Automatic definition of engineer archetypes: A text mining approach

With the rapid and continuous advancements in technology, as well as the constantly evolving competences required in the field of engineering, there is a critical need for the harmonization and unification of engineering professional figures or archetypes. The current limitations in tymely defining and updating engineers' archetypes are attributed to the absence of a structured and automated approach for processing educational and occupational data sources that evolve over time. This study aims to enhance the definition of professional figures in engineering by automating archetype definitions through text mining and adopting a more objective and structured methodology based on topic modeling. This will expand the use of archetypes as a common language, bridging the gap between educational and occupational frameworks by providing a unified and up-to-date engineering professional figure tailored to a specific period, specialization type, and level. We validate the automatically defined industrial engineer archetype against our previously manually defined profile

Mapping Industry 4.0 Enabling Technologies into United Nations Sustainability Development Goals

The emerging of the fourth industrial revolution, also known as Industry 4.0 (I4.0), from the advancement in several technologies is viewed not only to promote economic growth, but also to enable a greener future. The 2030 Agenda of the United Nations for sustainable development sets out clear goals for the industry to foster the economy, while preserving social well-being and ecological validity. However, the influence of I4.0 technologies on the achievement of the Sustainable Development Goals (SDG) has not been conclusively or systematically investigated. By understanding the link between the I4.0 technologies and the SDGs, researchers can better support policymakers to consider the technological advancement in updating and harmonizing policies and strategies in different sectors (i.e., education, industry, and governmental) with the SDGs. To address this gap, academic experts in this paper have investigated the influence of I4.0 technologies on the sustainability targets identified by the UN. Key I4.0 element technologies have been classified to enable a quantitative mapping with the 17 SDGs. The results indicate that the majority of the I4.0 technologies can contribute positively to achieving the UN agenda. It was also found that the effects of the technologies on individual goals varies between direct and strong, and indirect and weak influences. The main insights and lessons learned from the mapping are provided to support future policy

Optimized Procedure to Schedule Physicians in an Intensive Care Unit: A Case Study

Hospitals are facing an important financial pressure due to the increasing of the operating costs. Indeed, the growth for the hospitals’ services demand causes a rising in the number of required qualified personnel. Enlarging the personnel number increases dramatically the fixed total cost. Based on some studies, 50% of operating costs in US hospitals are allocated to healthcare personnel. Therefore, reducing these types of costs without damaging the service quality becomes a priority and an obligation. In this context, several studies focused on minimizing the total cost by producing optimal or near optimal schedules for nurses and physicians. In this paper, a real-life physicians scheduling problem with cost minimization is addressed. This problem is encountered in an Intensive Care Unit (ICU) where the current schedule is manually produced. The manual schedule is generating a highly unbalanced load within physicians in addition to a high cost overtime. The manual schedule preparation is a time consuming procedure. The main objective of this work is to propose a procedure that systematically produces an optimal schedule. This optimal schedule minimizes the total overtime within a short time and should satisfies the faced constraints. The studied problem is mathematically formulated as an integer linear program. The constraints are real, hard, and some of them are non-classical ones (compared to the existing literature). The obtained mathematical model is solved using a state-of-the-art software. Experimental tests on real data have shown the performance of the proposed procedure. Indeed, the new optimal schedules reduce the total overtime by up to 69%. In addition, a more balanced workload for physicians is obtained and several physician preferences are now satisfied

A Multi-Criteria Decision Framework Considering Different Levels of Decision-Maker Involvement to Reconfigure Manufacturing Systems

Reconfigurable Manufacturing Systems (RMSs) rely on a set of technologies to quickly adapt the manufacturing system capacity and/or functionality to meet unexpected disturbances, such as fluctuation/uncertainty of demand and/or unavailability/unreliability of resources. At the operational stage, such disturbances raise new production requirements and risks, which call upon Decision-Makers (DMs) to analyze the opportunity to move from a running configuration to another more competitive one. Such a decision is generally based on an evaluation of a multitude of criteria, and several multi-criteria decision-making (MCDM) approaches have been suggested to help DMs with the reconfiguration process. Most existing MCDM approaches require some assignment of weights to the criteria, which is not a trivial task. Unfortunately, existing studies on MCDM for an RMS have not provided guidelines to weigh the evaluation criteria. This article fills in this gap by offering a framework to set up such weights. We provide a comprehensive set of quantitative indicators to evaluate the reconfiguration decisions during the operation of the RMS. We suggest three weighting methods that are convenient to different levels of DM expertise and desired degree of involvement in the reconfiguration process. These weighting methods are based on (1) intuitive weighting, (2) revised Simos procedural weighting combined with the Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS), and (3) DM independent weighting using ELECTRE IV. The implementation of the suggested framework and a comparison of the suggested methods carried out on an industrial case study are described herein

