Hasil untuk "Manufacturing industries"

R. Schmalensee

Joseph Moses Juran

G. McMullan, C. Meehan, A. Conneely et al.

D. Audretsch

Jaesang Lee, Shaily Mahendra, P. Alvarez

T. Beck

The author explores a possible link between financial development and trade in manufactures. His theoretical model focuses on the role of financial intermediaries in facilitating large-scale, high-return projects. Results show that economies with better developed financial sectors have a comparative advantage in manufacturing industries. He provides evidence for this hypothesis, first proposed by Kletzer and Bardhan (1987), using a 30-year panel of data for 65 countries. Controlling for country-specific effects and possible reverse causality, he shows that financial development exerts a large causal impact on the level of both exports and the trade balance of manufactured goods.

James Bessen

Will new technologies cause industries to shed jobs, requiring novel policies to address mass unemployment? Sometimes productivity-enhancing technology increases industry employment instead. In manufacturing, jobs grew along with productivity for a century or more; only later did productivity gains bring declining employment. What changed? The elasticity of demand. Using data over two centuries for US textile, steel and auto industries, this paper shows that automation initially spurred job growth because demand was highly elastic. But demand later became satiated, leading to job losses. A simple model explains why this pattern might be common, suggesting that today’s technologies may cause some industries to decline and others to grow. Automation might not cause mass unemployment, but it may well require workers to make disruptive transitions to new industries, requiring new skills and occupations.

G. Kannan, Shaligram Pokharel, P. S. Kumar

Steven Wright

Joanna I. Lewis, R. Wiser

Sriganesh K. Rao, R. Prasad

Shohin Aheleroff, Huiyue Huang, Xun Xu et al.

There is a recognized need for mass personalization for sustainability at scale. Mass personalization is becoming a leading research trend in the latest Industrial Revolution, whereas substantial research has been undertaken on the role of Industry 4.0 enabling technologies. The world is moving beyond mass customization, while manufacturing has led to mass personalization ahead of other industries. However, most studies have not treated human capabilities, machines, and technologies as sustainable collaboration. This research investigates mass personalization as a common goal under the latest Industrial revolutions. Also, it proposes a Reference Architecture Model for achieving mass personalization that contributes to understanding how Industry 5.0 enhances Industry 4.0 for higher resilience and sustainability through a human-centric approach. The study implies that Human Capital 5.0 leads collaboration with machines and technologies, bringing more value-added and sustainable products.

Yu Lu, Qi Zhang, Yukai Chen et al.

Metal additive manufacturing (AM) holds significant potential for the rapid prototyping of complex parts in the aerospace, defense, and military industries, biomedicine, and other fields. Despite its advantages over conventional manufacturing methods, AM faces technical bottlenecks (e.g., poor densification, high residual stress, and significant anisotropy of mechanical properties), which hinder its large-scale industrial application. The newly emerging metal hybrid additive manufacturing (MHAM) serves as a viable approach to address the inherent issues associated with AM. This method integrates different auxiliary technologies (e.g., subtractive manufacturing, formative manufacturing, magnetic fields, ultrasonic fields, thermal fields, etc.), leveraging the strengths of these technologies to enhance the performance of metal components produced via AM. MHAM offers numerous advantages, such as controlling the flow of the melt pool, refining the microstructure, optimizing the grain size orientation, reducing the residual stress, enhancing the surface quality, and improving the mechanical properties and fatigue resistance. This work offers a thorough and current analysis of the state of MHAM development, including additive and subtractive hybrid manufacturing, additive and formative hybrid manufacturing, and energy field-assisted additive manufacturing. It delineates the MHAM technology framework and clarifies the interaction mechanisms among various auxiliary technologies used in AM. Additionally, it discusses the impacts of MHAM on melt pool dynamics, solidification processes, densification, microstructure evolution, surface quality, and mechanical and fatigue properties. In summary, the distinct characteristics of various MHAM techniques are outlined, and future trends in MHAM development are anticipated.

Marcel FIGURA, Denis JURACKA, Jorma IMPPOLA

Artificial intelligence (AI) is becoming a significant driver of transformation in the business environment, particularly for startups, which are characterized by high levels of adaptability, innovation orientation and strategic flexibility. Startups that incorporate artificial intelligence into their structures and processes are reshaping traditional approaches to value creation. This study aims to explore how artificial intelligence influences the formation and evolution of business models in startups across different industries. The analysis draws on academic literature, case study evidence and current market observations in order to identify key areas where artificial intelligence may affect fundamental business model components. The comparative part of the study focuses on differences between AI-driven startups and traditional companies that did not emerge as startups and do not rely on artificial intelligence as a core strategic technology. The comparison is carried out within three selected industries, namely banking, automotive manufacturing and retail. The study applies the Business Model Canvas (BCM) as a conceptual tool to evaluate the configuration of business models in both categories of companies. The results of the analysis indicate that startups using artificial intelligence are creating new types of business models in which AI plays a significant role in shaping the value proposition, sales channels, and revenue streams. Traditional companies, on the other hand, are not transforming their business models radically but are integrating artificial intelligence mainly in support areas. Building on these findings, this research contributes to the broader understanding of business model innovation under the influence of artificial intelligence and outlines the analytical foundations for identifying structural distinctions between AI-driven startups and traditional companies.

