Part Of Industry Research Articles

Implementation of digital marketing at the Grand Kutilang Syariah Hotel Bandar Lampung during the recovery period after the Covid-19 pandemic: A sharia business perspective

IntroductionPrevious studies have analyzed the application of digital marketing in the hotel industry during the Covid-19 pandemic. However, research on digital marketing in the context of the hotel industry with an Islamic approach is still limited.ObjectivesThis study discusses the implementation of digital marketing in a sharia hotel as response to the Covid-19 pandemic. MethodThis study used a qualitative approach with a case study at Grand Kutilang Syariah Hotel Bandar Lampung. Data collection was carried out using questionnaires, and data analysis was carried out using inductive technique.ResultsThe Grand Kutilang Sharia Hotel, as part of tourism and hospitality industry in Lampung Province, employed digital marketing strategies to maintain business continuity during and after the COVID-19 pandemic. The implementation of digital marketing in The Grand Kutilang Sharia Hotel during the Covid-19 pandemic, involves optimizing the use of social media platforms such as WhatsApp, Instagram, Facebook, Twitter, YouTube, and TikTok. This implementation aligns with Sharia business principles.ImplicationsThis study shows the importance of adopting technological advancement in sharia hotel industry. Sharia hotels should take advantage of technological developments to maintain their business.Originality/NoveltyThis study contributes to the literature regarding sharia hotel marketing strategies in facing the crisis.

Badewo Kayangan in Okura Pekanbaru Community from Treatment Rituals to Aesthetic Dance: Ecotourism

This research aims to explain the form and function of Badewo Kayangan as a healing ritual in the past and present for the people of Tebing Tinggi Okura. This research is qualitative research with a descriptive approach that understands the phenomenon of the research subject. The data in this research is information obtained through various sources, both sources obtained directly through interviews with sources who know about the Badewo Khayangan dance, video recordings, photographs, and data in the form of documentation. Apart from this data, it is also supported by data in the form of notes obtained during observations. The research findings are that Badewo Kayangan was originally a healing ritual used to cure various diseases, including those caused by supernatural forces in the Okura High Cliff area. As time went by, people began to ask Wak Damai to change Badewo Kayangan into the Badewo Kayangan dance. The movements contained in Badewo Kayangan are combined with new elements and realized in the form of a dance performance known as the Badewo Kayangan dance. Badewo Kayangan has two main roles, namely as a traditional healing ritual and as a means of performing arts or entertainment. By considering the potential of the Badewo Kayangan Tebing Tinggi Okura dance as a local cultural asset, this dance has the potential to become part of the tourism industry based on culture.

The Effect of Data Security Procedures and Big Data Analytics on Engineering Performance: A Case Study of Lagos (Iganmu) Industrial Layout

The purpose of this research is to comprehend how big data analytics affect engineering performance. The industrial part especially the engineering practice is among the most significant and delicate in the world. Gathering and manufacturing have a huge social impact on the economies of the nations and, consequently, on the lives of individuals all over the world. The potential for big data to completely alter engineering practice and enhance ongoing engineering projects. Many organizations appear to be aware of the advantages big data can bring to their performance in engineering practice, particularly its significant possible worth, but they encounter a number of challenges when implementing it, primarily because they are having trouble figuring out how to use the derived insights for their development. The development of new strategies and services is a crucial engineering activity, and it has been demonstrated to significantly affect an organization’s viability. If these insights are monetized, Organizations aiming for an improved engineering practice can build brand-new, customer-centered, and data-driven projects or both goods and services, providing a long-lasting competitive advantage and new revenue streams. According to empirical research, companies that have engineering practice incorporated with a data-driven approach that can show how big data contributes to improved performance, while those that have not yet instilled the entire organization struggle with an absence of comprehension on how to use big data technology to create potential value and accomplish their organizational goals. Due to the enormous strategic potential of big data, this article tries to conceptualize and investigate its effects on corporate performance. It also explores the impacts of big data on engineering performance because of its high strategic potential. Finally, it explores whether and how the creation of new engineering services and projects makes use of big data and related technologies. An in-depth SWOT, binary Logistic Regression analysis, and the use of grounded theory combine previous big data studies with several enterprises in Lagos, Nigeria’s Iganmu industrial layout area. The caliber of data gathered, data availability, legal considerations of data confidentiality and safekeeping, and highly qualified individuals working with big data are additional critical factors that influence the use of a data-driven approach. Therefore, in order for companies to achieve effectiveness and efficiency, they need to reflect on and make strategic decisions utilizing a comprehensive perspective on big data.

