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"Machine industry"
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Artificial intelligence and machine learning for industry 4.0
Essential for any leader seeking to understand how to leverage intelligent automation and predictive maintenance to drive innovation, enhance productivity, and minimize downtime in their manufacturing processes. Intelligent automation is widely considered to have the greatest potential for Industry 4.0 innovations for corporations. Industrial machinery is increasingly being upgraded to intelligent machines that can perceive, act, evolve, and interact in an industrial environment. The innovative technologies featured in this machinery include the Internet of Things, cyber-physical systems, and artificial intelligence. Artificial intelligence enables computer systems to learn from experience, adapt to new input data, and perform intelligent tasks. The significance of AI is not found in its computational models, but in how humans can use them.
BOOK
New formulation and valid inequalities for a periodic capacitated vehicle routing problem with multiple depots, heterogeneous fleet, and hard time-windows
This paper presents a new formulation and valid constraints for a periodic capacitated vehicle routing problem with multiple depots, heterogeneous fleet, and hard time-windows (MDHFPCVRP-TW). The problem raises from a real-world application in the vending machine industry in Medellín, Colombia. Our main contribution is a novel formulation that replaces binary depot-client assignment variables with continuous auxiliary variables and implements depot replication, achieving both model simplicity and computational efficiency. We introduce preprocessing techniques and valid constraints, particularly focusing on capacity-based constraints with client combinations, which significantly strengthen the formulation’s linear relaxation. Computational experiments demonstrate that our formulation consistently outperforms previous approaches across different instance sizes, achieving optimality for small instances and maintaining single-digit optimality gaps for medium-sized instances where earlier formulations showed gaps above 12%. The formulation shows particularly strong performance in solution time, often requiring less time to find feasible solutions. While limitations persist for very large instances, our results suggest promising directions for developing hybrid exact-heuristic methods for industrial-scale problems.
Journal Article
A Real-Time Application for the Analysis of Multi-Purpose Vending Machines with Machine Learning
With the development of mobile payment, the Internet of Things (IoT) and artificial intelligence (AI), smart vending machines, as a kind of unmanned retail, are moving towards a new future. However, the scarcity of data in vending machine scenarios is not conducive to the development of its unmanned services. This paper focuses on using machine learning on small data to detect the placement of the spiral rack indicated by the end of the spiral rack, which is the most crucial factor in causing a product potentially to get stuck in vending machines during the dispensation. To this end, we propose a k-means clustering-based method for splitting small data that is unevenly distributed both in number and in features due to real-world constraints and design a remarkably lightweight convolutional neural network (CNN) as a classifier model for the benefit of real-time application. Our proposal of data splitting along with the CNN is visually interpreted to be effective in that the trained model is robust enough to be unaffected by changes in products and reaches an accuracy of 100%. We also design a single-board computer-based handheld device and implement the trained model to demonstrate the feasibility of a real-time application.
Journal Article
Fabricating consumers
Since its early days of mass production in the 1850s, the sewing machine has been intricately connected with the global development of capitalism. Andrew Gordon traces the machine's remarkable journey into and throughout Japan, where it not only transformed manners of dress, but also helped change patterns of daily life, class structure, and the role of women. As he explores the selling, buying, and use of the sewing machine in the early to mid-twentieth century, Gordon finds that its history is a lens through which we can examine the modern transformation of daily life in Japan. Both as a tool of production and as an object of consumer desire, the sewing machine is entwined with the emergence and ascendance of the middle class, of the female consumer, and of the professional home manager as defining elements of Japanese modernity.
eBook
The impact of family ownership on innovation: evidence from the German machine tool industry
There has been much debate concerning the innovative output of family-owned and non-family-owned companies. The purpose of this study was to show that the impact of family ownership differs depending on important governance conditions. Drawing on secondary data from the German machine tool industry from 2000 to 2010, we show that it is not family ownership per se that drives or impedes innovation in terms of the number of patents granted to a firm. Increases in the degree of family ownership and the generation of the family reduce the innovative output, whereas dedicated family business institutions nurture it. We discuss the implications of our findings for research and management.
