Crystallizing Metal Shrinkage: Automation of High-Pressure Crystallization Control

The properties of bulk metal products are formed when molten metal transforms from an unstructured liquid into a solid crystal state. We suggest a new approach to the automation of the control over crystallized metal shrinkage compensation based on controlling the law of change in pressure applied to crystallizing metal through a program taking into account the transition process in the hydraulic system of the production equipment. We observed the increase in rigidity, durability, and pliability of В95-alloy samples as compared to cast aluminum alloys. The metal utilization rate can be increased up to 0.90 of the liquid metal volume.

Ontology-Based Modelling of State Machines for Production Robots in Smart Manufacturing Systems

The integration of modern IT technologies in production equipment does not only enable them to acquire information from different sources and provide it to others but also to make decisions depending on the situation. Due to the limited processing power of such equipment, usage of state machine to describe and program it is considered a promising direction. However, the necessity of intensive interaction of the equipment units causes problems related to interoperability, which are usually solved with the usage of ontologies. The objective of the presented research is to model state machines of production robots via ontologies. The results are demonstrated on the example of a fragment of an automated production line.

Pemberdayaan ekonomi kelompok nelayan Desa Pangkah Kulon-Gresik dalam memproduksi kerupuk ikan sebagai upaya peningkatan nilai ekonomi ikan sortiran

Pangkah Kulon is one of the villages in Gresik Regency which is located in Ujung Pangkah District, Gresik, East Java. The lack of public knowledge about fish processing makes people required to be more creative in increasing the selling value of fish into processed products. So far, fresh fish caught by fishermen are sold directly to middlemen, while fresh fish that do not pass the sorting is simply thrown away. To increase the economic value of fish into high selling value products, training in the production of fish crackers is carried out. The training was conducted on the socialization of creative preparations, training on the manufacture and creative industry of fish crackers. In this training, participants (fishermen's wives) are trained to operate production equipment, from dough making, milling, to cutting. The knowledge and skills provided can be used as a pioneering effort for the fish cracker creative industry which is a favorite food for the community in general. In addition, it is also a business opportunity that can increase household income.

BUSSINES MODEL CANVAS SEBAGAI ALTERNATIF STRATEGI BISNIS KERAJINAN SEDOTAN PURUN DI DESA TUMBANG NUSA, KECAMATAN JABIREN KABUPATEN PULANG PISAU

This study aims to analyze the business model of the purun straw craft business in Tumbang Nusa Village and determine the strategy for developing the purun straw craft business model in Tumbang Nusa Village with the Bussines Model Canvas (BMC) approach. Purun straws in Tumbang Nusa village. This study uses descriptive research methods to collect detailed actual information that describes existing symptoms, identifies problems or examines prevailing conditions and practices. The results of the research on the canvas model business mapping that have been carried out, it turns out that the customer segment of the purun straw craftsmen has been diversified into Bussines to Bussines and Bussines to Consumer customers with marketing reach in the cities of Palangkaraya, Jakarta and Bali. The revenue stream element from straw craftsmen is only in the form of selling straws. Furthermore, the main resources used are production equipment, human resources, capital, transportation and communication tools with key activities in the form of production and marketing activities. Meanwhile, the main partnership that keeps the business running is the Liaison and the government. The last element in the form of a cost structure contains fixed costs and variable costs. After getting information from the business model environment and SWOT analysis, the changes to the existing canvas business model are obtained. In order for the production process to run more efficiently, the use of appropriate technology is added through production mechanization, while for the main activity promotional activities are added. Researchers suggest craftsmen can implement improvement strategies on the Business Model Canvas elements that focus on five elements, namely, Customer segments, Channels, Customer relationships, Key activities and Key partners so that operational activities are expected to be more effective

Application of Text Mining Method for Classification of Work Order in Power Grid Production

With the completion of the State Grid Corporation’s maintenance system, the number of substations has increased dramatically, the grid structure has become increasingly complex, and there have been internal and external reasons such as the contingency of emergencies, and equipment failures have occurred from time to time. This paper aims to explore the potential value of massive data, show the laws of business data, and further give full play to the comprehensive support of data for enterprise operation and production management, and promote the realization of intelligent and lean power grid core business. This paper uses power system data to provide reliable data support for equipment defect full cycle management and equipment state analysis through ANOVA and neural network statistical analysis. At the same time, we use Term Frequency-Inverse Document Frequency(TF-IDF)Algorithm to calculate the importance of keywords and construct the power keyword library. By constructing Bayesian text classification model, we can classify the defect parts, defect categories and defect causes automatically. This method can be applied to the construction of power grid production work order text analysis system, improve the data quality and system automation level, help the business department to improve work efficiency and provide the basis for power grid business analysis. This method is applied to the data cleaning of the primary production equipment of power grid enterprises, and the accuracy of data error correction for equipment defects with voltages above 110kV is between 93% and 95%, and good results have been achieved.