The Integration of Critical Risk with Building Information Modelling Application Strategies in Building Refurbishment Project Lifecycle

Building refurbishment project has rapidly becoming a significant part of the construction industry in Malaysia. Refurbishment projects are typically higher risk, more complex, and require more coordination than new construction projects. Therefore, the aim of this research is to establish the integration of critical risk with Building Information Modelling (BIM) application strategies for building refurbishment project lifecycle improvement. This study is conducted through a quantitative method using the questionnaire which is distributed by employing a self-administrated approach as a research medium to obtain feedback from contractor grade 7 (G7) from construction organization who are registered with Construction Industry Development Board (CIDB) Malaysia. As a result, 96.5 percent of the response rate are accepted. The analysis shows that the integration of critical risk with BIM application strategies is recognized as important factors and strategies towards building refurbishment projects lifecycle improvement and found that the mean is in very high range. Additionally, the results indicate that the level of critical risk and BIM application strategies have been measured through descriptive analysis. The findings of this study are expected to establish a foundation for future research in order to develop an adequate framework for managing building refurbishment projects and improve the quality of decision making among the building industry professionals.

A study on the path of ideological and political construction of English courses for tourism majors in higher vocational colleges

As an important part of modern service industry, tourism industry has become an important force to promote the development of national economy and the improvement of people's quality of life. The training of tourism major in higher vocational colleges is the key link to ensure the sustainable development of tourism industry. However, with the rapid development of the society and the increasing frequency of international exchanges, tourism students not only need to obtain solid professional knowledge and skills, but also need to have a high level of English to meet the needs of international exchanges. Based on the characteristics of the tourism industry and the needs of students, this paper discusses how to construct a set of teaching system suitable for tourism English courses in higher vocational colleges through ideological and political education, promote the overall development of students and the improvement of professional quality, and find a more scientific and systematic path for ideological and political construction, in order to provide some constructive enlightenment for the ideological and political education of tourism English courses in higher vocational colleges [1].

(Invited) Simulations of Ultra-Scaled Electronic Devices with a Novel Flexible Nano-TCAD Nano-Electronic Simulation Software (NESS) Environment

Simulation of conventional and emerging electronic devices using Technology Computer Aided Design (TCAD) tools has been an essential part of the semiconductor industry as well as academic research. Computational efficiency and accuracy of the numerical modeling are the key criteria on which quality and utility of a TCAD tool is ascertained. Further, the ability of the tool to incorporate different modeling paradigms and to be applicable to a wide range of device architectures and operating conditions is essential.In this talk, I will provide an overview of the new device simulator NESS (Nano-Electronic Software Simulator) developed at Device Modelling Group at University of Glasgow. NESS is a fast, modular software with its own structure and mesh generators, and contains different modules for classical, semi-classical, and quantum transport solvers, mobility calculation, kinetic Monte-Carlo etc. NESS can simulate numerous device architectures such as nanowire and bulk transistors, tunnelling field effect transistors (TFET) and resonant tunnelling diodes. Moreover, NESS accounts for various sources of statistical variability in nano-size electronic devices and it can perform statistical simulations for thousands microscopically different devices.

