A BIM Based Framework for Damage Segmentation, Storage, and Visualization

Current bridge inspection practices rely on paper-based data acquisition, digitization, and multiple conversions in between incompatible formats to facilitate data exchange. This practice is time-consuming, error-prone, cumbersome, and leads to information loss. One aim for future inspection procedures is to have a fully digitized workflow that achieves loss-free data exchange, which lowers costs and offers higher efficiency. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information through out different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focused on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.

Operational Data Repository as the First Step to Digital Oil Field

Digital oil field is a terminology that frequently appeared in the last few years. In the era of industry 4.0 and the proliferation of digital technology, oil and gas companies need to adapt in order to gain advantage in business process development, and this term is the answer. In digital oil field, data is significantly valuable. Therefore, robust database and real time data monitoring need to be developed. Pertamina EP has established a robust, easy-to-access, and web-based database application called Operational Data Repository (ODR). This application handles end-to-end business process from exploration all the way to commercial. Several modules were integrated for this application and the main modules consist of exploration, exploitation, production, finance, safety and commercial. For every module in ODR, the first task to carry is to create and input master data. After database is created, calculation according to module's purpose is performed. Once the system is there, automatic data acquisition and monitoring will enter the picture. Exploration module in ODR handles database of Pertamina EP exploration activities. This module include lithology, biostratigraphy, and geochemical data of exploration project in Pertamina EP. This module ensures that initial data of a structure is preserved and available. Exploitation module deals with oil and gas reserves and resources reporting process, well proposal for annual work plan, and surface project monitoring. This module rules development phase from subsurface to surface. Production module shows daily operational activities, production data, and quadrant mapping of wells productivity. Data from this module is taken for evaluating production and operation performance. Finance module handles company's financial report, including revenue, expense, and tax. Safety module handles work permit, hazard identification, risk assessment and control for every project and work plan. Safety is a very important aspect in a company and this module ensures that documents needed to perform work safely is well-documented and easy to submit and access. Last but not least is commercial module. This module consists of gas sales agreement documents (GSA), metering system location, and customer complaints monitoring. ODR has already been well-established, therefore Pertamina EP started its pilot project for automatic data acquisition for eight wells and currently on monitoring phase. This paper describes Pertamina EP first step to digital oil field, which is developing virtual warehouse to store company's data. The step is strengthened with attempting for automatic data acquisition that will be integrated to the ODR for the next phase.

Automatic Data Acquisition and Monitoring Device to Indicate the Freshness of Milk during Transportation

Milk is a nutrient-rich liquid food and it is the primary source of nutrition and a cheap source of protein for large vegetarian population living in India. Dairy industry in India is the world's largest milk producer and dominates about 13% of world milk production. Milk contains several groups of nutrients & considerable amount of organic substances and functional elements such as traces of vitamins, enzymes & dissolved gases, dissolved salts, calcium, water, carbohydrates, proteins, fats, complex & simple lipids, minerals, vitamins , etc.,. Milk transportation has shown to contribute to a greater extent to milk spoilage. Most of the milk which has been rejected by milk processing plants had samples which indicate milk of good quality at farm level before transportation. Milk processors request that milk must be cooled to 2°C to 4°C within 2 to 3 h of milking. The monitoring system that we have implied here is to check the temperature throughout the transportation using micro-controller and to ensure the quality of the milk. This monitoring device consist of NTC Temperature sensor to indicate the exposure to excessive temperature and controlled temperature like cold storage and a gas sensor is used to detect the spoilage of milk while transportation. The RFID tags are used to record the information of the vendor, temperature and how much litre they are giving to the society and hereby, the complete record of this is maintained separately by data acquisition system with the open source software cayenne. In this monitoring device, the temperature of the milk is continuously monitored using microcontroller and an immediate alert message is given to the driver and admin when there is raise in temperature. Keywords: Milk, cayenne, data acquisition, RFID, NTC

Enhancement of Machinery Activity Recognition in a Mining Environment with GPS Data

Fast-growing methods of automatic data acquisition allow for collecting various types of data from the production process. This entails developing methods that are able to process vast amounts of data, providing generalised knowledge about the analysed process. Appropriate use of this knowledge can be the basis for decision-making, leading to more effective use of the company’s resources. This article presents the approach for data analysis aimed at determining the operating states of a wheel loader and the place where it operates based on the recorded data. For this purpose, we have used several methods, e.g., for clustering and classification, namely: DBSCAN, CART, C5.0. Our approach has allowed for the creation of decision rules that recognise the operating states of the machine. In this study, we have taken into account the GPS signal readings, and thanks to this, we have indicated the differences in machine operation within the designated states in the open pit and at the mine base area. In this paper, we present the characteristics of the selected clusters corresponding to the machine operation states and emphasise the differences in the context of the operation area. The knowledge obtained in this study allows for determining the states based on only a few selected most essential parameters, even without consideration of the coordinates of the machine’s workplace. Our approach enables a significant acceleration of subsequent analyses, e.g., analysis of the machine states structure, which may be helpful in the optimisation of its use.

Effectiveness of Electrical and Optical Detection at Pixel Circuit on Thin-Film Transistors

The paper presents a typology of electrical open and short defects on thin-film transistors (TFT) using an electrical tester and automatic optical inspection (AOI). The experiment takes the glass 8.5th generation to detect the electrical characteristics engaged with time delay and integration (TDI) charged-coupled-devices (CCDs), a fast line-scan, and a review CCD with five sets of magnification lenses for further inspection. An automatic data acquisition program (ADAP) controls the open/short (O/S) sensor, TDI-CCD, and motor device for machine vision and statistics of substrate defects simultaneously. Furthermore, the quartz mask installed on AOI verified its optical resolution; a TDI-CCD can grab an image of a moving object during transfers of the charge in synchronous scanning with the object that is significant.