracy of the current process and a vision for the future process.

A Review of Further Directions for Artificial Intelligence, Machine Learning, and Deep Learning in Smart Logistics

Abstract: Industry 4.0 concepts and technologies ensure the ongoing development of micro- and macro-economic entities by focusing on the principles of interconnectivity, digitalization, and automation. In this context, artificial intelligence is seen as one of the major enablers for Smart Logistics and Smart Production initiatives. This paper systematically analyzes the scientific literature on artificial intelligence, machine learning, and deep learning in the context of Smart Logistics management in industrial enterprises. Furthermore, based on the results of the systematic literature review, the authors present a conceptual framework, which provides fruitful implications based on recent research findings and insights to be used for directing and starting future research initiatives in the field of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in Smart Logistics.

Industry 4.0 triggered by Lean Thinking: insights from a systematic literature review

Abstract: Lean Thinking has successfully challenged mass production practices, by providing ‘leaner’ processes and supply chains, i.e. with less waste. Industry 4.0 has become an important strategic approach...

Productivity gains through standardization-of-work in a manufacturing company

Abstract: The purpose of this paper is to identify the non-value-adding activities (NVAs) of core making process and to eliminate them through the standardization-of-work (SW) procedures in a manufacturing company.,The action-research methodology was adopted for the current study. First, various lean tools were identified through literature review, and the bottleneck area was identified in discussion with the shop-floor executives. NVAs were recorded after a continuous process study including method study and motion analysis followed by the standard operating procedure. Second, the standardized work combination tables were prepared and NVAs were eliminated using the SW procedures. SW has been opted because it is a set of actions which helps in analyzing, improving and controlling the process and it leads to continual improvement.,The production logbook revealed that the capacity in this particular workstation was 54 pieces per 7 h work shift against the current production of approx. 45–50 pieces (past data). SW saved 31.6 s per cycle which boosted the production up to 58 pieces per 7 h work shift. Finally, the authors came to know that the productivity of this particular process increased up to 6.5 percent which may upsurge if this action is executed continually with the support from shop-floor executives and management. These results were also compared with previous research works in this area and found significant relevance, and hence, the results appear to be reliable.,This is a unique study in itself which explores the lean model by assessing NVAs of core making process. The proposed approach needs to be tested across different other core making processes of the case company so as to generalize the effectiveness of SW as well as the results obtained in the current study.,The current study illustrates an important step to give more visibility to the lean concept by addressing the problem of lack of standard procedures. This study will help the shop-floor executives and managers to focus their efforts in achieving high performance through effective implementation of SW. The study should be of the interest of researchers in the area of lean manufacturing, operations management, productivity analysis, etc.,The findings of this study are based on the problem formulation for productivity gains using SW procedures in the case company. The study introduces a new perspective for the execution of SW for core making processes. SW created transparency in workflow, enhanced the safety and eliminated the 3Ms. The outcome of the current study was discussed with the production team and management of the company to validate the productivity gains and received an optimistic response. Most importantly, these improvements were achieved with no investment in machinery or tooling.

How Industry 4.0 can enhance Lean practices

Abstract: The global industrial landscape has deeply changed over the last few years and the Industry 4.0 concept has emerged, being enabled by successive disruptive innovations and technological development that have transformed manufacturing processes. This concept is being pointed out as the fourth industrial revolution that embraces a set of new technologies that are shaping the future manufacturing vision. However, Lean Production is a widely used manufacturing approach that brings several benefits to organizations. Despite the integration between Industry 4.0 and Lean Production is being researched in the recent years, the impacts that result from the implementation of new technologies in established lean practices is not clear. The purpose of this study that consists in a systematic literature review is assessing how these emerging disruptive technologies can enhance lean practices and analyse their impacts and benefits for organizations that are moving towards this new industrial paradigm.

Business analytics in industry 4.0: a systematic review

Abstract: The work of P. Cortez was supported by FCT - Fundacao para a Ciencia e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020. We would like to thank to the three anonymous reviewers for their helpful suggestions.