(Invited) Industrial Relevance of Pulsed Electrochemical Methods

Industrial demands are the driving force on any optimization and development process for electrochemical plating processes and coatings. The classical demands focused on the mechanical properties such as wear resistance and hardness as well as the stability against corrosion.The galvanic coatings were tailored for meeting these requirements, defining the electrochemical systems that are currently standard in galvanic protection of industrial parts.With the introduction of new applications and production methods over the last 10 to 15 years additional functionality has been seeked by the industry, including chemical stability, bio-compatibility, microstructured surfaces, lubrication effects, magnetic properties and the ability of shock absorbance. Coating had to be adjusted, leading to the industrial realisation of dispersion and compound coatings, alloy deposition on a wider scale and Pulse (reverse) plating. While these, from an industrial perspective, relatively new plating processes already required some major rethinking of the traditional galvanic industry, the industrial requirements got even more demanding over the last few years. Especially with the origin of new industrial production methods, the homogenous treatment and coating of e.g. complex bionical structures became relevant.In order to follow the changing demands, the transfer from the classical thermodynamically controlled direct current or constant potential based surface treatment towards a kinetically controlled pulsed surface finishing has to be executed.While pulse plating is the most popular representation of these categories of finishing processes, pulsed electrochemical processes comprise a much larger variety of methods. Among these, pulse anodization, pulsed plasma electrolytic oxidation (PEO), pulsed electropolishing, electrochemical machining (ECM) and the recently introduced Hirtisation process are industrially used.The presenation will give an overview of possibilities for electrochemical engineering of surfaces for high-end technical applications by pulsed electrochemical techniques.

A quick look at the recent advances, current state of utilization and expected future usage of artificial intelligence (AI) in the global textile manufacturing industry

A significant part of the current textile manufacturing industry around the world is managed and governed by individuals who are not sufficiently trained in information technology. While future textile engineers and technologists may come out sufficiently equipped to understand IT and its implications to the textile manufacturing industry, those running the industry today can benefit through simple elaboration of potentially useful IT tools and the many benefits they offer to the textile industry. This is especially true in the case of technologies that surfaced within the last two decades and are already making a sizable impact on products, production processes and the bottom lines of manufacturing industries. Artificial intelligence (AI) and related technologies fall under the category of rapidly emerging technologies that carry the potential to significantly re-shape the global manufacturing and service industries. This paper makes an attempt to describe these technologies and their potential benefits in such a way that textile industry leaders who are not IT experts can understand them to the extent of driving themselves to enthusiastically adopt them.

Mekanik Tahrikli Rastgele Kısa Desen Yapan Makine Prototipi

One of the important producers of the industrial industry in our country is the textile sector. The importance of the textile industry for our country is growing day by day with increasing production and employment. In order to keep up with this growth, manufacturers need to go beyond their existing systems, show their differences and make the right innovations in their production. Considering these values, changes to be made in the yarn structure or dyeing process come to the fore. In this study, the dyeing process is discussed. Weaving and home textiles, which are an important part of the textile industry, have a wide market. There are different dyeing systems that have an important market for the products made in these areas. Spaced and smart painting, which are among these painting systems, do not meet the needs in the desired direction. A new machine design is needed to provide the desired features. In the study conducted in this direction; A commercially unavailable machine has been implemented, designed and manufactured to generate random short patterns with mechanical drive. In project scope; First of all , the paint stand to be integrated into the system was designed . Different yarn lifters and godet systems have been designed. Paint container, drive system and electronic panel are also mounted on the system. In addition, new software has been developed within the scope of the project to provide automatic control of the system. Studies were carried out with PLC and Arduino electronic circuit board. In the first stage, motor driver circuits were designed with PLC and Arduino. Then, with the software loaded on the PLC and Arduino processor board, the frequency values to be given to the inverter were started by changing the threshold ranges we wanted. Lifters and painting cylinders are connected to each other so that the same sequence is not repeated. Thus, in this study carried out in line with the needs, both a new machine and a new textile product with different dye patterns emerged.

CONCEPTUAL PRINCIPLES OF THE HIGH-TECH SECTOR OF MANUFACTURING INDUSTRY ESSENCE AND METHODOLOGICAL PRINCIPLES OF ASSESSING ITS TECHNOLOGICAL LEVEL IN THE CONTEXT OF CAPITALIZATION

CONCEPTUAL PRINCIPLES OF THE HIGH-TECH SECTOR OF MANUFACTURING INDUSTRY ESSENCE AND METHODOLOGICAL PRINCIPLES OF ASSESSING ITS TECHNOLOGICAL LEVEL IN THE CONTEXT OF CAPITALIZATION

An Empirical Study on Developing the Tourism Potentials of Fairs and Festivals in Odisha in India

