Unveiling the relation between the challenges and benefits of Operational Excellence and Industry 4.0: A Hybrid Fuzzy Decision-Making Approach

Operational excellence (OpEx) is a direction toward learning and developing an excellent culture in all aspects of an organization. To reach this culture, revolutionizing activities using industry 4.0 (i4.0) technologies might be a significant empowering tool. This study aims to identify the challenges and benefits of both concepts and investigate their interrelationship to be considered in applying industry 4.0 technologies toward operational excellence. The challenges and benefits of OpEx and i4.0 are identified and finalized by reviewing the literature. The causal relations between the considered factors are extracted using the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) method. Then, the analytical network process (ANP) is applied to determine the importance and weight of the factors (challenges and benefits of OpEx and i4.0) according to the constructed network. The findings illustrated a strong network structure between the factors. First, the causal factors included OpEx and i4.0 challenges, while the OpEx challenges also affected the i4.0 challenges. Both group challenges had a significant effect on OpEx and i4.0 benefits. This means that challenges are the causal factors to be considered in the alignment of i4.0 toward OpEx. Among the OpEx challenges, lack of strategic planning and proper infrastructure were the main influential factors. In contrast, lack of government support and undeveloped business models were identified as the main challenges of i4.0. OpEx and i4.0 concepts are reviewed, and their pros and cons are studied. Previous studies determined an interaction among these concepts. However, from a practical viewpoint, the relation between the challenges and benefits of i4.0 and OpEx was studied for the first time for their alignment

A sentiment analysis software framework for the support of business information architecture in the tourist sector

In recent years, the increased use of digital tools within the Peruvian tourism industry has created a corresponding increase in revenues. However, both factors have caused increased competition in the sector that in turn puts pressure on small and medium enterprises' (SME) revenues and profitability. This study aims to apply neural network based sentiment analysis on social networks to generate a new information search channel that provides a global understanding of user trends and preferences in the tourism sector. A working data-analysis framework will be developed and integrated with tools from the cloud to allow a visual assessment of high probability outcomes based on historical data, to help SMEs estimate the number of tourists arriving and places they want to visit, so that they can generate desirable travel packages in advance, reduce logistics costs, increase sales, and ultimately improve both quality and precision of customer service

Cell surface marker mediated purification of iPS cell intermediates from a reprogrammable mouse model

Mature cells can be reprogrammed to a pluripotent state. These so called induced pluripotent stem (iPS) cells are able to give rise to all cell types of the body and consequently have vast potential for regenerative medicine applications. Traditionally iPS cells are generated by viral introduction of transcription factors Oct-4, Klf-4, Sox-2, and c-Myc (OKSM) into fibroblasts. However, reprogramming is an inefficient process with only 0.1-1% of cells reverting towards a pluripotent state, making it difficult to study the reprogramming mechanism. A proven methodology that has allowed the study of the reprogramming process is to separate the rare intermediates of the reaction from the refractory bulk population. In the case of mouse embryonic fibroblasts (MEFs), we and others have previously shown that reprogramming cells undergo a distinct series of changes in the expression profile of cell surface markers which can be used for the separation of these cells. During the early stages of OKSM expression successfully reprogramming cells lose fibroblast identity marker Thy-1.2 and up-regulate pluripotency associated marker Ssea-1. The final transition of a subset of Ssea-1 positive cells towards the pluripotent state is marked by the expression of Epcam during the late stages of reprogramming. Here we provide a detailed description of the methodology used to isolate reprogramming intermediates from cultures of reprogramming MEFs. In order to increase experimental reproducibility we use a reprogrammable mouse strain that has been engineered to express a transcriptional transactivator (m2rtTA) under control of the Rosa26 locus and OKSM under control of a doxycycline responsive promoter. Cells isolated from these mice are isogenic and express OKSM homogenously upon addition of doxycycline. We describe in detail the establishment of the reprogrammable mice, the derivation of MEFs, and the subsequent isolation of intermediates during reprogramming into iPS cells via fluorescent activated cells sorting (FACS).Christian M. Nefzger, Sara Alaei, Anja S. Knaupp, Melissa L. Holmes, Jose M. Pol

A Survey on Weapon Target Allocation Models and Applications

In Command and Control (C2), Threat Evaluation (TE) and Weapon Target Allocation (WTA) are two key components. To build an automated system in this area after modeling Threat Evaluation and Weapon Target Allocation processes, solving these models and finding the optimal solution are further important issues. This setting demands instantaneous operational planning and decision making under inherent severe stress conditions. The associated responsibilities are usually divided among a number of operators and also computerized decision support systems that aid these operators during the decision making process. In this Chapter, the literature in the area of WTA system with the emphasis on the modeling and solving methods are surveyed