Chunnan Qian, Xiaorong Tang

Industry 4.0 technologies, particularly automation and digital transformation, are increasingly central to sustainable innovation in manufacturing. This study examines the role of Industry 4.0 in promoting green innovation within Chinese manufacturing firms. Using firm-level panel data from 2011 to 2019, we develop an econometric model incorporating industry-level I4.0 density and firm-level exposure to automation. Results show that I4.0 adoption significantly enhances green innovation, especially among large firms. Digital transformation and managerial efficiency strengthen this effect, while firms led by IT-savvy CEOs experience further benefits. However, regional and sectoral disparities exist: larger firms in technology-intensive and developed regions benefit more, while smaller firms face greater challenges. To address endogeneity, an instrumental variable approach is employed, and robustness is verified through alternative specifications. This study offers methodological contributions through its use of firm-level data and multi-level modeling, and provides strategic guidance for managers and policymakers aiming to achieve environmental goals through automation.

Zecheng Ren, Zengnan Yu, Wenyi Zhang et al.

Industrial robots are indispensable in modern manufacturing across various sectors, including nuclear, chemical, and aerospace industries. They serve to replace humans in hazardous operations, ensuring worker safety, while also enhancing production efficiency and product quality, particularly in tasks such as welding and assembly. However, the maintenance and repair of these robots present significant challenges. When malfunctions occur, workers often face the daunting task of sifting through extensive industrial manuals to diagnose the root cause based on error codes, a process that is time-consuming and hampers productivity.To address this issue, this paper proposes an intelligent voice query method designed to facilitate access to industrial manual content. The goal is to empower workers to swiftly comprehend the causes of robot failures and retrieve corresponding solutions through interactive voice commands, thereby streamlining troubleshooting efforts. Leveraging voice recognition technology, workers can effortlessly issue queries without the need for manual search and interpretation. The effectiveness of this method was rigorously evaluated through experimental validation in real-world scenarios, demonstrating notable improvements in maintenance efficiency.

Gustavo A. Espinoza Calderón, Gloria O. Bustamante Cárdenas

The Occupational Safety and Health Administration (OSHA) is a division of the U.S. Department of Labor. Its mission is to minimize health and safety hazards to workers in manufacturing industries. The focus was on its application in the food industry. Specifically in the manufacture of corn and wheat flour tortillas. These products have a high consumption in the North American country. The purpose of this study was to examine the mechanisms of the tortilla industry to adapt each activity to safety standards. In addition, to evaluate a measurable impact on the accidents that occurred and how they were corrected. The results show that OSHA standards enabled the design and management of industrial safety for the tortilla industry. This study identified three safety measures: personal protective equipment (PPE), chemical handling (SDS), and lockout/tagout (LOTO). Descriptive analyses were conducted to examine the impacts of the revised standard on tortilla worker safety. The findings indicate that nearly 24% of all injuries occur in this type of industry. It can be concluded that increasing workplace safety and compliance with legislation is currently a high priority in the food industry, although food safety is also of great importance. Both aspects can now go hand in hand thanks to the wide variety of safety solutions identified with low risk of contamination.

Yoonjae Lee, Dongju Seo, Sangyoon Lee et al.

In continuous-process systems, failures of rolling-element bearings typically cause accidents, reduced productivity, and production-related financial losses. Therefore, predicting both the lifespan of rolling-element bearings and their replacement time is crucial for preventing machine system failures. Accordingly, numerous studies have reported various machine and deep learning classifiers for predicting the lifespan of bearings. However, these studies did not consider degradation trends of bearings. Thus, this study aimed to develop an algorithm to predict the lifespan of a bearing by considering its degradation trend. A vibration dataset of bearings was obtained at low and high speeds. Using a second-order curve-fitting model, various degradation patterns in the dataset were classified. Appropriate time-domain or frequency-domain feature variables applicable to the design of a classifier were determined according to classified patterns. In addition, the classifier was trained using multiple bidirectional long short-term memories. Finally, the performance of the developed classifier was verified experimentally

Dini Wahjoe Hapsari*, Dwi Fitrizal Salim, Dudi Pratomo et al.

SMK YPPS Sumedang is a formal education unit that organizes vocational education focusing on hospitality, culinary, and fashion expertise. The school has provideda practice room to support students' business expertise. Business management must be equipped with financial management skills. Service and manufacturing industries require the accurate calculation of the produc costingto determine selling prices. The obstacle faced by the school is that students have not been able to calculate the cost of goods and selling price accurately Students need additional insight related to these calculations. The team of community service activities was implemented in class X, consisting of students of the hospitality, catering, and fashion programs. This activity used a combination of investigative, quantitative and descriptive approach.In addition to providing material, students work on pre-test and post-test questions. The test scores showed an increase after students obtained the material. The results of the questionnaire filled out by students showed 94% agreed that the implementation of the activity went according to the objectives, 97% agreed that the activity program suited the needs of the partners (students of SMK YPPS), 90% agreed that the implementation of the program was relatively sufficient, 96% agreed that the implementation team was friendly and helpful, 97% agreed that this program was sustainable

Yuseok Kim, Seung Mun Lee, Suk-Hee Park

In this study, we present the fabrication of dual-morphing vascular stents using an additive-lathe printing method and two different shape-memory polymers. Traditional additive manufacturing techniques confront significant challenges in producing vascular stents with complex, hollow, mesh-like structures due to limitations such as a flat printing bed and the placement of supports. To overcome these obstacles, we employed a lathe-type additive manufacturing system with a rotatable base substrate, enabling precise fabrication of cylindrical-shaped stents. To achieve shape transformability, we used shape-memory polymers as the stent materials, offering the advantage of minimally invasive surgery. Two distinct shape-memory polymers, with different transition temperatures (35 and 55oC), were printed using the additive-lathe method. The printed stents consisted of two distinct parts that underwent dual-stage morphological changes at the different temperatures. By manipulating the printing paths, the dual-morphing properties of the stents could be adjusted in both longitudinal and circumferential directions. This innovative approach could be a solution to several limitations associated with the application of stents in diseased vascular tissues with complex shapes, facilitating minimal invasion during surgical procedures.