Numerous studies on the appeal of tourist sites have been done. However, little study has been conducted on festival attractiveness and its effect on place attachment. This study adopted a mixed-methods strategy to examine the festivals in Odisha. Travel and tourism have become essential economic activities throughout the world in this globalization market. Festivals have recently grown in number, variety, and popularity, making them one of the strongest parts of the tourism industry. During tourism activities, tourists pay close attention to how attractive something is. The festival’s appeal is one of the most important things that determines whether or not a tourist will go and take part in activities. Also, the appeal of a festival can makes tourists more likely to come back, which is the key to the success of festival activities. This paper sought to determine the role of tourism as a long-run economic growth mechanism in Odisha. The Government of Odisha promotes tourism, but the focus remains on the golden triangle, which includes Puri, Konark, and Bhubaneswar. Without a doubt, these locations are well-equipped to meet the needs of both domestic and foreign tourists. Other beautiful places in Odisha still are largely unknown to tourists. In this paper, we try to demonstrate the overall importance of various fairs and festivals for the development of tourism and relate the significance of fairs and festivals.

Resolved Simulation of the Clarification and Dewatering in Decanter Centrifuges

Solid–liquid separation is a fundamental operation in process engineering and thus an important part of many process chains in the preparation of slurries in the chemical industry and other parts of the industrial environment. For the separation of micron-sized particles which, due to their size, do not settle or settle very slowly in the earth’s gravity field, centrifuges are often used. The preferred choice are often decanter centrifuges because they work continuously and stabilize the process against product fluctuations due to their adjustment possibilities. The design of the apparatus is complex: The main components of the apparatus are the cylindrical-conical bowl, which rotates at a high speed, and a screw located inside the bowl, which rotates in the same direction at a low differential speed to transport the separated solids out of the apparatus. Geometrical properties of the apparatus, as well as the adjustable operating parameters, such as rotational speed or differential speed, have a significant influence on the separation. In practice, analytical models and the experience of the manufacturers form the basis for the design. Characteristics of the disperse phase, interactions with the liquid, as well as the influence of the flow on the separation, are not taken into account. As a consequence, the transfer to industrial scale always requires a large number of pilot-scale experiments, which are time-consuming and expensive. Due to the increasing computational power, computational fluid dynamics (CFD) provides one possibility to minimize the experimental effort in centrifuge design. In this work, the open-source software OpenFOAM is used to simulate the multi-phase flow in a laboratory decanter centrifuge. For validation, experiments were carried out on a laboratory scale and the main operating parameters, such as speed, differential speed, and volume flow rate, were varied. The simulation results show a good agreement with the experimental data. Furthermore, the numerical investigations show the influence of the flow on the separation of the particles. To evaluate the transportability of a material, the transport efficiency was introduced as a dimensionless parameter. In addition, the simulation allows the consideration of the individual velocity components, making it possible to generate an impression of the complex three-dimensional flow in the apparatus for the first time.

Detection of chalcopyrite in digital images of copper ore sample sections

Copper ores are mineral formations of natural origin, the concentration of copper or copper compounds in which is sufficient for their commercial mining. Because of this, copper ores are on the list of minerals that are of strategic importance for the sustainable development of the economy and defense capability of Ukraine. In addition, due to the high thermal conductivity, copper and its alloys are widely used for the manufacture of various types of heat exchangers and radiators. The content of copper in ores usually ranges from 1 to 5%; ores containing less than 0.5% copper are unprofitable for processing at the current level of technology. Mining of copper is of strategic importance, as copper is the main material for the production of cable products and other conductive parts in the electrical industry. The efficiency of technological processes in the mining and industry during the production of copper depends on the quality of ores in relation to the content of minerals that contain copper. Copper ore can be considered a heterogeneous material consisting of two homogeneous phases, one phase is host rock, and the other is copper mineral. Modern image processing techniques have allowed as to automate the identification of minerals in ore samples. Automatic recognition and quantification of minerals using X-Ray tomography, scanning electronic microscope, light microscopy, is one of the most important problems in ore processing systems, as the amount of the minerals in the ore must be determined for further processing. A method of segmentation of colour images of sections of test samples of copper ore is proposed to estimate the percentage content of its components in the section of the tested samples. It is based on the use of chalcopyrite colour features in the HSV model. This colour-based segmentation method is proposed to exploit the average value and distribution of HSV colour components of chalcopyrite in an copper ore image. Segmentation parameters are configured. The experimental results of the segmentation of colour images of copper ore slices by the proposed method are analyzed. The effectiveness of the method is checked using synthesized test images. The method provides an absolute error less than 2.5%.