Journal Article
Experiences, Achievements, Developments
The machine tool industry is a small sector with a big impact. Almost all technical products are manufactured with the help of machine tools - one reason why the machine tool is considered to be »the ultimate machine\".Berthold Leibinger, longtime managing partner of the machine tool and technology company TRUMPF, investigates the development of the machine tool industries of Germany, Japan and the United States since 1960. Key factors such as innovations, the importance of science and the training of employees are all examined. The structure of the machine tool industry and their characteristics are highlighted. In addition to the author's own experiences during his working life, numerous discussions held with experts and company representatives have also been taken into consideration.This analysis of the machine tool industry's development in three different countries also mentions numerous influential factors that lead to success or failure. From these, Berthold Leibinger derives recommended measures for managers of machine tool companies.
eBook
Unleashing innovation
In publications such as BusinessWeek and Fast Company, the media have celebrated Whirlpool′s transformation into a leading-edge innovator and Nancy Tennant Snyder′s role as chief innovation officer. Ten years after this remarkable transformation, Unleashing Innovation tells the inside story of one of the most successful innovation turnarounds in American history. Nancy Tennant Snyder and coauthor Deborah L. Duarte reveal how Whirlpool undertook one of the largest change efforts in corporate history and show how innovation was embedded throughout the company, which ultimately lead to bottom-line results.
eBook
White Castle burgers from a vending machine? We tried it
Food reporter Tim Carman flew from D.C. to Boston try New England's first White Castle location — a vending machine. At Logan International Airport.
Streaming Video
Vending machines for reducing harm associated with substance use and use disorders, and co-occurring conditions: a systematic review
Background
To stem rising fatal overdoses and other substance use/use disorder (SUD)-related harms, communities are turning to low-barrier harm reduction strategies, such as harm reduction-focused vending machines (VMs) that distribute naloxone, fentanyl test strips, and other harm reduction-related items. This systematic review aims to synthesize literature on VMs for SUD-related harm reduction.
Methods
Four databases (Embase, Cochrane, PubMed, MEDLINE) were searched from their inception through November 29, 2023. References of identified eligible articles and pertinent prior reviews were also searched for relevant eligible research articles describing VM’s feasibility, acceptability, reach, and/or impact when used for SUD-related harm reduction. Data from eligible articles were systematically extracted and summarized.
Results
The search found 45 eligible articles covering 30 separate studies involving 191,242 participants (190,576 VM users; 666 non-users). Most studies were conducted outside of the U.S. (n = 20), focused on individuals who injected drugs (n = 18), and evaluated syringe-dispensing VMs (n = 12). Of the 45 articles, the majority evaluated feasibility (n = 35), followed by acceptability (n = 21), impact (n = 17), and reach (n = 14). The feasibility-assessing articles noted high demand for VM-dispensed items, with usage mostly occurring outside of traditional business hours, and more syringes and HIV self-tests being dispensed compared to some in-person programs. The VMs were generally accepted by target populations, regardless of the items dispensed, and reached high-risk populations. Impact evaluation was limited and based on item dispensed. Seven articles examined the impact of syringe-dispensing VMs and described reductions in syringe sharing (n = 4) and drug use (n = 2), as well as stable or declining rates in drug use-related crime (n = 1). Articles evaluating the impact of HIV self-test-dispensing VMs (n = 3) described HIV detection rates ranging from 1.9% to 17.7%. Two articles reported reduced fatal overdoses after naloxone-dispensing VMs were implemented.
Discussion
VMs show promise as a low-barrier method for reducing SUD-related harm, decreasing health disparities, and engaging hard-to-reach populations. Future implementation science-based research is needed to assess VMs’ impact on individual and community health outcomes, including overdose.
Journal Article