Toward a Modeling Framework for Organizational Competency

Part 6: Computational Systems ApplicationsInternational audienceCompetency modeling framework serves as a; (a) very important basis for the explanation of a generic competency modeling approach, (b) base element in the consolidation of existing knowledge in this area, (c) tool for model developers on selecting appropriate competency models, and (d) basis for competency modeling. This research uses literature review approach to propose a modeling framework for organizational competency. The proposed modeling framework has been developed based on the most relevant well known competency models. The research suggests that organizational competency can be categorized into three groups; individual competency, enterprise competency and collaboration-oriented competency. For modeling each of these groups, it is essential that the modeling process have to be aligned with model developer purpose (Modeling perspective), thus the model developing process will be based on the same segmentation model. Furthermore, competencies have to be model at different levels of abstraction (modeling intent)

Mesenchymal stem cell secretome induced the acquisition of anti-inflammatory phenotype in rat cortical microglia in vitro

Introduction: Here, we aimed to address the impact of mesenchymal stem cells-conditioned medium (MSCs-CM) on M1/M2 phenotype shifting of rat microglia after 48 hours in vitro. Methods: Rat neonatal cortical microglia were randomly allocated into four different groups as follows: Control; MSC-CM; IL-4; and Anti-IL-4 groups. In the MSC-CM, microglia were treated with MSC condition media. In the interleukin-4 (IL-4), cells received 20 ng/mL IL-4; conceived as a positive M2 control group). In the Anti-IL-4, the combination of IL-4 peptide and anti-IL-4 antibody was used. After 48 hours, protein levels of Iba1, CD86, and CD206 were monitored using immunofluorescence imaging and flow cytometry analysis. Results: According to immunofluorescence imaging, 48-hour incubation of rat cortical microglia with stem cells condition media increased protein levels of CD206 and decreased CD86, showing the polarization of microglia toward M2 type lineage compared to the non-treated control group. We found a similar trend in the group that received IL-4. By contrast, the incubation of microglia with anti-IL-4 antibody blunted the stimulatory effect of IL-4 to promote M2-type microglia. Similar to the immunofluorescence data, flow cytometry analysis revealed a significant increase of CD206 positive microglia after exposure to MSC-CM and IL-4 (P<0.05). Treatment with anti-IL-4 antibody significantly reduced the percent of CD206 positive cells, showing the inhibition of M1-to-M2 phenotype acquisition. Conclusion: The current study highlighted a notable anti-inflammatory effect of MSC secretome on cortical microglia by promoting M1-to-M2 phenotype acquisition

Energy consumption optimization for sustainable flexible robotic cells: Proposing exact and metaheuristic methods

Many manufacturing companies are always looking for a way to reduce energy consumption by utilizing energy-efficient production methods. These methods can be different depending on the type of products and production technology. For instance, one of the ways to increase energy efficiency and keep the precision of production is to use robots for the transportation of the parts among the machines and loading/unloading the machines. This technology is affordable compared to the technologies used in manufacturing companies. Manufacturing companies that rely on robotics technology must have a strategy to reduce energy costs and at the same time increase production by adjusting the intensity of processing or controlling the production rate. This study presents an exact solution method for flexible robotic cells to control the production rate and minimize energy consumption, which aims to both reduce electricity prices and minimize greenhouse gas (GHG) emissions under a lead time of production. Then, considering the NP-hardens nature of the problem, a heuristic solution method based on the genetic algorithm (GA) is proposed. Using the proposed approach, manufacturing companies will be able to make more accurate decisions about processing intensity and process scheduling while ensuring sustainability

Towards a Capability-Based Decision Support System for a Manufacturing Shop

Part 8: Models and Metamodels IInternational audienceTo succeed, long term organizations must compete efficiently and out-perform their competitors in a dynamic environment. To survive in this competition, identification, classification and management of organizational capabilities are vital. This paper presents a methodology for developing a system to store, manage, and maintain intra-organizational capabilities for decision making processes on resources, processes and strategies for business opportunities. The proposed methodology is explored in an educational manufacturing cell

Effect of tool traverse speed on microstructure and mechanical performance of friction stir welded 7020 aluminum alloy