Rethinking scene representation: A saliency-driven hierarchical multi-scale resampling for RGB-D scene point cloud in robotic applications

Effective three-dimensional (3D) scene representation for grasping is significant in smart manufacturing and industrial applications. Serving as a foundational element for robot manipulation, the desired 3D scene representation should encapsulate critical high-level properties. Nonetheless, little attention has been paid to the impact of the object-aware sampling strategy on generating valid grasps. Although pleasing to the eye, natural point cloud mapping is not always appropriate for real-world robotic applications. We introduce a point cloud framework called saliency-driven hierarchical multi-scale resampling: a 3D stereoscopic scene representation that recognizes and tracks novel objects while predicting their saliency in robot interactions. In particular, the new scene representation captures object-level features, which have long been argued as crucial to human scene understanding. Through this approach, we have discovered that our method yields favorable results in terms of feature persistence and resistance to uneven distribution of input scene point clouds, even when the computational time is comparable or slightly increased. Real-world experiments were also conducted to validate the proposed work’s performance to achieve more accurate grasp estimates in generic object and industrial part grasp tasks.

An ARIMA-based study of pricing and replenishment decisions for vegetable commodities

Fresh produce superstores face many challenges as an important part of the livelihood industry. The short freshness period and variable quality make their daily sales efficiency crucial. A simple, efficient and applicable decision model for supermarkets is beneficial to further promote the healthy and sustainable development of the fresh food market and the overall livelihood industry. In order to predict the daily replenishment and pricing strategy of each vegetable category in the coming week, the key lies in analyzing the supermarket's historical data. Since the sales volume shows strong cyclical fluctuations, the time series model ARIMA is chosen for this purpose to observe the model training and predict the pricing of different categories of products in the next 7 days. Due to the cost-plus pricing mechanism of the superstore, after processing the data, we selected simple linear regression model, multiple linear regression model and nonlinear regression model to fit the data, and opted for multiple linear regression to get the sales volume on the cost-plus pricing of the fitting formula, taking into account the discount rate of the different types of vegetables, we corrected the sales volume of the six types of vegetables, and ultimately obtained the superstore's daily replenishment and pricing strategy for the next seven days.

A Review of the Metal Additive Manufacturing Processes.

Metal additive manufacturing (AM) is a layer-by-layer process that makes the direct manufacturing of various industrial parts possible. This method facilitates the design and fabrication of complex industrial, advanced, and fine parts that are used in different industry sectors, such as aerospace, medicine, turbines, and jewelry, where the utilization of other fabrication techniques is difficult or impossible. This method is advantageous in terms of dimensional accuracy and fabrication speed. However, the parts fabricated by this method may suffer from faults such as anisotropy, micro-porosity, and defective joints. Metals like titanium, aluminum, stainless steels, superalloys, etc., have been used-in the form of powder or wire-as feed materials in the additive manufacturing of various parts. The main criterion that distinguishes different additive manufacturing processes from each other is the deposition method. With regard to this criterion, AM processes can be divided into four classes: local melting, sintering, sheet forming, and electrochemical methods. Parameters affecting the properties of the additive-manufactured part and the defects associated with an AM process determine the method by which a certain part should be manufactured. This study is a survey of different additive manufacturing processes, their mechanisms, capabilities, shortcomings, and the general properties of the parts manufactured by them.