Hydrogen Diffusion and Adsorption on WO3 (001) based on First Principles Calculation

Hydrogen reduction of tungsten oxide is currently the most widely applied ultrafine tungsten powder production process. The process has the advantage of short, pollution free and simple production equipment. But it is difficult to effectively control the morphology and particle size of the tungsten powder because of lacking in-depth understanding of the dynamic mechanism of the process. The first-principles calculations are carried out to explore the diffusion and internal adsorption of hydrogen on the WO-terminated surface of WO3 based on the density functional theory. The results show that hydrogen can diffuse from the WO terminal surface to the inside of WO3, the activation energy of diffusion is 46.682 Kcal/mol. It’s preferable for hydrogen to diffuse from the surface to the inside than diffuse within the WO3 lattice. The adsorption energy of hydrogen on the WO termination surface of WO3 is 15.093 Kcal/mol, the adsorption energy of hydrogen inside the WO termination surface of WO3 is 14.116 Kcal/mol, which means the hydrogen is easier to adsorb inside the WO3 lattice.

Data Science Meets High-Tech Manufacturing – The BTW 2021 Data Science Challenge

For its third installment, the Data Science Challenge of the 19th symposium “Database Systems for Business, Technology and Web” (BTW) of the Gesellschaft für Informatik (GI) tackled the problem of predictive energy management in large production facilities. For the first time, this year’s challenge was organized as a cooperation between Technische Universität Dresden, GlobalFoundries, and ScaDS.AI Dresden/Leipzig. The Challenge’s participants were given real-world production and energy data from the semiconductor manufacturer GlobalFoundries and had to solve the problem of predicting the energy consumption for production equipment. The usage of real-world data gave the participants a hands-on experience of challenges in Big Data integration and analysis. After a leaderboard-based preselection round, the accepted participants presented their approach to an expert jury and audience in a hybrid format. In this article, we give an overview of the main points of the Data Science Challenge, like organization and problem description. Additionally, the winning team presents its solution.

Proposal of a Tool for Determining Sub- and Main Dimension Indicators in Assessing Internal Logistics Readiness for Industry 4.0 within a Company

Key elements of Industry 4.0 are the digitization of products and production, enterprise information systems, robotic workplaces, communication infrastructure, and of course, employees. Industry 4.0 transforms production from stand-alone automated units to fully integrated automated and continuously optimized production environments. According to the prediction of Industry 4.0, new global networks will be created based on the interconnection of production equipment into CPS systems. These systems will be the basic building block of the so-called “smart factories”, and will be able to exchange information autonomously, trigger the necessary actions in response to current conditions and mutually independent inspections. The aim of this article is to describe the issue of readiness models for the Industry 4.0 concept, which are commonly used as tools for conceptualizing and measuring the maturity of an organization or process related to a specific target state. Characteristic for the models is their use because, on this basis, it is possible to identify the current readiness for the concept of Industry 4.0 comprehensively in the whole company or in various sub-areas.

Spark Plasma Sintering of Aluminum Nanocomposite Powders: Recent Strategy to Translate from Lab-Scale to Mass Production

The aim of this paper focuses on presenting a recent study that describes the fundamental steps needed to effectively scale-up from lab to mass production parts produced from Al powders reinforced with 0.5 wt% of industrial multiwalled carbon nanotubes (MWCNTs), with mechanical and electrical conductivity properties higher that those measured at the lab scale. The produced material samples were produced via a Spark Plasma Sintering (SPS) process using nanocomposite aluminum powders elaborated with a planetary ball-mill at the lab scale, and high-volume attrition milling equipment in combination with controlled atmosphere sinter hardening furnace equipment, which were used to consolidate the material at the industrial level. Surprisingly, the electrical conductivity and mechanical properties of the samples produced with the reinforced nanocomposite Al powders were made with mass production equipment and were similar or higher than those samples fabricated using metallic powders prepared with ball-mill lab equipment. Experimental measurements show that the hardness and the electrical conductivity properties of the samples fabricated with the mass production Al powders are 48% and 7.5% higher than those of the produced lab samples. This paper elucidates the steps that one needs to follow during the mass production process of reinforced aluminum powders to improve the physical properties of metallic samples consolidated via the SPS process.

Optimizing Directional Drilling While Simultaneously Maximizing the Whole Life Value of the Well

Increasingly complex wells and longer laterals present new challenges for wellbore placement and wellbore quality. There is a growing understanding of the impact of well placement and wellbore quality on the overall value of the well and on the economics of completions and production. This paper looks at how requirements have evolved and will evolve beyond simply "getting to TD" as quickly as possible and how emerging technologies can help. There is already an undercurrent of opinion that completions and production are sometimes compromised to maximize rate of penetration, but with some controversy about the exact value and how easy it is to attribute cause. This paper reviews how directional drilling practice has evolved over 100 years, and how the wellbore quality that results from the directional drilling process can be a driver for the overall value of the well. Specifically, it draws on a number of key references to examine how tortuosity doesn't just have an influence on drilling but also how it can adversely impact completions, reliability of production equipment and even production rates. The paper proposes that we consider the whole-life value of the well as a key performance indicator as we drill. It emphasises that we must cease to focus solely on rate of penetration and the depth-time curve. The paper shows, with examples, how modern directional drilling systems can address tortuosity and improve wellbore quality. It presents an unbiased view of the industry from an independent viewpoint, exploring how directional drilling has been partially automated over the years and examining the state of the art in current automated directional drilling systems. It proposes the need for a modern directional drilling system not just in terms of drilling parameters but also in terms of automation of geometric and, ultimately, geologic aspects of directional drilling. The paper is intended to break down the silos that can exist between drilling, completions and production functions, and to help the industry to think about the long-term consequences of performance when specifying future directional drilling equipment.