Peugeot Teams Up With 3D Printing Startup for Parts and Possibly Full Cars
Daniel Bentley for Fortune: French carmaker PSA said on Thursday a partnership with a U.S. 3D printing startup would lead to cheaper production of whole vehicle structures as well as parts for its models.
The maker of Peugeot, Citroen and DS cars said it had agreed with Los Angeles-based Divergent 3D to develop metal printing processes for PSA production lines.
Carlos Tavares, PSA’s chief executive, said this could “dramatically scale down the size and scope of our manufacturing footprint” and yield lighter, more profitable vehicles. The carmaker did not quantify any impact on production jobs.
Industries from aerospace to healthcare use 3D printing for the production of metal and plastic components, while elaborate assemblies with moving parts often prove more difficult. Ford is among other carmakers exploring the technology. Cont'd...
Why manufacturing will make or break the future of energy
Lauren Hepler for GreenBiz: From solar panels a decade ago to energy storage today, the history of clean tech is littered with capital-intensive concepts poised to radically alter the relationship between industrialized society and the environment.
But why do these widely heralded breakthroughs always seem to limp along so slowly when it comes to actually hitting the market? The dreaded "valley of death" between conception and commercialization is one increasingly recognized explanation, dooming novel technologies to relegation in never-ending pilot projects as follow-on investment lags.
For Mark Johnson, the Department of Energy's resident innovation expert, the real problem often boils down to production. That is, not just inventing a new energy-centric technologies, but making sure those new tools can be reliably made in a cost-effective manner. Cont'd...
New technologies reshape production lines
LINSEY MILLER & CHRISTOF WEHNER OF ARTESYN EMBEDDED TECHNOLOGIES, originally Published on Embedded Computing Design: Whether people call it Industry 4.0, Industrial Internet of Things (IIoT), or networked production, they are all talking about coming changing paradigms in the industrial network.
Today there are several single-task workstations, manned by humans or robots, which are connected to a higher-level enterprise resource planning (ERP) system. However, that hierarchy is on the cusp of changing massively in the near future to accommodate newer, more intelligent technologies spanning multiple segments of the production line. Cont'd...
How to prepare a business for an Industry 4.0 network
Joe Bombagi for Business Review Europe: The first industrial revolution was based on the use of steam to power machines. The second centred on the use of electricity to supply energy to assembly lines. The third came about with the use of electronics and IT to further automate production.
But all of that is in the past. We are now in the midst of the fourth industrial revolution, known as Industry 4.0, in which the Internet of Things (IoT) is set to overhaul not only business, but also every aspect of modern life. From cars, washing machines, and even clothing, to heart monitors and dams, anything and everything will soon be connected.
As a result, the Industry 4.0 phenomenon is expected to revolutionise all areas within the manufacturing space, connecting all the elements that take part in the production process within the industrial environment: machines, products, systems, and people. The IoT will make today’s organisations more competitive by enabling them to further automate manufacturing processes, and collect and analyse data which they can then use to tailor their products to specific client needs. Cont'd...
Do the benefits of robotics outweigh the heavy demands on infrastructure?
Ben Rossi for Information Age: Robotics has already been deployed in manufacturing to great effect for over a decade, performing delicate and precise tasks with greater accuracy than humans.
But now cutting-edge robots and other smart machines are set to join forces with the rapidly expanding Internet of Things, which Gartner estimates will total 25 billion devices by 2020.
In healthcare, robotic services are already operating pharmacy dispensers and robotic trolleys are now deployed in a growing number of hospitals. In hospitality, robots deliver services such as drinks dispensing and automated trolley deliveries.
Robots have even made their way into education, where they are being deployed successfully as a tutor, tool or peer in learning activities.
But what impact will this large-scale adoption of robotics have on existing networks as they encounter inevitable further strain? Cont'd...
IISc building India's 1st smart factory in Bengaluru
Chethan Kumar for The Times of India: India's first smart factory — moving from automation to autonomy — where machines speak with each other, is being set up in Bengaluru.