Optimization of Packing Irregular Three-Dimensional Objects

Introduction. Nowadays the irregular packing problem is becoming more important, since effective space management and optimal arrangement of objects are becoming key factors for ensuring efficiency and saving resources in a wide range of applications, e.g., additive manufacturing, space engineering, material sciences and logistics. It becomes an integral part of strategic development in the fields of production and science. The purpose of the paper. The paper is devoted to construction of a mathematical model and development of an efficient technique for densely filling a container with the maximum number of sets of irregular three-dimensional objects. Results. Irregular objects are approximated with a certain accuracy by non-convex polyhedra, which can be represented by the union of convex polytopes. Non-overlapping and containment constraints are described using quasi-phi-functions and phi-functions. A mathematical model of the packing problem is provided as a mixed-integer nonlinear programming considering given proportions of different types of objects. A solution strategy is proposed to search for local-optimal solutions. To find reasonable feasible packing, a fast algorithm based on a strip approximation of objects is used. A numerical example of the development of a print map of a set of industrial parts with maximum filling of the working chamber of a 3D-printer is given. Conclusions. The results confirm the efficiency of the proposed packing strategy, which is based on an integrated approach that takes into account the geometric features of irregular objects and their completeness. Keywords: packing, irregular objects, set of parts, mathematical modeling, optimization, 3D-printing.

The Application of Alternative Data in Personal Consumption Credit

Credit evaluation has been an important part in personal consumption industry and developed since 1960s. Alternative data provides a new view of data mining and gets to be one of the research hotspots in this field. This paper will summarize the application situation and development status of alternative data in personal consumption credit, according to the specific usage in the researches. Alternative data has been more and more widely used in personal credit industry. It has the advantage of improving predictivity and decreasing discrimination. However, meanwhile, because of the incompleteness of relative law and the existence of Lucas Critique, the legality of the employment of alternative data and the reliability of the results are to be proven. Many researches based on machine learning or other AI algorithm couldnt provide enough power of explanatory. This paper will give financial candidates a distinct view of the pros and cons in the research about applications of alternative data in personal consumption credit and leads to an increasing accuracy in credit assessment.

Optimized Inconel 718 pressure vessel manufactured with laser powder bed fusion

Laser powder bed fusion (L-PBF) is one of the most novel additive manufacturing methods used for a wide range of industrial grade metallic materials. The process can produce end-use metal parts with desirable qualities and mechanical properties. L-PBF however, remains a complicated and expensive manufacturing method. Design for additive manufacturing (DfAM) is a key aspect leveraging the uptake of advantages and possibilities offered by AM in augmenting its competitiveness against conventional manufacturing (CM) methods. Inconel 718 (IN718) is a nickel-based superalloy boasting high temperature strength, good oxidation, and corrosion resistance at elevated temperatures. IN718 is commonly used for high performance applications, such as power and process industry parts, and gas turbine components. High inherent toughness, hardness, work hardening, and low thermal conductivity properties make the material difficult to manufacture through conventional machining methods. The layer-by-layer building of powder metals via L-PBF makes it possible to build different geometrical intricacy. The offered manufacturing flexibility for complex high-end metal structures for variety of applications makes L-PBF an alternative manufacturing method for high performance metals. This study investigates use of DfAM for a small-scale pressure vessel with predefined geometry, dimensions, design space and load condition. The aim is to introduce and exploit contemporary design optimization methods and their feasibility with AM. Structures, such as lattices and stress field driven geometries based on finite element analysis are investigated in this study. The designs are virtually tested under predefined pressure load of 50 bar. All four design options are manufactured on EOS M290 and IN718 powder. The result of the study shows the different optimizations decrease weight and improve material savings without compromising the linear load capacity. Optimized designs could also be made in such a way that it does not increase the manufacturing duration or add additional steps to it.

The Process of AI-Aided Drug Design

Artificial Intelligence (AI) is a growing field in today’s world and plays a part in many industries today. Its role in drug design and the biological sciences has begun to expand in recent years. DeepChem is an open source tool that explores and employs the methods behind drug design. The tool’s process and end result will be indicative of how well AI can perform the job of drug discovery and how much it can expedite the process, as well as reveal the future of tools like DeepChem. DeepChem handles everything from data processing to fitting AI models to performing predictions on proposed molecules. By applying DeepChem and reviewing it, we will be revealing AI’s power and limitations in biomedical chemistry and technology. In addition, other AI tools, such as Chemistry 42 and inClinico by Insilico that achieve other parts of the drug design process. Completing a comprehensive review of these methods will provide an overview of what can be improved and the scope of AI as a big money-maker and solution in the biomedical field. The synthesis of drugs is a complicated process that can be simplified by AI tools. This paper explores how AI tools operate and their limitations in the medicinal world.