Abstract The effect of tool traverse speed on microstructure and mechanical properties of friction stir welded 7020-T6 aluminum alloy was investigated. For this purpose, 5 mm thick 7020-T6 aluminum alloy plates were friction stir welded at traverse speeds of 50, 100, 150, and 200 mm/min and constant rotational speed of 900 r/min. Also, the peak temperatures of the joints during friction stir welding were recorded by accurate thermocouples. Moreover, the microstructure, hardness, tensile properties, and fracture surfaces of the joints were examined. The results showed that increasing the tool traverse speeds from 50 to 200 mm/min decreased the peak temperature from 331 C to 211 C, and hence caused to lower heat input during friction stir welding. Furthermore, the higher hardness and ultimate tensile strength of the joints welded at higher traverse speeds was related to the grain boundary, precipitation, and substructure strengthening mechanisms. In addition, the fracture surfaces of the joints welded at higher heat input conditions showed more ductile mode in comparison with those welded at lower heat input condition, which confirmed the lower tensile elongation of the joints welded at higher traverse speeds

Effect of Reinforcement Amount, Mold Temperature, Superheat, and Mold Thickness on Fluidity of in-Situ Al-Mg2Si Composites

In the present study, the effects of mold temperature, superheat, mold thickness, and Mg2Si amount on the fluidity of the Al-Mg2Si as-cast in-situ composites were investigated using the mathematical models. Composites with different amounts of Mg2Si were fabricated, and the fluidity and microstructure of each were then analyzed. For this purpose, the experiments were designed using a central composite rotatable design, and the relationship between parameters and fluidity were developed using the response surface method. In addition, optical and scanning electron microscopes were used for microstructural observation. The ANOVA shows that the mathematical models can predict the fluidity accurately. The results show that by increasing the mold temperature from 25 degrees C to 200 degrees C, superheat from 50 degrees C to 250 degrees C, and thickness from 3 mm to 12 mm, the fluidity of the composites decreases, where the mold thickness is more effective than other factors. In addition, the higher amounts of Mg2Si in the range from 15wt.% to 25wt.% lead to the lower fluidity of the composites. For example, when the mold temperature, superheat, and thickness are respectively 100 degrees C, 150 degrees C, and 7 mm, the fluidity length is changed in the range of 11.9 cm to 15.3 cm. By increasing the amount of Mg2Si, the morphology of the primary Mg2Si becomes irregular and the size of primary Mg2Si is increased. Moreover, the change of solidification mode from skin to pasty mode is the most noticeable microstructural effect on the fluidity.WoSScopu

Half a century of promises The failure to realise 'community care' for older people

1994 Graham Lecture, London (Great Britain), 10 Nov 1994Available from British Library Document Supply Centre- DSC:q95/03815 / BLDSC - British Library Document Supply CentreSIGLEGBUnited Kingdo

Cyber-physical-based PAT (CPbPAT) framework for Pharma 4.0

Industry 4.0 aims to integrate manufacturing operations into a seamless digital whole by incorporating flexibility, agility, re-configurability, and sustainability. The result of this integration is a "smart factory" that is more lean, agile, and flexible in operations. There are valid reasons, and perhaps requirements, for pharmaceutical industries to embrace smart factory and to "borrow" the concept of Industry 4.0 to give rise to "Pharma 4.0" (i.e., the pharmaceutical version of Industry 4.0). This paper proposes a cyber-physical-based PAT framework called CPbPAT for implementing smart manufacturing systems in the pharmaceutical industry. The framework has been developed using an agent-based system and is presented by a standard system modeling language called the Unified Modeling Language (UML). The pharmaceutical manufacturing system shown in "Quality by Design for ANDAs" is used as a case study to illustrate the application of the proposed framework

Enterprise Competency Modelling in Practice-an Exploratory Case Study

AbstractCompetency modelling is a standardized way to found an enterprise area of experts. Identifying and managing competences acquired by an enterprise and further representing them in a structured manner provide important knowledge for ‘know-how’ approach. The purpose of this paper is developing a competency based knowledgebase for an enterprise using case study approach. The developed competency knowledgebase for the case study provides information important to decision-making, and can act as an indicator for an enterprise's willingness to engage in robust collaboration

Elucidating the effect of electrical discharge machining parameters on the surface roughness of AISI D6 tool steel using response surface method

83-90In this investigation, response surface method was used to predict and optimize the surface roughness during electrical discharge machining of AISI D6 tool steel. Pulse on time, pulse current and voltage were considered as input process parameters. Also, the analysis of variance was employed for checking the developed model results. The results showed that the developed model predicted the roughness values, accurately. Also, the pulse on time was the most effective parameter influencing the roughness. Moreover, it was found that the higher values of pulse on time and pulse current and lower values of input voltage caused to in higher amounts of surface roughness. Moreover, the optimal condition to obtain a minimum of surface roughness was 10.22 µs, 8.02 A and 174.74 V, respectively for the pulse on time, pulse current and input voltage