Requirements of the Smart Factory System: A Survey and Perspective

With the development of Industry 4.0 and the emergence of the smart factory concept, the traditional philosophy of manufacturing systems will change. The smart factory introduces changes to the factors and elements of traditional manufacturing systems and incorporates the current requirements of smart systems so that it can compete in the future. An increasing amount of research in both academia and industry is dedicated to transitioning the concept of the smart factory from theory to practice. The purpose of the current research is to highlight the perspectives that shape the smart factory and to suggest approaches and technical support to enable the realization of those perspectives. This paper fills this gap by identifying and analyzing research on smart factories. We suggest a framework to analyze existing research and investigate the elements and features of smart factory systems

An Archetype for Engineering Education Towards Industry 4.0 Enabled Sustainability

Educational accreditation bodies provide standards of the programs that students should meet. This is a high-level and broad perspective guideline [1]. On the other hand, educational institutes define course syllabi or Intended Learning Outcomes (ILOs) to guide the learning process and proffer a sense of measurable statement of acquiring a specific skill, which are used by academics and students [2]. There is a massive gap in engineering education to match the higher-level standards and the lower-level ILOs with the industrial needs. At the same time, these standards and ILOs are rigid and do not accommodate current edge technology advances (I4.0), especially those with promising potential for sustainable development [3]. Harmonization quantitatively with sustainability goals is another major challenge [4]

Dimethyl 2-(4-methylbenzylidene)malonate

In the molecule of the title compound, C13H14O4, the benzene ring forms dihedral angles of 18.60 (7) and 81.36 (8)° with the two arms of the malonate moiety. The crystal structure features C—H...O interactions, which form chains running parallel to the b axis

Synthesis, Spectroscopic Investigations (X-ray, NMR and TD-DFT), Antimicrobial Activity and Molecular Docking of 2,6-Bis(hydroxy(phenyl)methyl)cyclohexanone

The synthesis of 2,6-bis(hydroxy(phenyl)methyl)cyclohexanone 1 is described. The molecular structure of the title compound 1 was confirmed by NMR, FT-IR, MS, CHN microanalysis, and X-ray crystallography. The molecular structure was also investigated by a set of computational studies and found to be in good agreement with the experimental data obtained from the various spectrophotometric techniques. The antimicrobial activity and molecular docking of the synthesized compound was investigated

Fabrication and Evaluation of Quercetin Nanoemulsion: A Delivery System with Improved Bioavailability and Therapeutic Efficacy in Diabetes Mellitus

The current study was intended to fabricate and evaluate ultrasonically assisted quercetin nanoemulsion (Que-NE) for improved bioavailability and therapeutic effectiveness against diabetes mellitus in rats. Ethyl oleate, Tween 20, and Labrasol were chosen as oil, surfactant, and cosurfactant, respectively. Box–Behnken design (BBD) was employed to study the influence of process variables such as % surfactant and cosurfactant mixture (Smix) (5 to 7%), % amplitude (20–30%) and sonication time (2.5–7.5 min) on droplet size, polydispersibility index (PDI), and % entrapment efficiency (%EE) were studied. The optimization predicted that 9% Smix at 25% amplitude for 2.5 min would produce Que-NE with a droplet size of 125.51 nm, 0.215 PDI, and 87.04% EE. Moreover, the optimized Que-NE exhibited appreciable droplet size and PDI when stored at 5, 30, and 40 °C for 45 days. Also, the morphological characterization by transmission electron microscope (TEM) indicated the spherical shape of the optimized nanoemulsion. Furthermore, the Que-NE compared to pure quercetin exhibited superior release and enhanced oral bioavailability. The streptozocin-induced antidiabetic study in rats revealed that the Que-NE had remarkable protective and therapeutic properties in managing body weight, blood glucose level, lipid profile, and tissue injury markers, alongside the structure of pancreatic β-cells and hepatocytes being protected. Thus, the developed Que-NE could be of potential use as a substitute strategy for diabetes