A smart factory, armed with data exchange in manufacturing and the Internet of Things (IoT) is the future and experts are calling it revolution Industry 4.0. Reports peg the smart factory industry to touch $215 billion by by 2025 and there has been no major economy in the world that is not embracing it.
And, India's very own smart factory, the first one, is making progress at the Indian Institute of Science's (IISc) Centre for Product Design and Manufacturing (CPDM) with a seed funding from The Boeing Company.
CPDM Chairman Amaresh Chakrabarti, who spoke exclusively to TOI about the project, said: "Yes, it will actually be manufacturing things here. But it will be a scaled down version, we won't have the numbers of an actual factory." As for the funding, he said: "I can only say Boeing is giving us enough to implement the project. I cannot discuss details. But the project is revolutionary. Indian factories now have automation, we've made some progress there, but here, we are talking about a facility that is autonomous, thinking and working on its own." Cont'd...
Industrial digitisation on fast track
The New Indian Express: In a move to build the digital enterprise, the digitisation in industrial sector is set to grow to 65 percent in the next five years as it is a priority of most CEOs in the industry, according to a PwC report.
According to PwC Industry 4.0 report, more than half of the industrial companies in India are using data analytics and over 90 per cent expect data to impact their decision-making in five years.
Globally, digitisation is expected to rise to 72 per cent from 33 per cent, the report noted.
It is also noted that around 39 percent of the companies plan to invest more than 8 percent of their annual revenues in digital programmes in the next five years. Cont'd...
Where do you get the I/O for the IIoT?
Nick Butler, National Instruments for ControlDesign: Data is the heart of all Internet of Things systems, including systems deployed into industrial environments.
When we talk about making the aging electrical grid smarter or the factory of the future more efficient, what we’re really after are insights that can make our equipment and infrastructure smarter and more efficient. And to deliver these incredibly valuable insights, which will result in millions of dollars in savings, uptime or operational efficiency, we need data. Lots of it. We also need complex, computationally intensive algorithms that scour the data to find trends, patterns and anomalies (Figure 1).
While these algorithms and analysis routines are a very important piece of the IIoT puzzle, the best data scientists in the world cannot predict equipment failures without enormous amounts of data. Cont'd...
10 Ways Machine Learning Is Revolutionizing Manufacturing
Louis Columbus for Forbes: Every manufacturer has the potential to integrate machine learning into their operations and become more competitive by gaining predictive insights into production.
Machine learning’s core technologies align well with the complex problems manufacturers face daily. From striving to keep supply chains operating efficiently to producing customized, built- to-order products on time, machine learning algorithms have the potential to bring greater predictive accuracy to every phase of production. Many of the algorithms being developed are iterative, designed to learn continually and seek optimized outcomes. These algorithms iterate in milliseconds, enabling manufacturers to seek optimized outcomes in minutes versus months.
The ten ways machine learning is revolutionizing manufacturing include the following:
How Big Area Additive Manufacturing is Enabling Automotive Microfactories
Ian Wright for Engineering.com: Make no mistake, 3D printing is changing manufacturing.
Although it may take years before we see the full impact of bringing this technology from rapid prototyping to full-scale production, there are already hints of big things to come.
Take Local Motors’ recent purchase of two Big Area Additive Manufacturing (BAAM) systems from Cincinnati Incorporated (CI) as an example. The former company designs, builds and sells custom vehicles out of its US-based microfactories. The latter is a century-old manufacturer of metal fabrication tools and, more recently, BAAM. Cont'd...
How Small Manufacturers Can Leverage Smart Manufacturing
Andrew Waycott for Industry Week: I see three ways in which smaller manufacturers can leverage Smart Manufacturing. The first is the way applicable to all manufacturers—using today’s affordable sensors to get better data, then using that data to fine-tune the process, decrease variability and remove bottlenecks. All of these bring costs down and drive quality up.
