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...

Robotics, automation, and how a strong network is needed to connect it all up

Manish Sablokk for IoTTech:   Cutting-edge robots and other advanced smart machines are set to be added into the rapidly expanding Internet of Things, which is projected to reach 25 billion devices by 2020. Robotics has already been used in manufacturing to great effect for over a decade, performing delicate and precise tasks with a higher success rate than humans. With advancements such as 'deep learning' robots, delivery drones and ubiquitous knowledge-sharing between machines, widespread robotics adoption is becoming far more feasible. In healthcare, there are already robotic services in operation with automated pharmacy dispensing and robotic trolleys - robots that can navigate between floors and even call the lift using a Wi-Fi sensor. The hospitality sector has also been a keen adopter of robotics to deliver services and in education, robots are being deployed successfully as a tutor, tool or peer in learning activities, providing language, science and technology education.   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...

Method for Calculating Moment Loads on Linear Actuators

With the actual equipment, there are various kinds of equipment conditions and driving conditions for electric actuators and cylinders and thus, it is very difficult to explain all the operating conditions.

Is There a Tomorrow for Manufacturing in the United States?

Operators will soon be able to test and optimize the machine settings for the next product in line in the virtual world before they make the physical change-over.

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...

How Embedded Devices and the Cloud Are Leading a Paradigm Shift in Manufacturing and Production

This cannot be a simple extension of today's processes, but needs to be a complete rethink of how manufacturing and production systems are designed to take full advantage of the cloud and the analytics that it brings to bear.

Logistic companies Swisslog, Dematic, Egemin and Intelligrated have all been Acquired

All these companies are logistics and material handling vendors and times are changing in logistics and fulfillment

Hitachi Begins Development of Factory Automation Platform as a Service Testbed

Kagan Pittman for Engineering.com:  Will the Internet of Things be the future of manufacturing? Global conglomerate Hitachi Group seems to think so. Hitachi recently partnered with Mitsubishi Electric and Intel to receive approval for their Factory Automation Platform as a Service (FA PaaS) Testbed at the Industrial Internet Consortium (IIC), a global non-profit organization. The testbed will operate as a testing platform based on the reference model of IIC to test solutions in controlled scenarios that match real-world conditions, for the ultimate purpose of connecting manufacturing sites with head offices in order to streamline their operations. Hitachi hopes to use the FA PaaS to respond to what they see as a market rapidly growing and demanding faster product development, market introduction, quality improvements and shorter lead times.   Cont'd...

What Super-Efficient Manufacturing Looks Like

The Tesla factory in Fremont, California, and the Gigafactory in Nevada are monuments to science and progress.

Schneider Electric's three steps for implementing Industry 4.0

Eric Emin Wood for IT World Canada:  Manufacturing companies with visions of incorporating the latest automated, cloud-based, analytical tech into their production process need to recognize the value of a measured approach, an original equipment manufacturing (OEM) veteran says. Martin Stephenson, vice president of process automation for OEM Schneider Electric Canada, which specializes in power management, building management, datacentres, and process and automation control, says that while some firms are equipped to embrace the change right away, others might find that implementing what he calls “Industry 4.0” isn’t a good fit for them at all. “Just because you can, doesn’t mean you should,” he says. “Customers need to have a truthful conversation with themselves and say, ‘How do we manage what we do now? Are we ready for this step? … Do we have the right infrastructure? Do we have the right cybersecurity in place?’ There are a lot of discussions to be had before this leap of faith happens.”   Cont'd...

Rise in Robotics Requires New Tax Approach, EU Report Warns

Linda A. Thompson for Bloomberg:  European lawmakers warn that the growing use of robots and artificial intelligence may cause job losses across the continent, threatening to result in plummeting tax revenues if current tax frameworks aren't revised to account for the rise of the robotic workforce. Practitioners told Bloomberg BNA that taxing robots as “electronic persons,” as the EU contemplates in a recent report, would hinder innovation and that other ways of taxing the value that robotics create should be explored. The recent European Parliament Committee on Legal Affairs draft reportrecommends the European Commission adopt a resolution to require companies to report on “the extent and proportion of the contribution of robotics and AI to the economic results of a company for the purpose of taxation and social security contributions.” Its first paragraph references Frankenstein, and comes amid mounting concerns that the rise in automation and artificial intelligence in the workplace will fundamentally alter economies, destroy jobs and jeopardize social welfare programs such as social security.   Cont'd...

China's Midea buys nearly half of German robotics firm Kuka

The Star:  Chinese appliances giant Midea moved a step closer to fulfilling its ambition to acquire German industrial robotics firm Kuka with two weekend deals raising its stake to nearly a majority.  Two of Kuka’s biggest German shareholders – technology company Voith and entrepreneur Friedhelm Loh – said they had decided to take up Midea’s offer of €115 (RM512) per share and sell their stakes.  German news agency DPA reported that Voith had agreed to sell its stake of 25.1% for €1.2bil (RM5.34bil).  And Loh told the business daily Handelsblatt he had decided to sell his stake of 10% for nearly €500mil (RM2.22bil).  Combined with its existing holding of 13.5% in Kuka, the two purchases mean Midea now holds 48.5%, or not far from the outright majority, in the Augsburg-based robot builder.   Cont'd.. .

Understanding Industry 4.0

Process and device will become inseparable. This is the direction we're heading in and it is all powered by the capabilities of Industry 4.0.

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:

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