Now let’s talk about the other two ways—ways that are specific to the smaller manufacturer.
Smaller manufacturers have the edge in building volumes of one—in other words, customized orders. For many smaller manufacturers, the look is less assembly line and more set of work stations. This means that the operator in a smaller plant typically makes more decisions. It’s a more people-oriented process. Cont'd...
Global Manufacturers Investing Heavily To Take The Manufacturing Floor High-Tech: KPMG Survey
Many devoting significant R&D budget towards robotics;
A quarter say they have already invested in AI and cognitive computing technologies
The Biggest Challenges of Data-Driven Manufacturing
Willy C. Shih and Helmuth Ludwig for Harvard Business Review: The widespread deployment of low-cost sensors and their connection to the internet has generated a great deal of excitement (and hype) about the future of manufacturing. The internet of things (IoT) and industrial internet in the United States, Industrie 4.0 in Germany, and 物"网 (wù lián wăng) in China are all centered on the application of big data and analytics to creating the next generation of manufacturing: using data to reduce costs through next generation sales and operations planning, dramatically improved productivity, supply chain and distribution optimization, and new types of after-sales services. In fact, IoT is at the peak of Gartner’s 2015 hype cycle, which suggests the next phase will be disillusionment, and it will be years before we see real productivity gains.
We believe data-driven manufacturing is indeed the next wave that will drive efficient and responsive production systems. But to get beyond the hype, managers need to understand some underlying challenges and paradigm shifts. While there are a multitude of challenges on the road to successful implementation, we think there are four especially important ones. Cont'd...
German manufacturers take aim at smart factories, mass customization
TOMOHISA TAKEI, Nikkei staff writer: It has been five years since Industry 4.0, the fourth industrial revolution, was first unveiled at the Hannover Messe industrial technology trade fair in Germany.
Industry 4.0 was more of a conceptual model at that time. This year, however, the trade show witnessed an emerging trend toward "smart factories" that can provide mass customization.
On April 25, SEW-Eurodrive's booth at Hannover Messe drew crowds of visitors. The German industrial motor maker demonstrated its automated vehicles for next-generation assembly plants, what it calls the "Lean Smart Factory."
In SEW-Eurodrive's demonstration, about 10 such "smart vehicles" moved about as five workers assembled products. One vehicle approached its target worker, displayed a procedure on its screen and instructed the worker to do the assembly work. After the worker completed the task, the vehicle received the product and moved on to another worker in charge of the next process.
These smart vehicles were connected over a network and programmed at the company factory. But it looked as if the products themselves were driving the vehicles and moved to where the tasks needed to be done. SEW-Eurodrive has already introduced the system at its factory in the southwestern German town of Graben-Neudorf, intending to make individually tailored products in the future. Cont'd...
These Five Exponential Trends Are Accelerating Robotics
Alison E. Berman for Singularity Hub: If you've been staying on top of artificial intelligence news lately, you may know that the games of chess and Go were two of the grand challenges for AI. But do you know what the equivalent is for robotics? It's table tennis. Just think about how the game requires razor sharp perception and movement, a tall order for a machine.
As entertaining as human vs. robot games can be, what they actually demonstrate is much more important. They test the technology's readiness for practical applications in the real world—like self-driving cars that can navigate around unexpected people in a street.
Though we used to think of robots as clunky machines for repetitive factory tasks, a slew of new technologies are making robots faster, stronger, cheaper, and even perceptive, so that they can understand and engage with their surrounding environments. Consider Boston Dynamic’s Atlas Robot, which can walk through snow, move boxes, endure a hefty blow with a hockey stick by an aggressive colleague, and even regain its feet when knocked down. Not too long ago, such tasks were unthinkable for a robot.
At the Exponential Manufacturing conference, robotics expert and director of Columbia University’s Creative Machine Labs, Hod Lipson, examined five exponential trends shaping and accelerating the future of the robotics industry. Cont'd...
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